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Hindawi Publishing CorporationJournal of ClimatologyVolume 2013 Article ID 680565 16 pageshttpdxdoiorg1011552013680565
Research ArticleClimatic Variation at Thumba Equatorial RocketLaunching Station India
K V S Namboodiri P K Dileep and Koshy Mammen
Meteorology Facility Thumba Equatorial Rocket Launching Station (TERLS) Vikram Sarabhai Space Centre (VSSC)Indian Space Research Organization Thiruvananthapuram 695 022 India
Correspondence should be addressed to K V S Namboodiri sambhukvyahoocom
Received 22 June 2013 Accepted 25 September 2013
Academic Editors A V Eliseev and E Paoletti
Copyright copy 2013 K V S Namboodiri et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited
Long-term (45 years) diversified surface meteorological records from Thumba Equatorial Rocket Launching Station (TERLS)India were collected and analysed to study the long-term changes in the overall climatology climatology pertained to a particularobservational timemeandaily climatology in temperature inter-annual variability in temperature interannual variability in surfacepressure and rainfall for themain Indian seasonsmdashSouthWest andNorth Eastmonsoons and inter-annualmeanmonthly anomalystructure in temperature Results on various analyses show strong and vivid features contributed by climate change for this SouthPeninsular Indian Arabian Sea Coastal Station and this paper may be a first time venture which discusses climate change impartedperturbations in several meteorological parameters in different time domains like a specific time daily monthly and interannuallyover a station Being a coastal rocket launching station climatic change information is crucial for long-term planning of its facilitiesas well as for various rocket range operational demands
1 Introduction
Climate change refers to a statistically strong and significantvariation in either the average state of the climate or in itsvariability persisting for an extended period typically indecades or longer Short-period oscillations are statisticallyinsignificant in the scenario of long-term climate changecontext Climate change may be due to natural internalprocesses on earth (atmospheric seismic volcanic andoceanic) external forces (variation in solar activity rotationand revolution of earth) and more recently anthropogenicactivities It is now well established that anthropogenicactivities cause intensification of the greenhouse effect andthereby contribute to the climate change The paper byOreskes [1] highlighted the listings in the ISI database onclimate change from several abstracts published in refereedscientific journals between 1993 and 2003
In India the first time document on the concern ofgreenhouse effect and possible mitigation measures waspublished in the Science Reporter CSIR by Ayyar [2]Several papers were published in a special session in Current
Science (volume 90 2006) focussing the concerns over thesocioeconomic and scientific aspects attributed to climatechange on Indian scenario To develop high-resolution cli-mate change simulations over the Indian region ProvidingRegional Climates for Impact Studies (PRECIS) modellingsystem was applied [3] and it was observed that the warmingis monotonously widespread over India with substantialspatial differences in the projected rainfall changes
Different data sets have been used in order to examine themonotonic change in the level of global temperature by vari-ous investigators [4ndash7] From the diversified methodologiesadopted it is observed that the global surface temperaturehas risen by 074∘C with an error of plusmn018∘C when estimatedby a linear trend over the last 100 years (1906ndash2005) and007∘C plusmn 002∘C per decade An executive summary is madeavailable by Solomon et al [8] on climate change in the fourthassessment report of the Intergovernmental Panel on ClimateChange (IPCC) Climate change features are local or regionalhighly influenced by agricultural practices urbanisationheat island effect changing irrigation aerosol modificationsdesertification deforestation and decay processes of organic
2 Journal of Climatology
materials [9ndash14] Long-term changes in maximum temper-ature minimum temperature and their range have beenanalyzed over two stations in Cyprus by Price et al [15] whoestablished a reduction in range and thereby a possibility inincreased cloud cover and tropospheric aerosols Recentlyseasonal variability in mean sea level pressure extremes overthe 11 zones of India and adjoining sea area has been studiedby Singh et al [16]
In the present paper features on surface climate changeoverThumba Equatorial Rocket Launching Station (TERLS)a coastal station near the South tip of Peninsular Indiaare critically examined TERLS was established as an inter-national rocket launching station dedicated to the UnitedNations for conducting meteorological and sounding rocketexperiments on the geomagnetic equator Meteorologygroup TERLS has one of the heaviest responsibilities inthe range to cater (i) weather forecasting and data needs ofsounding rocket launch operations (in planning pad opera-tions and launching) (ii) climatological briefing to workingcrews including scientists to plan experiments (iii) Organisevarious met Observations (iv) processing analyses storageand retrieval of various met data (Class I surface observa-tory autoweather stations sonic anemometers 50m micrometeorological flux tower facility meteorological balloonlaunches rocket chaff derived wind data) and provide thedata for users demand For the planning of a scientificmission the variability of climate is very crucial and therebythe importance of the present study on the climate changeperspective Importance of weather factors affecting rocketoperations can be found elsewhere in detail [17 18] Steadyincrease in temperature anomaly at different levels in thetroposphere over TERLSwas investigated and documented inthe Space research in India [19] Joseph and Simon [20] haveinvestigated weakening trend of the South West monsooncurrent through Peninsular India Dash et al [21] reportedthe decreasing frequency of monsoon depressions over theIndian region and Krishnakumar et al [22] have analysedsignificant decrease in South West monsoon rainfall whileincrease in post monsoon season over the whole KeralaState (also a meteorological subdivision) India From thevoluminous data bank the present study analyses dailymonthly seasonal and interannual variability on differentmeteorological parameters based on both eye reading instru-ments and non-instrumental practices in cloud and visibil-ity observations as per World Meteorological Organization(WMO) practices Till the inception of long-term unin-terrupted data collection through instrument-based cloudand visibility measurements data collection from such non-instrumental means solely vested on conventional methodsin surface meteorological observations adopted worldwide isto be accepted for a reasonable climatology extraction Thepresent work examines the imprints made by the climaticchange on severalmeteorological parameters in different timedomains like a specific time daily monthly and interannu-ally unlike the climate change associated variations on a singlemeteorological parameter like temperature or rainfall alonehave dealt in most of the climatic change studies
N Indiaoutline map
China(Tibet)Nepal
Pakistan
Bhutan
Arabian SeaBay of Bengal
BangladeshMyanmar
Thumba (8∘32998400998400N76∘52998400998400 67 amsl)E
Figure 1 Location shows the class-I surface meteorological obser-vatory at Thumba
2 Data and Methodology
A class I surface meteorological observatory was establishedat TERLS (8∘3210158401015840N76∘ 5210158401015840E 67 amsl) by India Meteorolog-ical Department (IMD) approximately 70m away from thecoastline of the Arabian Sea coast (Figure 1) TERLS is situ-ated hardly 8 km West North West of Thiruvananthapuramthe capital city of the Kerala state of India Various meteo-rological data from 0830 IST (Indian Standard Time IST =GMT + 0530 hr) observations for a period of 45 years (1964ndash2008) except for pressure where it is hourly data (1973ndash2008) are used in order to investigate changes encounteredinmeteorological parameters due to climate changeThe dataused are obtained from the following measurements at 0830IST (1964ndash2008) namely (i) maximum temperature (past24 hr reported at 0830 IST) (ii) minimum temperature (past24 hr reported at 0830 IST) (iii) past 24 hr rainfall (reportedat 0830 IST) (iv) dry-bulb temperature at 0830 IST (v) wet-bulb temperature at 0830 IST (vi) relative humidity at 0830IST (vii) soil temperature at 0830 IST (viii) non-instrumentaleye observations on clouds and visibility at 0830 IST (ix)wind speed and direction at 0830 IST and (x) hourly surfacepressure (1973ndash2008) Table 1 provides details on variousinstrumentation exposure maintenance data span and thelowest and the highest in maximum absolute error valuesamong various monthly statistics from 1964 to 2008
The above mentioned 45 years of data have partitionedinto two climatological slots of 30 years each namely 1964to 1993 and from 1979 to 2008 respectively called as pastdata for the former and present data for the later Maximumabsolute error values in the total data set (1962ndash2008) are the
Journal of Climatology 3
Table1Detailson
instrumentatio
ndatausedand
theo
bservedvaria
tionin
maxim
umabsoluteerrorinmon
thlymeanused
inthed
iscussio
nof
climatolog
yat0830
IST
Sno
Parameter
Datau
sed
Instrument
Height(agl)
(cm)
Expo
sure
Lowestand
high
est
maxim
umabsolute
error
Make
Maintenance
and
calib
ratio
nprotocol
1Maxim
umtemperature
(∘ C)
1964
ndash2008
Maxim
umthermom
eter
(Mercury-in
-glassthermom
eter)
122
Stevensonscreen
0087to
0132(∘ C
)IM
D
Daily
weeklymon
thly
halfyearly
annu
aland
perio
dic
2Minim
umtemperature
(∘ C)
1964
ndash2008
Minim
umthermom
eter
(spirit-in
-glass)
122
Stevensonscreen
0061to0145(∘ C
)IM
D
3Dry-bulbtemperature
(∘ C)
1964
ndash2008
Drybu
lbthermom
eter
(mercury-in
-glassthermom
eter)
122
Stevensonscreen
0088to
0125(∘ C
)IM
D
4Ra
infall(m
m)
Non
recordingrain
gaugeo
fcollector
area
20square
cm0
Groun
d
4Wet-bulbtemperature
(∘ C)
1964
ndash2008
Wet-bulbthermom
eter
122
Stevensonscreen
006
to0146(∘ C
)IM
D
5Re
lativeh
umidity
()
1964
ndash2008
Drybu
lbthermom
eterw
etbu
lbthermom
eterand
psychrom
eter
table
122
Stevensonscreen
0512to
0916(
)IM
D
6Soiltemperature
(∘ C)
1964
ndash2008
Soilthermom
eter
inmetallic
tube
minus5
0201to0261(∘
C)IM
D
7Pressure
(mb)
1974ndash2008
Aneroid
barograph(diaph
ragm
type)
670
mam
slIM
D
8Windspeed
1964
ndash2008
Anemom
eter
300
0043to
024
(ms)
IMDD
ynalab
9Winddirection
1964
ndash2008
Windvane
300
With
in1d
egree
IMDD
ynalab
4 Journal of Climatology
summation of errors [23] of past and present data sets Indi-vidual error is computed as the ratio of standard deviation tothe number of observations of a particular data set Trenberth[24] has established the climate shift as a prominent upwardtrend in temperature after 1976 In order to include thisobservation influence half portion (15 years) period from1979 to 1993 ismade common in the latter half of past data andin the former part of present data The difference obtainedamong present data and past data has been represented as Δin the discussions throughout To see genuineness in findingsattributed to climate change Δ values are compared withabsolute errors so as to see that Δ do not fall within absoluteerrors of corresponding meteorological parameters
3 Results and Discussion
31 Δ Climatology of the Past 24 hr Observations Maximumtemperature minimum temperature and 24 hr accumulatedrainfall are the only 3meteorological parameters registered at0830 IST having effect of the past 24 hr variability behaviourClimatology for various parameters has been derived for pastdata and present data and presented in Tables 2 3 4 and5 in which months that constitute the different seasons arementioned Derived Δ values are also incorporated in theabove tables Comparison between past data and present datamaximum temperature climatology shows marked increasein present data climatology in relation to the past datacounterpart and thereby positive values alone are observedin Δ Δ values vary from +001∘C in the North East monsoon(NE monsoon) month November to +043∘C in the pre-South West monsoon (SW monsoon) month May The NEmonsoon season comprises October and November whereasthe four months from June to September designate SWmonsoon season which are the main two Indian seasonsIn minimum temperature all Δ values are positive withmaximum value in the winter month February with a value+053∘C The observations among maximum and minimumtemperature climatology derived in past data and presentdata along with Δ values can infer that the minimum dailytemperatures have generally increased at a larger rate thanthe maximum daily temperatures Karl et al [25] studied thepossible cause of increased urbanisation effects and Rebetezand Beniston [26] justified the result of increased cloud coverin the large increase in minimum temperature and smallincrease in maximum temperatures
From each individual daily maximum and minimumtemperature mean daily temperatures ((maximum temper-ature + minimum temperature)2) are computed and furtherderive the past data and present data climatologies of meantemperatures Only positive Δ values are observed through-out the year which clearly indicate that the temperature overthis tropical coastal station is increasing Temperature clima-tologies have shown the tropical monsoonal characteristic oftwo maxima and two minima in monthly variation
The diurnal temperature range is calculated from indi-vidual maximum and minimum temperature value andcalculated past data and present data temperature rangeclimatologies Range climatologies are featured by annualvariation The prominent feature of negative Δ values in
range is seen which shows that the difference betweenmaximum temperature and minimum temperature in a dayis decreasing Also the larger rate of increase in minimumtemperatures than maximum temperatures results in thesenegative Δ values in the diurnal temperature range
The rainfall Δ shows decrease in rainfall in present datafor the summermonthsApril andMayWell-marked negativeΔ values of about 21mm are observed in the SW monsoonmonths (JunendashAugust) An increase in rainfall activity isdetected in the SW monsoon month September and in theNE monsoon months October and November (debted tomonsoonal climate) with maximum value of +3650mm inOctober The station weather is dominated by convectivemesoscale systems during the NE monsoon Probably thisinvestigation poses the doubt about whether suchmeso-scaleweather phenomena like thunderstorm formations are onincreasing trend duringNEMonsoon and thereby an increasein Δ
32 Climatology of a Particular Observation at 0830 ISTAnalyses are carried out on different parameters collected at0830 IST Δ in dry bulb temperature wet bulb temperatureand dew point temperature obtained from the two climatolo-gies show only positive values It ranges from +060∘C in Julyto +101∘C in January for dry bulb temperature Variations inΔ among the SW monsoon months are less in general for allthe above three variables even though a maximum value inΔ is observed in dry bulb temperature The less variation ofwet bulb and dew point temperatures may be as a result ofmoisture laden atmosphere during the period which impartscorresponding variations in the moisture parameters like wetbulb temperature and dew point temperature
Station relative humidity values at 0830 IST show morethan 70 throughout the year with maximum in SW mon-soon of the order 89 Low negative values in Δ relativehumidity are detected as the air becomes drier in present datacompared to past As the air is getting dried both dew pointand the wet bulb temperatures are supposed to show negativeΔ values but the feature is not detectedThis may be inferredas the dry bulb temperature is the key parameter in elevatingΔ values of both dew point and wet bulb temperatures andthe meagre relative humidity decrease in present data thanpast data is insignificant to impartΔ changes in dewpoint andwet bulb temperatures Climatologies of RH also have showntwomaxima and twominimawhereas the secondaryminimaaround the NE monsoon is shallow in character
Significant positive Δ values are observed among the twoclimatologies in soil temperature with a low value of +099∘Cto a high of +235∘C in July and January respectively Perhapsthe Δ increase observed in the winter months January andFebruary may contribute reduction in radiational coolingwhich leads to a reduction in fog formation probability overthe station Soil temperature climatologies also have showntropical monsoonal type with two maxima and minima
Wind speed (both scalar and resultant) is decreased inpresent climatologies Mathematically resultant wind speedshall be determined as the square root of the sum of thesquares of zonal and meridional wind components Theencountered Δ values that rise to a maximum value of
Journal of Climatology 5
Table2Clim
atolog
yandΔof
maxim
umtemperaturem
inim
umtemperaturem
eandaily
temperaturem
eanrangeintemperatureand
mon
thlyrainfall
Mon
thMaxim
umtemperature∘
CMinim
umtemperature∘
CMeandaily
temperature∘
CMeanrangeintemperature∘
CMon
thlyrainfallmm
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
3259
3276
+017
2130
2158
+028
2694
2716
+022
1129
1117
minus012
1180
1110
minus070
FEB
3312
3332
+020
2189
2242
+053
2751
2787
+036
1124
1091minus033
1620
1640
+020
MAR
3384
3407
+023
2375
2413
+038
2878
2909
+031
1006
992
minus014
3320
3480
+160
APR
3425
3441
+016
2524
2551
+027
2976
2995
+019
905
888
minus017
10410
9940minus470
MAY
3303
3346
+043
2514
2550
+036
2912
2948
+036
797
796
minus001
1792
016580minus1340
JUN
3036
3071
+035
2399
2436
+037
2720
2753
+033
643
635
minus008
29270
27220minus2050
JUL
2938
2948
+010
2336
2379
+043
2638
2663
+025
603
568
minus035
20300
1813
0minus2170
AUG
2927
2960
+033
2339
2380
+041
2635
2670
+035
592
579
minus013
1415
012090minus2060
SEP
3034
3070
+036
2368
2400
+032
2704
2734
+030
671
667
minus004
15820
1710
0+1280
OCT
3119
3153
+034
2374
2404
+030
2750
2776
+026
753
744
minus009
20490
2414
0+3
650
NOV
3176
3177
+001
2321
2357
+036
2748
2767
+019
853
820
minus033
16680
17070
+390
DEC
3230
3256
+026
2244
2244
+000
2735
2750
+015
983
1011
+028
6660
5370minus1290
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
6 Journal of Climatology
Table3Clim
atolog
yandΔof
dry-bu
lbtemperaturew
etbu
lbtemperaturedew
pointtem
peraturerelativeh
umidityand
soiltemperature
Mon
thDry-bulbtemperature
(0830IST)∘
CWet-bulbtemperature
(0830IST)∘
CDew
pointtem
perature
(0830IST)∘
CRe
lativeh
umidity
()
(0830IST)
Soiltemperature
(0830IST)∘
C1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
2606
2707
+101
2233
2290
+057
2035
2069
+034
7136
6885minus251
2903
3138
+235
FEB
2677
2771
+094
2304
2355
+051
2112
2143
+031
7176
6941minus235
3041
3254
+213
MAR
2831
2920
+089
2458
2494
+036
2281
2294
+013
7255
6953
minus302
3280
3425
+145
APR
2929
3000
+071
2609
2630
+021
2471
2472
+001
7656
7361minus295
3373
3511
+138
MAY
2870
2943
+073
2612
2643
+031
2502
2517
+015
8094
7833
minus261
3246
3416
+170
JUN
2661
2733
+072
2520
2557
+037
2455
2481
+026
8851
8643minus208
2955
3099
+144
JUL
2576
2636
+060
2455
2488
+033
2395
2421
+026
8980
8803minus17
72901
3000
+099
AUG
2590
2660
+070
2460
2496
+036
2397
2422
+025
8940
8698minus242
2960
3096
+136
SEP
2662
2737
+075
2484
2521
+037
2402
2425
+023
8577
8345minus232
3110
3223
+113
OCT
2681
2759
+078
2490
2533
+043
2402
2432
+030
8501
8261minus240
3140
3245
+105
NOV
2690
2763
+073
2440
2486
+046
2327
2358
+031
8084
7935minus14
93099
3202
+103
DEC
2670
2759
+089
2335
2372
+037
2161
2174
+013
7448
7139
minus309
3052
3209
+157
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
Journal of Climatology 7
Table4Clim
atolog
yandΔof
visib
ilitycodelow
cloud
highclo
udand
totalcloud
Mon
thVisib
ilitycode
(0830IST)
Lowclo
ud(0830IST)
Middlec
loud
(0830IST)
Highclo
ud(0830IST)
Totalcloud
(0830IST)
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
9679
9698
+019
055
047
minus008
081
078
minus003
118
135
+017
251
253
+002
FEB
9675
9691
+016
048
047
minus001
066
058
minus008
108
116
+008
221
217
minus004
MAR
9661
9688
+027
062
071
+009
054
037
minus017
106
121
+015
220
224
+004
APR
9677
9686
+009
125
157
+032
100
087
minus013
172
179
+007
391
394
+003
MAY
9670
9668minus002
202
208
+006
145
143minus002
156
164
+008
487
468
minus019
JUN
9626
9643
+017
286
284
minus002
231
237
+006
116
149
+033
596
590
minus006
JUL
9610
9637
+027
274
274
+000
250
282
+032
126
167
+041
596
606
+010
AUG
9641
9658
+017
227
238
+011
231
228
minus003
131
186
+055
563
568
+005
SEP
9648
9663
+015
216
215
minus001
163
162minus001
134
162
+028
493
490
minus003
OCT
9676
9670minus006
175
196
+021
207
214
+007
129
173
+044
492
506
+014
NOV
9668
9665minus003
144
155
+011
186
194
+008
126
172
+046
440
465
+025
DEC
9681
9679minus002
101
091
minus010
140
115minus025
120
140
+020
356
325
minus031
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
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ClimatologyJournal of
2 Journal of Climatology
materials [9ndash14] Long-term changes in maximum temper-ature minimum temperature and their range have beenanalyzed over two stations in Cyprus by Price et al [15] whoestablished a reduction in range and thereby a possibility inincreased cloud cover and tropospheric aerosols Recentlyseasonal variability in mean sea level pressure extremes overthe 11 zones of India and adjoining sea area has been studiedby Singh et al [16]
In the present paper features on surface climate changeoverThumba Equatorial Rocket Launching Station (TERLS)a coastal station near the South tip of Peninsular Indiaare critically examined TERLS was established as an inter-national rocket launching station dedicated to the UnitedNations for conducting meteorological and sounding rocketexperiments on the geomagnetic equator Meteorologygroup TERLS has one of the heaviest responsibilities inthe range to cater (i) weather forecasting and data needs ofsounding rocket launch operations (in planning pad opera-tions and launching) (ii) climatological briefing to workingcrews including scientists to plan experiments (iii) Organisevarious met Observations (iv) processing analyses storageand retrieval of various met data (Class I surface observa-tory autoweather stations sonic anemometers 50m micrometeorological flux tower facility meteorological balloonlaunches rocket chaff derived wind data) and provide thedata for users demand For the planning of a scientificmission the variability of climate is very crucial and therebythe importance of the present study on the climate changeperspective Importance of weather factors affecting rocketoperations can be found elsewhere in detail [17 18] Steadyincrease in temperature anomaly at different levels in thetroposphere over TERLSwas investigated and documented inthe Space research in India [19] Joseph and Simon [20] haveinvestigated weakening trend of the South West monsooncurrent through Peninsular India Dash et al [21] reportedthe decreasing frequency of monsoon depressions over theIndian region and Krishnakumar et al [22] have analysedsignificant decrease in South West monsoon rainfall whileincrease in post monsoon season over the whole KeralaState (also a meteorological subdivision) India From thevoluminous data bank the present study analyses dailymonthly seasonal and interannual variability on differentmeteorological parameters based on both eye reading instru-ments and non-instrumental practices in cloud and visibil-ity observations as per World Meteorological Organization(WMO) practices Till the inception of long-term unin-terrupted data collection through instrument-based cloudand visibility measurements data collection from such non-instrumental means solely vested on conventional methodsin surface meteorological observations adopted worldwide isto be accepted for a reasonable climatology extraction Thepresent work examines the imprints made by the climaticchange on severalmeteorological parameters in different timedomains like a specific time daily monthly and interannu-ally unlike the climate change associated variations on a singlemeteorological parameter like temperature or rainfall alonehave dealt in most of the climatic change studies
N Indiaoutline map
China(Tibet)Nepal
Pakistan
Bhutan
Arabian SeaBay of Bengal
BangladeshMyanmar
Thumba (8∘32998400998400N76∘52998400998400 67 amsl)E
Figure 1 Location shows the class-I surface meteorological obser-vatory at Thumba
2 Data and Methodology
A class I surface meteorological observatory was establishedat TERLS (8∘3210158401015840N76∘ 5210158401015840E 67 amsl) by India Meteorolog-ical Department (IMD) approximately 70m away from thecoastline of the Arabian Sea coast (Figure 1) TERLS is situ-ated hardly 8 km West North West of Thiruvananthapuramthe capital city of the Kerala state of India Various meteo-rological data from 0830 IST (Indian Standard Time IST =GMT + 0530 hr) observations for a period of 45 years (1964ndash2008) except for pressure where it is hourly data (1973ndash2008) are used in order to investigate changes encounteredinmeteorological parameters due to climate changeThe dataused are obtained from the following measurements at 0830IST (1964ndash2008) namely (i) maximum temperature (past24 hr reported at 0830 IST) (ii) minimum temperature (past24 hr reported at 0830 IST) (iii) past 24 hr rainfall (reportedat 0830 IST) (iv) dry-bulb temperature at 0830 IST (v) wet-bulb temperature at 0830 IST (vi) relative humidity at 0830IST (vii) soil temperature at 0830 IST (viii) non-instrumentaleye observations on clouds and visibility at 0830 IST (ix)wind speed and direction at 0830 IST and (x) hourly surfacepressure (1973ndash2008) Table 1 provides details on variousinstrumentation exposure maintenance data span and thelowest and the highest in maximum absolute error valuesamong various monthly statistics from 1964 to 2008
The above mentioned 45 years of data have partitionedinto two climatological slots of 30 years each namely 1964to 1993 and from 1979 to 2008 respectively called as pastdata for the former and present data for the later Maximumabsolute error values in the total data set (1962ndash2008) are the
Journal of Climatology 3
Table1Detailson
instrumentatio
ndatausedand
theo
bservedvaria
tionin
maxim
umabsoluteerrorinmon
thlymeanused
inthed
iscussio
nof
climatolog
yat0830
IST
Sno
Parameter
Datau
sed
Instrument
Height(agl)
(cm)
Expo
sure
Lowestand
high
est
maxim
umabsolute
error
Make
Maintenance
and
calib
ratio
nprotocol
1Maxim
umtemperature
(∘ C)
1964
ndash2008
Maxim
umthermom
eter
(Mercury-in
-glassthermom
eter)
122
Stevensonscreen
0087to
0132(∘ C
)IM
D
Daily
weeklymon
thly
halfyearly
annu
aland
perio
dic
2Minim
umtemperature
(∘ C)
1964
ndash2008
Minim
umthermom
eter
(spirit-in
-glass)
122
Stevensonscreen
0061to0145(∘ C
)IM
D
3Dry-bulbtemperature
(∘ C)
1964
ndash2008
Drybu
lbthermom
eter
(mercury-in
-glassthermom
eter)
122
Stevensonscreen
0088to
0125(∘ C
)IM
D
4Ra
infall(m
m)
Non
recordingrain
gaugeo
fcollector
area
20square
cm0
Groun
d
4Wet-bulbtemperature
(∘ C)
1964
ndash2008
Wet-bulbthermom
eter
122
Stevensonscreen
006
to0146(∘ C
)IM
D
5Re
lativeh
umidity
()
1964
ndash2008
Drybu
lbthermom
eterw
etbu
lbthermom
eterand
psychrom
eter
table
122
Stevensonscreen
0512to
0916(
)IM
D
6Soiltemperature
(∘ C)
1964
ndash2008
Soilthermom
eter
inmetallic
tube
minus5
0201to0261(∘
C)IM
D
7Pressure
(mb)
1974ndash2008
Aneroid
barograph(diaph
ragm
type)
670
mam
slIM
D
8Windspeed
1964
ndash2008
Anemom
eter
300
0043to
024
(ms)
IMDD
ynalab
9Winddirection
1964
ndash2008
Windvane
300
With
in1d
egree
IMDD
ynalab
4 Journal of Climatology
summation of errors [23] of past and present data sets Indi-vidual error is computed as the ratio of standard deviation tothe number of observations of a particular data set Trenberth[24] has established the climate shift as a prominent upwardtrend in temperature after 1976 In order to include thisobservation influence half portion (15 years) period from1979 to 1993 ismade common in the latter half of past data andin the former part of present data The difference obtainedamong present data and past data has been represented as Δin the discussions throughout To see genuineness in findingsattributed to climate change Δ values are compared withabsolute errors so as to see that Δ do not fall within absoluteerrors of corresponding meteorological parameters
3 Results and Discussion
31 Δ Climatology of the Past 24 hr Observations Maximumtemperature minimum temperature and 24 hr accumulatedrainfall are the only 3meteorological parameters registered at0830 IST having effect of the past 24 hr variability behaviourClimatology for various parameters has been derived for pastdata and present data and presented in Tables 2 3 4 and5 in which months that constitute the different seasons arementioned Derived Δ values are also incorporated in theabove tables Comparison between past data and present datamaximum temperature climatology shows marked increasein present data climatology in relation to the past datacounterpart and thereby positive values alone are observedin Δ Δ values vary from +001∘C in the North East monsoon(NE monsoon) month November to +043∘C in the pre-South West monsoon (SW monsoon) month May The NEmonsoon season comprises October and November whereasthe four months from June to September designate SWmonsoon season which are the main two Indian seasonsIn minimum temperature all Δ values are positive withmaximum value in the winter month February with a value+053∘C The observations among maximum and minimumtemperature climatology derived in past data and presentdata along with Δ values can infer that the minimum dailytemperatures have generally increased at a larger rate thanthe maximum daily temperatures Karl et al [25] studied thepossible cause of increased urbanisation effects and Rebetezand Beniston [26] justified the result of increased cloud coverin the large increase in minimum temperature and smallincrease in maximum temperatures
From each individual daily maximum and minimumtemperature mean daily temperatures ((maximum temper-ature + minimum temperature)2) are computed and furtherderive the past data and present data climatologies of meantemperatures Only positive Δ values are observed through-out the year which clearly indicate that the temperature overthis tropical coastal station is increasing Temperature clima-tologies have shown the tropical monsoonal characteristic oftwo maxima and two minima in monthly variation
The diurnal temperature range is calculated from indi-vidual maximum and minimum temperature value andcalculated past data and present data temperature rangeclimatologies Range climatologies are featured by annualvariation The prominent feature of negative Δ values in
range is seen which shows that the difference betweenmaximum temperature and minimum temperature in a dayis decreasing Also the larger rate of increase in minimumtemperatures than maximum temperatures results in thesenegative Δ values in the diurnal temperature range
The rainfall Δ shows decrease in rainfall in present datafor the summermonthsApril andMayWell-marked negativeΔ values of about 21mm are observed in the SW monsoonmonths (JunendashAugust) An increase in rainfall activity isdetected in the SW monsoon month September and in theNE monsoon months October and November (debted tomonsoonal climate) with maximum value of +3650mm inOctober The station weather is dominated by convectivemesoscale systems during the NE monsoon Probably thisinvestigation poses the doubt about whether suchmeso-scaleweather phenomena like thunderstorm formations are onincreasing trend duringNEMonsoon and thereby an increasein Δ
32 Climatology of a Particular Observation at 0830 ISTAnalyses are carried out on different parameters collected at0830 IST Δ in dry bulb temperature wet bulb temperatureand dew point temperature obtained from the two climatolo-gies show only positive values It ranges from +060∘C in Julyto +101∘C in January for dry bulb temperature Variations inΔ among the SW monsoon months are less in general for allthe above three variables even though a maximum value inΔ is observed in dry bulb temperature The less variation ofwet bulb and dew point temperatures may be as a result ofmoisture laden atmosphere during the period which impartscorresponding variations in the moisture parameters like wetbulb temperature and dew point temperature
Station relative humidity values at 0830 IST show morethan 70 throughout the year with maximum in SW mon-soon of the order 89 Low negative values in Δ relativehumidity are detected as the air becomes drier in present datacompared to past As the air is getting dried both dew pointand the wet bulb temperatures are supposed to show negativeΔ values but the feature is not detectedThis may be inferredas the dry bulb temperature is the key parameter in elevatingΔ values of both dew point and wet bulb temperatures andthe meagre relative humidity decrease in present data thanpast data is insignificant to impartΔ changes in dewpoint andwet bulb temperatures Climatologies of RH also have showntwomaxima and twominimawhereas the secondaryminimaaround the NE monsoon is shallow in character
Significant positive Δ values are observed among the twoclimatologies in soil temperature with a low value of +099∘Cto a high of +235∘C in July and January respectively Perhapsthe Δ increase observed in the winter months January andFebruary may contribute reduction in radiational coolingwhich leads to a reduction in fog formation probability overthe station Soil temperature climatologies also have showntropical monsoonal type with two maxima and minima
Wind speed (both scalar and resultant) is decreased inpresent climatologies Mathematically resultant wind speedshall be determined as the square root of the sum of thesquares of zonal and meridional wind components Theencountered Δ values that rise to a maximum value of
Journal of Climatology 5
Table2Clim
atolog
yandΔof
maxim
umtemperaturem
inim
umtemperaturem
eandaily
temperaturem
eanrangeintemperatureand
mon
thlyrainfall
Mon
thMaxim
umtemperature∘
CMinim
umtemperature∘
CMeandaily
temperature∘
CMeanrangeintemperature∘
CMon
thlyrainfallmm
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
3259
3276
+017
2130
2158
+028
2694
2716
+022
1129
1117
minus012
1180
1110
minus070
FEB
3312
3332
+020
2189
2242
+053
2751
2787
+036
1124
1091minus033
1620
1640
+020
MAR
3384
3407
+023
2375
2413
+038
2878
2909
+031
1006
992
minus014
3320
3480
+160
APR
3425
3441
+016
2524
2551
+027
2976
2995
+019
905
888
minus017
10410
9940minus470
MAY
3303
3346
+043
2514
2550
+036
2912
2948
+036
797
796
minus001
1792
016580minus1340
JUN
3036
3071
+035
2399
2436
+037
2720
2753
+033
643
635
minus008
29270
27220minus2050
JUL
2938
2948
+010
2336
2379
+043
2638
2663
+025
603
568
minus035
20300
1813
0minus2170
AUG
2927
2960
+033
2339
2380
+041
2635
2670
+035
592
579
minus013
1415
012090minus2060
SEP
3034
3070
+036
2368
2400
+032
2704
2734
+030
671
667
minus004
15820
1710
0+1280
OCT
3119
3153
+034
2374
2404
+030
2750
2776
+026
753
744
minus009
20490
2414
0+3
650
NOV
3176
3177
+001
2321
2357
+036
2748
2767
+019
853
820
minus033
16680
17070
+390
DEC
3230
3256
+026
2244
2244
+000
2735
2750
+015
983
1011
+028
6660
5370minus1290
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
6 Journal of Climatology
Table3Clim
atolog
yandΔof
dry-bu
lbtemperaturew
etbu
lbtemperaturedew
pointtem
peraturerelativeh
umidityand
soiltemperature
Mon
thDry-bulbtemperature
(0830IST)∘
CWet-bulbtemperature
(0830IST)∘
CDew
pointtem
perature
(0830IST)∘
CRe
lativeh
umidity
()
(0830IST)
Soiltemperature
(0830IST)∘
C1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
2606
2707
+101
2233
2290
+057
2035
2069
+034
7136
6885minus251
2903
3138
+235
FEB
2677
2771
+094
2304
2355
+051
2112
2143
+031
7176
6941minus235
3041
3254
+213
MAR
2831
2920
+089
2458
2494
+036
2281
2294
+013
7255
6953
minus302
3280
3425
+145
APR
2929
3000
+071
2609
2630
+021
2471
2472
+001
7656
7361minus295
3373
3511
+138
MAY
2870
2943
+073
2612
2643
+031
2502
2517
+015
8094
7833
minus261
3246
3416
+170
JUN
2661
2733
+072
2520
2557
+037
2455
2481
+026
8851
8643minus208
2955
3099
+144
JUL
2576
2636
+060
2455
2488
+033
2395
2421
+026
8980
8803minus17
72901
3000
+099
AUG
2590
2660
+070
2460
2496
+036
2397
2422
+025
8940
8698minus242
2960
3096
+136
SEP
2662
2737
+075
2484
2521
+037
2402
2425
+023
8577
8345minus232
3110
3223
+113
OCT
2681
2759
+078
2490
2533
+043
2402
2432
+030
8501
8261minus240
3140
3245
+105
NOV
2690
2763
+073
2440
2486
+046
2327
2358
+031
8084
7935minus14
93099
3202
+103
DEC
2670
2759
+089
2335
2372
+037
2161
2174
+013
7448
7139
minus309
3052
3209
+157
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
Journal of Climatology 7
Table4Clim
atolog
yandΔof
visib
ilitycodelow
cloud
highclo
udand
totalcloud
Mon
thVisib
ilitycode
(0830IST)
Lowclo
ud(0830IST)
Middlec
loud
(0830IST)
Highclo
ud(0830IST)
Totalcloud
(0830IST)
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
9679
9698
+019
055
047
minus008
081
078
minus003
118
135
+017
251
253
+002
FEB
9675
9691
+016
048
047
minus001
066
058
minus008
108
116
+008
221
217
minus004
MAR
9661
9688
+027
062
071
+009
054
037
minus017
106
121
+015
220
224
+004
APR
9677
9686
+009
125
157
+032
100
087
minus013
172
179
+007
391
394
+003
MAY
9670
9668minus002
202
208
+006
145
143minus002
156
164
+008
487
468
minus019
JUN
9626
9643
+017
286
284
minus002
231
237
+006
116
149
+033
596
590
minus006
JUL
9610
9637
+027
274
274
+000
250
282
+032
126
167
+041
596
606
+010
AUG
9641
9658
+017
227
238
+011
231
228
minus003
131
186
+055
563
568
+005
SEP
9648
9663
+015
216
215
minus001
163
162minus001
134
162
+028
493
490
minus003
OCT
9676
9670minus006
175
196
+021
207
214
+007
129
173
+044
492
506
+014
NOV
9668
9665minus003
144
155
+011
186
194
+008
126
172
+046
440
465
+025
DEC
9681
9679minus002
101
091
minus010
140
115minus025
120
140
+020
356
325
minus031
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
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International Journal of
Geophysics
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EarthquakesJournal of
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BiodiversityInternational Journal of
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ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Journal of Climatology 3
Table1Detailson
instrumentatio
ndatausedand
theo
bservedvaria
tionin
maxim
umabsoluteerrorinmon
thlymeanused
inthed
iscussio
nof
climatolog
yat0830
IST
Sno
Parameter
Datau
sed
Instrument
Height(agl)
(cm)
Expo
sure
Lowestand
high
est
maxim
umabsolute
error
Make
Maintenance
and
calib
ratio
nprotocol
1Maxim
umtemperature
(∘ C)
1964
ndash2008
Maxim
umthermom
eter
(Mercury-in
-glassthermom
eter)
122
Stevensonscreen
0087to
0132(∘ C
)IM
D
Daily
weeklymon
thly
halfyearly
annu
aland
perio
dic
2Minim
umtemperature
(∘ C)
1964
ndash2008
Minim
umthermom
eter
(spirit-in
-glass)
122
Stevensonscreen
0061to0145(∘ C
)IM
D
3Dry-bulbtemperature
(∘ C)
1964
ndash2008
Drybu
lbthermom
eter
(mercury-in
-glassthermom
eter)
122
Stevensonscreen
0088to
0125(∘ C
)IM
D
4Ra
infall(m
m)
Non
recordingrain
gaugeo
fcollector
area
20square
cm0
Groun
d
4Wet-bulbtemperature
(∘ C)
1964
ndash2008
Wet-bulbthermom
eter
122
Stevensonscreen
006
to0146(∘ C
)IM
D
5Re
lativeh
umidity
()
1964
ndash2008
Drybu
lbthermom
eterw
etbu
lbthermom
eterand
psychrom
eter
table
122
Stevensonscreen
0512to
0916(
)IM
D
6Soiltemperature
(∘ C)
1964
ndash2008
Soilthermom
eter
inmetallic
tube
minus5
0201to0261(∘
C)IM
D
7Pressure
(mb)
1974ndash2008
Aneroid
barograph(diaph
ragm
type)
670
mam
slIM
D
8Windspeed
1964
ndash2008
Anemom
eter
300
0043to
024
(ms)
IMDD
ynalab
9Winddirection
1964
ndash2008
Windvane
300
With
in1d
egree
IMDD
ynalab
4 Journal of Climatology
summation of errors [23] of past and present data sets Indi-vidual error is computed as the ratio of standard deviation tothe number of observations of a particular data set Trenberth[24] has established the climate shift as a prominent upwardtrend in temperature after 1976 In order to include thisobservation influence half portion (15 years) period from1979 to 1993 ismade common in the latter half of past data andin the former part of present data The difference obtainedamong present data and past data has been represented as Δin the discussions throughout To see genuineness in findingsattributed to climate change Δ values are compared withabsolute errors so as to see that Δ do not fall within absoluteerrors of corresponding meteorological parameters
3 Results and Discussion
31 Δ Climatology of the Past 24 hr Observations Maximumtemperature minimum temperature and 24 hr accumulatedrainfall are the only 3meteorological parameters registered at0830 IST having effect of the past 24 hr variability behaviourClimatology for various parameters has been derived for pastdata and present data and presented in Tables 2 3 4 and5 in which months that constitute the different seasons arementioned Derived Δ values are also incorporated in theabove tables Comparison between past data and present datamaximum temperature climatology shows marked increasein present data climatology in relation to the past datacounterpart and thereby positive values alone are observedin Δ Δ values vary from +001∘C in the North East monsoon(NE monsoon) month November to +043∘C in the pre-South West monsoon (SW monsoon) month May The NEmonsoon season comprises October and November whereasthe four months from June to September designate SWmonsoon season which are the main two Indian seasonsIn minimum temperature all Δ values are positive withmaximum value in the winter month February with a value+053∘C The observations among maximum and minimumtemperature climatology derived in past data and presentdata along with Δ values can infer that the minimum dailytemperatures have generally increased at a larger rate thanthe maximum daily temperatures Karl et al [25] studied thepossible cause of increased urbanisation effects and Rebetezand Beniston [26] justified the result of increased cloud coverin the large increase in minimum temperature and smallincrease in maximum temperatures
From each individual daily maximum and minimumtemperature mean daily temperatures ((maximum temper-ature + minimum temperature)2) are computed and furtherderive the past data and present data climatologies of meantemperatures Only positive Δ values are observed through-out the year which clearly indicate that the temperature overthis tropical coastal station is increasing Temperature clima-tologies have shown the tropical monsoonal characteristic oftwo maxima and two minima in monthly variation
The diurnal temperature range is calculated from indi-vidual maximum and minimum temperature value andcalculated past data and present data temperature rangeclimatologies Range climatologies are featured by annualvariation The prominent feature of negative Δ values in
range is seen which shows that the difference betweenmaximum temperature and minimum temperature in a dayis decreasing Also the larger rate of increase in minimumtemperatures than maximum temperatures results in thesenegative Δ values in the diurnal temperature range
The rainfall Δ shows decrease in rainfall in present datafor the summermonthsApril andMayWell-marked negativeΔ values of about 21mm are observed in the SW monsoonmonths (JunendashAugust) An increase in rainfall activity isdetected in the SW monsoon month September and in theNE monsoon months October and November (debted tomonsoonal climate) with maximum value of +3650mm inOctober The station weather is dominated by convectivemesoscale systems during the NE monsoon Probably thisinvestigation poses the doubt about whether suchmeso-scaleweather phenomena like thunderstorm formations are onincreasing trend duringNEMonsoon and thereby an increasein Δ
32 Climatology of a Particular Observation at 0830 ISTAnalyses are carried out on different parameters collected at0830 IST Δ in dry bulb temperature wet bulb temperatureand dew point temperature obtained from the two climatolo-gies show only positive values It ranges from +060∘C in Julyto +101∘C in January for dry bulb temperature Variations inΔ among the SW monsoon months are less in general for allthe above three variables even though a maximum value inΔ is observed in dry bulb temperature The less variation ofwet bulb and dew point temperatures may be as a result ofmoisture laden atmosphere during the period which impartscorresponding variations in the moisture parameters like wetbulb temperature and dew point temperature
Station relative humidity values at 0830 IST show morethan 70 throughout the year with maximum in SW mon-soon of the order 89 Low negative values in Δ relativehumidity are detected as the air becomes drier in present datacompared to past As the air is getting dried both dew pointand the wet bulb temperatures are supposed to show negativeΔ values but the feature is not detectedThis may be inferredas the dry bulb temperature is the key parameter in elevatingΔ values of both dew point and wet bulb temperatures andthe meagre relative humidity decrease in present data thanpast data is insignificant to impartΔ changes in dewpoint andwet bulb temperatures Climatologies of RH also have showntwomaxima and twominimawhereas the secondaryminimaaround the NE monsoon is shallow in character
Significant positive Δ values are observed among the twoclimatologies in soil temperature with a low value of +099∘Cto a high of +235∘C in July and January respectively Perhapsthe Δ increase observed in the winter months January andFebruary may contribute reduction in radiational coolingwhich leads to a reduction in fog formation probability overthe station Soil temperature climatologies also have showntropical monsoonal type with two maxima and minima
Wind speed (both scalar and resultant) is decreased inpresent climatologies Mathematically resultant wind speedshall be determined as the square root of the sum of thesquares of zonal and meridional wind components Theencountered Δ values that rise to a maximum value of
Journal of Climatology 5
Table2Clim
atolog
yandΔof
maxim
umtemperaturem
inim
umtemperaturem
eandaily
temperaturem
eanrangeintemperatureand
mon
thlyrainfall
Mon
thMaxim
umtemperature∘
CMinim
umtemperature∘
CMeandaily
temperature∘
CMeanrangeintemperature∘
CMon
thlyrainfallmm
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
3259
3276
+017
2130
2158
+028
2694
2716
+022
1129
1117
minus012
1180
1110
minus070
FEB
3312
3332
+020
2189
2242
+053
2751
2787
+036
1124
1091minus033
1620
1640
+020
MAR
3384
3407
+023
2375
2413
+038
2878
2909
+031
1006
992
minus014
3320
3480
+160
APR
3425
3441
+016
2524
2551
+027
2976
2995
+019
905
888
minus017
10410
9940minus470
MAY
3303
3346
+043
2514
2550
+036
2912
2948
+036
797
796
minus001
1792
016580minus1340
JUN
3036
3071
+035
2399
2436
+037
2720
2753
+033
643
635
minus008
29270
27220minus2050
JUL
2938
2948
+010
2336
2379
+043
2638
2663
+025
603
568
minus035
20300
1813
0minus2170
AUG
2927
2960
+033
2339
2380
+041
2635
2670
+035
592
579
minus013
1415
012090minus2060
SEP
3034
3070
+036
2368
2400
+032
2704
2734
+030
671
667
minus004
15820
1710
0+1280
OCT
3119
3153
+034
2374
2404
+030
2750
2776
+026
753
744
minus009
20490
2414
0+3
650
NOV
3176
3177
+001
2321
2357
+036
2748
2767
+019
853
820
minus033
16680
17070
+390
DEC
3230
3256
+026
2244
2244
+000
2735
2750
+015
983
1011
+028
6660
5370minus1290
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
6 Journal of Climatology
Table3Clim
atolog
yandΔof
dry-bu
lbtemperaturew
etbu
lbtemperaturedew
pointtem
peraturerelativeh
umidityand
soiltemperature
Mon
thDry-bulbtemperature
(0830IST)∘
CWet-bulbtemperature
(0830IST)∘
CDew
pointtem
perature
(0830IST)∘
CRe
lativeh
umidity
()
(0830IST)
Soiltemperature
(0830IST)∘
C1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
2606
2707
+101
2233
2290
+057
2035
2069
+034
7136
6885minus251
2903
3138
+235
FEB
2677
2771
+094
2304
2355
+051
2112
2143
+031
7176
6941minus235
3041
3254
+213
MAR
2831
2920
+089
2458
2494
+036
2281
2294
+013
7255
6953
minus302
3280
3425
+145
APR
2929
3000
+071
2609
2630
+021
2471
2472
+001
7656
7361minus295
3373
3511
+138
MAY
2870
2943
+073
2612
2643
+031
2502
2517
+015
8094
7833
minus261
3246
3416
+170
JUN
2661
2733
+072
2520
2557
+037
2455
2481
+026
8851
8643minus208
2955
3099
+144
JUL
2576
2636
+060
2455
2488
+033
2395
2421
+026
8980
8803minus17
72901
3000
+099
AUG
2590
2660
+070
2460
2496
+036
2397
2422
+025
8940
8698minus242
2960
3096
+136
SEP
2662
2737
+075
2484
2521
+037
2402
2425
+023
8577
8345minus232
3110
3223
+113
OCT
2681
2759
+078
2490
2533
+043
2402
2432
+030
8501
8261minus240
3140
3245
+105
NOV
2690
2763
+073
2440
2486
+046
2327
2358
+031
8084
7935minus14
93099
3202
+103
DEC
2670
2759
+089
2335
2372
+037
2161
2174
+013
7448
7139
minus309
3052
3209
+157
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
Journal of Climatology 7
Table4Clim
atolog
yandΔof
visib
ilitycodelow
cloud
highclo
udand
totalcloud
Mon
thVisib
ilitycode
(0830IST)
Lowclo
ud(0830IST)
Middlec
loud
(0830IST)
Highclo
ud(0830IST)
Totalcloud
(0830IST)
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
9679
9698
+019
055
047
minus008
081
078
minus003
118
135
+017
251
253
+002
FEB
9675
9691
+016
048
047
minus001
066
058
minus008
108
116
+008
221
217
minus004
MAR
9661
9688
+027
062
071
+009
054
037
minus017
106
121
+015
220
224
+004
APR
9677
9686
+009
125
157
+032
100
087
minus013
172
179
+007
391
394
+003
MAY
9670
9668minus002
202
208
+006
145
143minus002
156
164
+008
487
468
minus019
JUN
9626
9643
+017
286
284
minus002
231
237
+006
116
149
+033
596
590
minus006
JUL
9610
9637
+027
274
274
+000
250
282
+032
126
167
+041
596
606
+010
AUG
9641
9658
+017
227
238
+011
231
228
minus003
131
186
+055
563
568
+005
SEP
9648
9663
+015
216
215
minus001
163
162minus001
134
162
+028
493
490
minus003
OCT
9676
9670minus006
175
196
+021
207
214
+007
129
173
+044
492
506
+014
NOV
9668
9665minus003
144
155
+011
186
194
+008
126
172
+046
440
465
+025
DEC
9681
9679minus002
101
091
minus010
140
115minus025
120
140
+020
356
325
minus031
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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EcosystemsJournal of
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EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
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International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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BiodiversityInternational Journal of
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OceanographyInternational Journal of
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
4 Journal of Climatology
summation of errors [23] of past and present data sets Indi-vidual error is computed as the ratio of standard deviation tothe number of observations of a particular data set Trenberth[24] has established the climate shift as a prominent upwardtrend in temperature after 1976 In order to include thisobservation influence half portion (15 years) period from1979 to 1993 ismade common in the latter half of past data andin the former part of present data The difference obtainedamong present data and past data has been represented as Δin the discussions throughout To see genuineness in findingsattributed to climate change Δ values are compared withabsolute errors so as to see that Δ do not fall within absoluteerrors of corresponding meteorological parameters
3 Results and Discussion
31 Δ Climatology of the Past 24 hr Observations Maximumtemperature minimum temperature and 24 hr accumulatedrainfall are the only 3meteorological parameters registered at0830 IST having effect of the past 24 hr variability behaviourClimatology for various parameters has been derived for pastdata and present data and presented in Tables 2 3 4 and5 in which months that constitute the different seasons arementioned Derived Δ values are also incorporated in theabove tables Comparison between past data and present datamaximum temperature climatology shows marked increasein present data climatology in relation to the past datacounterpart and thereby positive values alone are observedin Δ Δ values vary from +001∘C in the North East monsoon(NE monsoon) month November to +043∘C in the pre-South West monsoon (SW monsoon) month May The NEmonsoon season comprises October and November whereasthe four months from June to September designate SWmonsoon season which are the main two Indian seasonsIn minimum temperature all Δ values are positive withmaximum value in the winter month February with a value+053∘C The observations among maximum and minimumtemperature climatology derived in past data and presentdata along with Δ values can infer that the minimum dailytemperatures have generally increased at a larger rate thanthe maximum daily temperatures Karl et al [25] studied thepossible cause of increased urbanisation effects and Rebetezand Beniston [26] justified the result of increased cloud coverin the large increase in minimum temperature and smallincrease in maximum temperatures
From each individual daily maximum and minimumtemperature mean daily temperatures ((maximum temper-ature + minimum temperature)2) are computed and furtherderive the past data and present data climatologies of meantemperatures Only positive Δ values are observed through-out the year which clearly indicate that the temperature overthis tropical coastal station is increasing Temperature clima-tologies have shown the tropical monsoonal characteristic oftwo maxima and two minima in monthly variation
The diurnal temperature range is calculated from indi-vidual maximum and minimum temperature value andcalculated past data and present data temperature rangeclimatologies Range climatologies are featured by annualvariation The prominent feature of negative Δ values in
range is seen which shows that the difference betweenmaximum temperature and minimum temperature in a dayis decreasing Also the larger rate of increase in minimumtemperatures than maximum temperatures results in thesenegative Δ values in the diurnal temperature range
The rainfall Δ shows decrease in rainfall in present datafor the summermonthsApril andMayWell-marked negativeΔ values of about 21mm are observed in the SW monsoonmonths (JunendashAugust) An increase in rainfall activity isdetected in the SW monsoon month September and in theNE monsoon months October and November (debted tomonsoonal climate) with maximum value of +3650mm inOctober The station weather is dominated by convectivemesoscale systems during the NE monsoon Probably thisinvestigation poses the doubt about whether suchmeso-scaleweather phenomena like thunderstorm formations are onincreasing trend duringNEMonsoon and thereby an increasein Δ
32 Climatology of a Particular Observation at 0830 ISTAnalyses are carried out on different parameters collected at0830 IST Δ in dry bulb temperature wet bulb temperatureand dew point temperature obtained from the two climatolo-gies show only positive values It ranges from +060∘C in Julyto +101∘C in January for dry bulb temperature Variations inΔ among the SW monsoon months are less in general for allthe above three variables even though a maximum value inΔ is observed in dry bulb temperature The less variation ofwet bulb and dew point temperatures may be as a result ofmoisture laden atmosphere during the period which impartscorresponding variations in the moisture parameters like wetbulb temperature and dew point temperature
Station relative humidity values at 0830 IST show morethan 70 throughout the year with maximum in SW mon-soon of the order 89 Low negative values in Δ relativehumidity are detected as the air becomes drier in present datacompared to past As the air is getting dried both dew pointand the wet bulb temperatures are supposed to show negativeΔ values but the feature is not detectedThis may be inferredas the dry bulb temperature is the key parameter in elevatingΔ values of both dew point and wet bulb temperatures andthe meagre relative humidity decrease in present data thanpast data is insignificant to impartΔ changes in dewpoint andwet bulb temperatures Climatologies of RH also have showntwomaxima and twominimawhereas the secondaryminimaaround the NE monsoon is shallow in character
Significant positive Δ values are observed among the twoclimatologies in soil temperature with a low value of +099∘Cto a high of +235∘C in July and January respectively Perhapsthe Δ increase observed in the winter months January andFebruary may contribute reduction in radiational coolingwhich leads to a reduction in fog formation probability overthe station Soil temperature climatologies also have showntropical monsoonal type with two maxima and minima
Wind speed (both scalar and resultant) is decreased inpresent climatologies Mathematically resultant wind speedshall be determined as the square root of the sum of thesquares of zonal and meridional wind components Theencountered Δ values that rise to a maximum value of
Journal of Climatology 5
Table2Clim
atolog
yandΔof
maxim
umtemperaturem
inim
umtemperaturem
eandaily
temperaturem
eanrangeintemperatureand
mon
thlyrainfall
Mon
thMaxim
umtemperature∘
CMinim
umtemperature∘
CMeandaily
temperature∘
CMeanrangeintemperature∘
CMon
thlyrainfallmm
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
3259
3276
+017
2130
2158
+028
2694
2716
+022
1129
1117
minus012
1180
1110
minus070
FEB
3312
3332
+020
2189
2242
+053
2751
2787
+036
1124
1091minus033
1620
1640
+020
MAR
3384
3407
+023
2375
2413
+038
2878
2909
+031
1006
992
minus014
3320
3480
+160
APR
3425
3441
+016
2524
2551
+027
2976
2995
+019
905
888
minus017
10410
9940minus470
MAY
3303
3346
+043
2514
2550
+036
2912
2948
+036
797
796
minus001
1792
016580minus1340
JUN
3036
3071
+035
2399
2436
+037
2720
2753
+033
643
635
minus008
29270
27220minus2050
JUL
2938
2948
+010
2336
2379
+043
2638
2663
+025
603
568
minus035
20300
1813
0minus2170
AUG
2927
2960
+033
2339
2380
+041
2635
2670
+035
592
579
minus013
1415
012090minus2060
SEP
3034
3070
+036
2368
2400
+032
2704
2734
+030
671
667
minus004
15820
1710
0+1280
OCT
3119
3153
+034
2374
2404
+030
2750
2776
+026
753
744
minus009
20490
2414
0+3
650
NOV
3176
3177
+001
2321
2357
+036
2748
2767
+019
853
820
minus033
16680
17070
+390
DEC
3230
3256
+026
2244
2244
+000
2735
2750
+015
983
1011
+028
6660
5370minus1290
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
6 Journal of Climatology
Table3Clim
atolog
yandΔof
dry-bu
lbtemperaturew
etbu
lbtemperaturedew
pointtem
peraturerelativeh
umidityand
soiltemperature
Mon
thDry-bulbtemperature
(0830IST)∘
CWet-bulbtemperature
(0830IST)∘
CDew
pointtem
perature
(0830IST)∘
CRe
lativeh
umidity
()
(0830IST)
Soiltemperature
(0830IST)∘
C1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
2606
2707
+101
2233
2290
+057
2035
2069
+034
7136
6885minus251
2903
3138
+235
FEB
2677
2771
+094
2304
2355
+051
2112
2143
+031
7176
6941minus235
3041
3254
+213
MAR
2831
2920
+089
2458
2494
+036
2281
2294
+013
7255
6953
minus302
3280
3425
+145
APR
2929
3000
+071
2609
2630
+021
2471
2472
+001
7656
7361minus295
3373
3511
+138
MAY
2870
2943
+073
2612
2643
+031
2502
2517
+015
8094
7833
minus261
3246
3416
+170
JUN
2661
2733
+072
2520
2557
+037
2455
2481
+026
8851
8643minus208
2955
3099
+144
JUL
2576
2636
+060
2455
2488
+033
2395
2421
+026
8980
8803minus17
72901
3000
+099
AUG
2590
2660
+070
2460
2496
+036
2397
2422
+025
8940
8698minus242
2960
3096
+136
SEP
2662
2737
+075
2484
2521
+037
2402
2425
+023
8577
8345minus232
3110
3223
+113
OCT
2681
2759
+078
2490
2533
+043
2402
2432
+030
8501
8261minus240
3140
3245
+105
NOV
2690
2763
+073
2440
2486
+046
2327
2358
+031
8084
7935minus14
93099
3202
+103
DEC
2670
2759
+089
2335
2372
+037
2161
2174
+013
7448
7139
minus309
3052
3209
+157
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
Journal of Climatology 7
Table4Clim
atolog
yandΔof
visib
ilitycodelow
cloud
highclo
udand
totalcloud
Mon
thVisib
ilitycode
(0830IST)
Lowclo
ud(0830IST)
Middlec
loud
(0830IST)
Highclo
ud(0830IST)
Totalcloud
(0830IST)
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
9679
9698
+019
055
047
minus008
081
078
minus003
118
135
+017
251
253
+002
FEB
9675
9691
+016
048
047
minus001
066
058
minus008
108
116
+008
221
217
minus004
MAR
9661
9688
+027
062
071
+009
054
037
minus017
106
121
+015
220
224
+004
APR
9677
9686
+009
125
157
+032
100
087
minus013
172
179
+007
391
394
+003
MAY
9670
9668minus002
202
208
+006
145
143minus002
156
164
+008
487
468
minus019
JUN
9626
9643
+017
286
284
minus002
231
237
+006
116
149
+033
596
590
minus006
JUL
9610
9637
+027
274
274
+000
250
282
+032
126
167
+041
596
606
+010
AUG
9641
9658
+017
227
238
+011
231
228
minus003
131
186
+055
563
568
+005
SEP
9648
9663
+015
216
215
minus001
163
162minus001
134
162
+028
493
490
minus003
OCT
9676
9670minus006
175
196
+021
207
214
+007
129
173
+044
492
506
+014
NOV
9668
9665minus003
144
155
+011
186
194
+008
126
172
+046
440
465
+025
DEC
9681
9679minus002
101
091
minus010
140
115minus025
120
140
+020
356
325
minus031
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
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BiodiversityInternational Journal of
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ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Journal of Climatology 5
Table2Clim
atolog
yandΔof
maxim
umtemperaturem
inim
umtemperaturem
eandaily
temperaturem
eanrangeintemperatureand
mon
thlyrainfall
Mon
thMaxim
umtemperature∘
CMinim
umtemperature∘
CMeandaily
temperature∘
CMeanrangeintemperature∘
CMon
thlyrainfallmm
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
3259
3276
+017
2130
2158
+028
2694
2716
+022
1129
1117
minus012
1180
1110
minus070
FEB
3312
3332
+020
2189
2242
+053
2751
2787
+036
1124
1091minus033
1620
1640
+020
MAR
3384
3407
+023
2375
2413
+038
2878
2909
+031
1006
992
minus014
3320
3480
+160
APR
3425
3441
+016
2524
2551
+027
2976
2995
+019
905
888
minus017
10410
9940minus470
MAY
3303
3346
+043
2514
2550
+036
2912
2948
+036
797
796
minus001
1792
016580minus1340
JUN
3036
3071
+035
2399
2436
+037
2720
2753
+033
643
635
minus008
29270
27220minus2050
JUL
2938
2948
+010
2336
2379
+043
2638
2663
+025
603
568
minus035
20300
1813
0minus2170
AUG
2927
2960
+033
2339
2380
+041
2635
2670
+035
592
579
minus013
1415
012090minus2060
SEP
3034
3070
+036
2368
2400
+032
2704
2734
+030
671
667
minus004
15820
1710
0+1280
OCT
3119
3153
+034
2374
2404
+030
2750
2776
+026
753
744
minus009
20490
2414
0+3
650
NOV
3176
3177
+001
2321
2357
+036
2748
2767
+019
853
820
minus033
16680
17070
+390
DEC
3230
3256
+026
2244
2244
+000
2735
2750
+015
983
1011
+028
6660
5370minus1290
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
6 Journal of Climatology
Table3Clim
atolog
yandΔof
dry-bu
lbtemperaturew
etbu
lbtemperaturedew
pointtem
peraturerelativeh
umidityand
soiltemperature
Mon
thDry-bulbtemperature
(0830IST)∘
CWet-bulbtemperature
(0830IST)∘
CDew
pointtem
perature
(0830IST)∘
CRe
lativeh
umidity
()
(0830IST)
Soiltemperature
(0830IST)∘
C1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
2606
2707
+101
2233
2290
+057
2035
2069
+034
7136
6885minus251
2903
3138
+235
FEB
2677
2771
+094
2304
2355
+051
2112
2143
+031
7176
6941minus235
3041
3254
+213
MAR
2831
2920
+089
2458
2494
+036
2281
2294
+013
7255
6953
minus302
3280
3425
+145
APR
2929
3000
+071
2609
2630
+021
2471
2472
+001
7656
7361minus295
3373
3511
+138
MAY
2870
2943
+073
2612
2643
+031
2502
2517
+015
8094
7833
minus261
3246
3416
+170
JUN
2661
2733
+072
2520
2557
+037
2455
2481
+026
8851
8643minus208
2955
3099
+144
JUL
2576
2636
+060
2455
2488
+033
2395
2421
+026
8980
8803minus17
72901
3000
+099
AUG
2590
2660
+070
2460
2496
+036
2397
2422
+025
8940
8698minus242
2960
3096
+136
SEP
2662
2737
+075
2484
2521
+037
2402
2425
+023
8577
8345minus232
3110
3223
+113
OCT
2681
2759
+078
2490
2533
+043
2402
2432
+030
8501
8261minus240
3140
3245
+105
NOV
2690
2763
+073
2440
2486
+046
2327
2358
+031
8084
7935minus14
93099
3202
+103
DEC
2670
2759
+089
2335
2372
+037
2161
2174
+013
7448
7139
minus309
3052
3209
+157
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
Journal of Climatology 7
Table4Clim
atolog
yandΔof
visib
ilitycodelow
cloud
highclo
udand
totalcloud
Mon
thVisib
ilitycode
(0830IST)
Lowclo
ud(0830IST)
Middlec
loud
(0830IST)
Highclo
ud(0830IST)
Totalcloud
(0830IST)
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
9679
9698
+019
055
047
minus008
081
078
minus003
118
135
+017
251
253
+002
FEB
9675
9691
+016
048
047
minus001
066
058
minus008
108
116
+008
221
217
minus004
MAR
9661
9688
+027
062
071
+009
054
037
minus017
106
121
+015
220
224
+004
APR
9677
9686
+009
125
157
+032
100
087
minus013
172
179
+007
391
394
+003
MAY
9670
9668minus002
202
208
+006
145
143minus002
156
164
+008
487
468
minus019
JUN
9626
9643
+017
286
284
minus002
231
237
+006
116
149
+033
596
590
minus006
JUL
9610
9637
+027
274
274
+000
250
282
+032
126
167
+041
596
606
+010
AUG
9641
9658
+017
227
238
+011
231
228
minus003
131
186
+055
563
568
+005
SEP
9648
9663
+015
216
215
minus001
163
162minus001
134
162
+028
493
490
minus003
OCT
9676
9670minus006
175
196
+021
207
214
+007
129
173
+044
492
506
+014
NOV
9668
9665minus003
144
155
+011
186
194
+008
126
172
+046
440
465
+025
DEC
9681
9679minus002
101
091
minus010
140
115minus025
120
140
+020
356
325
minus031
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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EcosystemsJournal of
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MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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EarthquakesJournal of
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BiodiversityInternational Journal of
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ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
6 Journal of Climatology
Table3Clim
atolog
yandΔof
dry-bu
lbtemperaturew
etbu
lbtemperaturedew
pointtem
peraturerelativeh
umidityand
soiltemperature
Mon
thDry-bulbtemperature
(0830IST)∘
CWet-bulbtemperature
(0830IST)∘
CDew
pointtem
perature
(0830IST)∘
CRe
lativeh
umidity
()
(0830IST)
Soiltemperature
(0830IST)∘
C1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
2606
2707
+101
2233
2290
+057
2035
2069
+034
7136
6885minus251
2903
3138
+235
FEB
2677
2771
+094
2304
2355
+051
2112
2143
+031
7176
6941minus235
3041
3254
+213
MAR
2831
2920
+089
2458
2494
+036
2281
2294
+013
7255
6953
minus302
3280
3425
+145
APR
2929
3000
+071
2609
2630
+021
2471
2472
+001
7656
7361minus295
3373
3511
+138
MAY
2870
2943
+073
2612
2643
+031
2502
2517
+015
8094
7833
minus261
3246
3416
+170
JUN
2661
2733
+072
2520
2557
+037
2455
2481
+026
8851
8643minus208
2955
3099
+144
JUL
2576
2636
+060
2455
2488
+033
2395
2421
+026
8980
8803minus17
72901
3000
+099
AUG
2590
2660
+070
2460
2496
+036
2397
2422
+025
8940
8698minus242
2960
3096
+136
SEP
2662
2737
+075
2484
2521
+037
2402
2425
+023
8577
8345minus232
3110
3223
+113
OCT
2681
2759
+078
2490
2533
+043
2402
2432
+030
8501
8261minus240
3140
3245
+105
NOV
2690
2763
+073
2440
2486
+046
2327
2358
+031
8084
7935minus14
93099
3202
+103
DEC
2670
2759
+089
2335
2372
+037
2161
2174
+013
7448
7139
minus309
3052
3209
+157
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
Journal of Climatology 7
Table4Clim
atolog
yandΔof
visib
ilitycodelow
cloud
highclo
udand
totalcloud
Mon
thVisib
ilitycode
(0830IST)
Lowclo
ud(0830IST)
Middlec
loud
(0830IST)
Highclo
ud(0830IST)
Totalcloud
(0830IST)
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
9679
9698
+019
055
047
minus008
081
078
minus003
118
135
+017
251
253
+002
FEB
9675
9691
+016
048
047
minus001
066
058
minus008
108
116
+008
221
217
minus004
MAR
9661
9688
+027
062
071
+009
054
037
minus017
106
121
+015
220
224
+004
APR
9677
9686
+009
125
157
+032
100
087
minus013
172
179
+007
391
394
+003
MAY
9670
9668minus002
202
208
+006
145
143minus002
156
164
+008
487
468
minus019
JUN
9626
9643
+017
286
284
minus002
231
237
+006
116
149
+033
596
590
minus006
JUL
9610
9637
+027
274
274
+000
250
282
+032
126
167
+041
596
606
+010
AUG
9641
9658
+017
227
238
+011
231
228
minus003
131
186
+055
563
568
+005
SEP
9648
9663
+015
216
215
minus001
163
162minus001
134
162
+028
493
490
minus003
OCT
9676
9670minus006
175
196
+021
207
214
+007
129
173
+044
492
506
+014
NOV
9668
9665minus003
144
155
+011
186
194
+008
126
172
+046
440
465
+025
DEC
9681
9679minus002
101
091
minus010
140
115minus025
120
140
+020
356
325
minus031
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Environmental Chemistry
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Journal of Climatology 7
Table4Clim
atolog
yandΔof
visib
ilitycodelow
cloud
highclo
udand
totalcloud
Mon
thVisib
ilitycode
(0830IST)
Lowclo
ud(0830IST)
Middlec
loud
(0830IST)
Highclo
ud(0830IST)
Totalcloud
(0830IST)
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
1964
ndash1993
1979ndash2008Δ
JAN
9679
9698
+019
055
047
minus008
081
078
minus003
118
135
+017
251
253
+002
FEB
9675
9691
+016
048
047
minus001
066
058
minus008
108
116
+008
221
217
minus004
MAR
9661
9688
+027
062
071
+009
054
037
minus017
106
121
+015
220
224
+004
APR
9677
9686
+009
125
157
+032
100
087
minus013
172
179
+007
391
394
+003
MAY
9670
9668minus002
202
208
+006
145
143minus002
156
164
+008
487
468
minus019
JUN
9626
9643
+017
286
284
minus002
231
237
+006
116
149
+033
596
590
minus006
JUL
9610
9637
+027
274
274
+000
250
282
+032
126
167
+041
596
606
+010
AUG
9641
9658
+017
227
238
+011
231
228
minus003
131
186
+055
563
568
+005
SEP
9648
9663
+015
216
215
minus001
163
162minus001
134
162
+028
493
490
minus003
OCT
9676
9670minus006
175
196
+021
207
214
+007
129
173
+044
492
506
+014
NOV
9668
9665minus003
144
155
+011
186
194
+008
126
172
+046
440
465
+025
DEC
9681
9679minus002
101
091
minus010
140
115minus025
120
140
+020
356
325
minus031
DEC
JANand
FEB
winterMAR
APR
and
MAY
sum
merJUNJULAU
Gand
SEP
SWmon
soon
OCT
NOV
NEmon
soon
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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EcosystemsJournal of
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MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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BiodiversityInternational Journal of
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ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
8 Journal of Climatology
Table 5 Climatology and Δ of wind speed (scalar) wind speed (resultant) and wind steadiness factor
MonthWind speed (scalar)(0830 IST) msminus1
Wind speed (resultant)(0830 IST) msminus1
Wind steadiness factor(0830 IST) ()
1964ndash1993 1979ndash2008 Δ 1979ndash2008 Δ 1964ndash1993 1979ndash2008 Δ
JAN 104 075 minus029 071 033 minus038 6889 4448 minus2441FEB 107 081 minus026 073 038 minus035 6795 4736 minus2059MAR 121 100 minus021 083 056 minus027 6849 5615 minus1234APR 129 100 minus029 092 063 minus029 7146 6315 minus831MAY 145 104 minus041 114 075 minus039 7840 7244 minus596JUN 149 109 minus040 103 08 minus023 6897 7365 +468JUL 168 135 minus033 115 094 minus021 6808 6960 +152AUG 161 131 minus030 136 105 minus031 8468 7999 minus469SEP 157 110 minus047 117 081 minus036 7457 7406 minus051OCT 110 082 minus028 064 040 minus024 5869 4926 minus943NOV 097 074 minus023 049 023 minus026 5029 3117 minus1912DEC 101 075 minus026 067 037 minus030 6644 4888 minus1756DEC JAN and FEB winter MAR APR and MAY summer JUN JUL AUG and SEP SWmonsoon OCT NOV NE monsoon
the order 05ms are due to decrease in wind speeds inthe present data climatology in comparison with past dataclimatology Wind steadiness factor values at 0830 IST arecomputed as the ratio of mean resultant wind speed to meanscalar wind (average value of scalar wind speeds) expressed in and the two slot climatologies are made Wind steadinessfactor is a general meteorological technique in order to derivethe quantitative estimate of steadiness of wind direction[27] The feature of losing controllability of blowing windsfrom a specific direction (computed from wind steadiness)as the demand of a particular season might be justified asa result of heat island effect of the very fast developingurbanisation hardly 8 km East South East of the observatoryand the increasing vehicle populations and thereby drasticmodifications in at 0830 IST observations which belongto land breeze prevalence over the station in the non-SWmonsoonal months (up to a maximum of 20 decrease)Throughout the day strong seabreeze is in prevalence in theSW monsoon months Even in the SW monsoon which isdominantly associated with unidirectional wind flow slightdeteriorations in the steadiness of the wind directions haveobserved Both the above observations brought out thephenomenal changes in the steadiness of offshorewinds (landbreeze) at 0830 IST during the non-SW monsoonal monthsat greater extend and onshore wind (sea breeze) at 0830 ISTduring the SW monsoon steadiness in smaller grades Thefeature of very prominent decrease in direction steadinessin preset data to the past is clearly detected As negative Δdominance exists in the non-SW monsoon months wherechange over of land-sea breezes are so pronounced for thestation this observation may be further studied in order tocheck any possible modifications in the meso-scale meteoro-logical phenomena like sealand breeze thunderstorms dueto associated thermal and moisture environment changes
Visibility and cloud climatologies are also studied Asthese observational procedures are non-instrumental thedata is too subjective and quality observation is solely vested
260265270275280285290295300305
Tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n (∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 2 (a) Mean daily temperature climatologies in 1964ndash19931979ndash2008 and their differences along with (b) standard deviationof corresponding climatologies
on the experience of the weather observer The observationshows better visibility codes in the present data climatologyA visibility code of 96 and above signifies that a well-definedobject (like a mobile phone tower) at least 1 km far can bedistinctly differentiable Among various cloud climatologydominant positiveΔ values are existed in high clouds throughout the year whichmay be pointed out as one of the reason forsubdued albedo effect which enhances greenhouse effect and
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
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BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Journal of Climatology 9
50556065707580859095
100105110115120125
Tem
pera
ture
rang
e (∘ C)
(a)
0004081216202428
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20 10 20M
ar 1 10 20
Apr
1 10 20M
ay 1 20
Jun
1 10 20Ju
l 1 10 20A
ug 1 10 20
Sep
1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 3 (a) Mean daily temperature range climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
285290295300305310315320325330335340345350
Max
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Jan
1 10 20 10 20M
ar 1 10 20
Apr 1 10 20
May
1 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
(b)
Figure 4 (a) Maximum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
200205210215220225230235240245250255260265
Min
imum
tem
pera
ture
(∘C)
(a)
00040812162024
Date
Stan
dard
devi
atio
n(∘
C)
1964ndash19931979ndash2008
Jan
1 10 20Fe
b 1 10 20
Mar
1 10 20A
pr 1 10 20
May
1 10 20Ju
n 1 10 20
Jul 1 10 20
Aug
1 10 20Se
p 1 10 20
Oct
1 10 20N
ov 1 10 20
Dec
1 10 20 D
ec 3
1
(b)
Figure 5 (a) Minimum daily temperature climatologies in 1964ndash1993 1979ndash2008 and their differences along with (b) standarddeviation of corresponding climatologies
0102030405060708090100
Less than zero Zero Greater than zero0
20406080
100120140160180200220240260280300320340360
Occ
urre
nces
(day
s)
Daily max tempDaily min temp
Daily mean tempRange
Occ
urre
nces
()
Figure 6 Difference statistics for 365 days between present data andpast data on daily maximum minimum mean temperatures andrange in temperature within a day
hereby surface temperature escalationThis may be the resultof number of high cloud types (Ci and Cc) are less comparedto the varieties of low and middle cloud types which enableseasy estimation for the observer while making counts onhigh clouds The increase in high cloud climatology valuesin present data may be the result of increase in air trafficresulted contrails over the region which results an increasein cirrus cloud formations due to tropical dynamics unlike
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
10 Journal of Climatology
271273275277279281283285
Mea
n te
mpe
ratu
re (∘
C)
101214161820
Stan
dard
devi
atio
n(∘
C)
dydx = 0013
r = 0891
(a)
minus10minus08minus06minus04minus02
00204060810
Tem
pera
ture
anom
aly
(∘C)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0013
r = 0891
Mean temperature11pt soothed line
Fitted lineStandard deviation
(b)
Figure 7 (a) Yearly mean temperature along with standard devia-tion and (b) anomaly
308312316320324328
1517192123252729dydx = 0012
r = 0725
Max
imum
tem
pera
ture
(∘C)
Stan
dard
devi
atio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
dydx = 0012
r = 0725
Tem
pera
ture
anom
aly
(∘C)
Standard deviationFitted line
11pt soothed lineMaximum temperature
(b)
Figure 8 (a) Yearly mean maximum temperature along withstandard deviation and (b) anomaly
microphysical processes in mid-latitudes as in Minnis et al[28] Zerefos et al [29] Eleftheratos et al [30] have studiedthe variability of cirrus clouds over the tropics governedby the activity of El Nino Southern Oscillation the QuasiBiennial Oscillation and solar activity Possible radiationbudget alterations modifications at the time of occurrenceof minimum and maximum temperatures are to be criticallyexamined as a part of future investigations Prominent twomaxima (secondarymaximum is very shallower compared to
dydx = 0014
r = 0952
226230234238242246
1012141618202224
Min
imum
tem
pera
ture
(∘C)
Stan
dard
dev
iatio
n(∘
C)
(a)
minus12minus08minus04
0040812
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
dydx = 0014
r = 0952
(year)
Standard deviationFitted line11pt soothed lineMinimum temperature
Tem
pera
ture
anom
aly
(∘C)
(b)
Figure 9 (a) Yearly mean minimum temperature along withstandard deviation and (b) anomaly
dydx = 0002
r = 0190
1620242832
Stan
dard
dev
iatio
n
6670747882869094
Tem
pera
ture
rang
e(∘ C)
(a)
minus12minus08minus04
0040812
dydx = 0002
r = 0190
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Tem
pera
ture
rang
ean
omal
y(∘
C)
(year)
Temperature range11pt soothed line
Fitted lineStandard deviation
(b)
Figure 10 (a) Yearly mean temperature range along with standarddeviation and (b) anomaly
the primary) and two minima were seen in middle high andtotal cloud climatology
33 Mean Daily Climatology in Temperature Mean of dailymaximum minimum mean and range in temperaturebetween daily maximum and minimum temperatures arecomputed and depicted for the 365 days in a year (Figures2 3 4 and 5) along with their standard deviations Theincrease inmean daily values in present data temperatures arequite obvious and standard deviation values are fallen within
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Journal of Climatology 11
(year)
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 11 Maximum temperature anomaly
27∘C for all the four mean daily climatologies A differencestatistics for 365 days between present data to past data ismade and is shown in Figure 6 Out of 365 days more than80 mean daily maximum minimum and mean tempera-tures are distributed as greater than zero occurrences in thedifference statistics An elevated frequency of occurrence ofmore than 65 under less than zero class is a concrete featurewhich implies that the range amongmaximumandminimumtemperature is alarmingly diminishing
34 Interannual Variability Inter annual variability has crit-ically examined for annual mean of minimum maximumand mean temperatures annual rainfall in the SW and NEmonsoon over the station and for theKerala State and averageannual surface pressure in the SW and NE monsoons forthe station Each inter annual variability data has undergonean 11 year moving average with end point extrapolation tillthe raw data availability to bring out long term trend andthe trend line also has shown in each inter annual variabilityfigures similar to Krishnakumar et al [22] for the interannualvariability of rainfall over Kerala Interpolated values areobtained for each year from the trend and such a data setobtained has been subjected to statistical significant testinterpolated data has not taken for a particular year if theraw data point is missing for the corresponding year Thismethod has enabled no reduction in the degrees of freedom(df ) To confirm the statistical significance on various 11year moving averaged data and also to assess the strength ofsample correlation coefficient (119903) linear regression t-test werecarried out and the results are presented (Table 6) Generallystrong and significant linear trend variations are observedEven though linear trends of maximum and minimumtemperatures have shown strong and significant statisticaltrends the derived variable-temperature range has resulteda weak and insignificant test statisticThis may be statisticallyinferred as a variable derived out of two variables whichfavours strong and significant test statistic separately need notshow the same test static of strong and significant
341 Interannual Variability in Temperature To assess theinterannual variability with temperature annual mean min-imum mean maximum and mean of mean temperaturesare found out for each year from 1964 to 2008 Also to
ascertain deviation from the normal each yearly mean valueis deducted from the mean of the entire values available forpresent data and thereby extracted the anomaly in tempera-ture Mean and standard deviation of daily mean maximumminimum and daily temperature range are computed for ayear and depicted in Figures 7 8 9 and 10 The fitted lineartrend line slope (dydx) as well as correlation coefficient (119903)values are annotated in graphs It is seen that from bothmeandaily temperature as well as from the maximum temperaturean abrupt prominent shift or a discernible upward trendis occurred after 1976 may be like the ldquoclimate shiftrdquo asstated by Trenberth [24] The 45 year rate in mean dailymaximum andminimum are obtained as +0585∘C +0540∘Cand +0630∘C respectively or with decadal rates of (+013 plusmn001)∘C (+012 plusmn 002)∘C and (+014 plusmn 00)∘C accordingly Inthe obtained value for the global mean surface temperatureas a whole (+007 plusmn 002)∘C surface temperatures over landhave risen at about double the ocean rate after 1979 (morethan (+027 plusmn 006)∘C per decade versus (+013 plusmn 004)∘Cper decade) as per the Trenberth et al [31] From 1950 to2004 the global land trend in diurnal temperature range wasextracted as negative (minus007∘C per decade) although tropicalareas are still underrepresented [31] Kumar et al [32] showedtrends of increase in diurnal temperature range significantincrease in annual maximum temperature and practicallytrendless annual minimum temperature over India in thelast century Our inter annual variability results coincidemostly with former studied data period which supports thedecrease of diurnal temperature range and the same is veryvivid from Figure 6 discussed earlier It infers that for thistropical coastal station the obtained decadal rate of (+0130plusmn001)∘C which is in agreement with global ocean rate maybe due to the station being coastal in origin The errorvalue reduction by plusmn003∘C for TERLS can be due to morestabilized single station data Also rate of increase in trend forminimum temperature is high in comparison to maximumtemperature A decreasing trend in maximum temperature isnoticed after 2005 with decreasing standard deviation valuesThis observation might be correct as a result of shifting theobservatory since 1964 to hardly 30m towards north in 2005were smooth and free sea-breeze flow which enables abruptreach of maximum temperature in the diurnal course aroundthe time of sea breeze onset The feature of attaining themaximum temperature of the day around the time of onset of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
12 Journal of Climatology
Table 6 Linear trends of 11 year moving averaged data on various inter-annual variability Level of significance was choosen at 005 toread out critical 119905 values (119905
119888
) corresponding to the degree of freedom (df ) If 119903 gt 05 strong 119903 lt 05 weak 119905 gt 119905119888
significant and 119905 lt 119905119888
notsignificant
No Interannualvariability in 119903
Slope (119889119910119889119909) plusmnerror Calculated 119905 df Comments Data missing
1 Mean temperature 0891 0013 plusmn 0001 1208154 38Strong and
significant (Figures7(a) and 7(b))
1974 1975 19761982 and 1992
2 Mean maximumtemperature 0725 00121 plusmn 0002 650392 38
Strong andsignificant
(Figures 8(a) and 8(b)
1974 1975 19761982 and 1992
3 Mean minimumtemperature 0952 0014 plusmn 0000 1929677 38
Strong andsignificant
(Figures 9(a) and9(b))
1974 1975 19761982 and 1992
4 Mean temperaturerange minus0190 minus0002 plusmn 0002 minus119078 38
Weak and notsignificant
(Figure 10(a))
1974 1975 19761982 and 1992
5South West
monsoon rainfall(Thumba)
minus0477 minus2145 plusmn 0616 minus3483 41 Weak and significant(Figure 14) 1964 1998
6North East
monsoon rainfall(Thumba)
0848 3928 plusmn 0393 10000 39 Strong and significant(Figure 15)
1964 1977 1992and 1998
7South West
monsoon rainfall(Kerala)
minus0721 minus6149 plusmn 0934 minus6587 40 Strong and significant(Figure 16)
1964 2007 and2008
8North East
monsoon rainfall(Kerala)
0737 3430 plusmn 0491 6986 41 Strong and significant(Figure 17) 1964 2008
9South West
monsoon surfacepressure
0445 0006 plusmn 0002 2899 34 Weak and significant(Figure 18) 1964 to 1972
10North East
monsoon surfacepressure
minus0616 0010 plusmn 0002 minus4555 34 Strong and significant(Figure 19) 1964 to 1972
123456789
101112
(mon
th)
1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
20181614121008060402minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20
(∘C)
Figure 12 Minimum temperature anomaly
sea breeze is known [33] As the station is of coastal in originthe occurrence of daily maximum temperature is very muchlinked to the setting and strong establishment of sea breezefront towards the land areas
Mean monthly anomaly structures in minimum max-imum and mean temperatures are presented in time sec-tion contour diagrams (Figures 11 12 and 13) All contour
depictions show well-marked temperature increase duringthe course of years and are so pronounced after 1976
342 Interannual Variability in SW and NE Monsoon Rain-fall and Surface Pressure Interannual variability in rainfalland surface pressure particularly for SW monsoon and NEmonsoon are studied A decrease in trend in SW monsoon
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Journal of Climatology 13
123456789
101112
(mon
th)
(year)1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
No data
14121008060402
(∘C)
minus00minus02minus04minus06minus08minus10minus12minus14minus16minus18minus20minus22
Figure 13 Mean temperature anomaly
300400500600700800900
100011001200130014001500
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
dydx = minus2145
r = minus0477
Figure 14 South West monsoon rainfall over Thumba
(year)
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = 3928
r = 0848
Figure 15 North East monsoon rainfall over Thumba
and an increase in trend in NE monsoons are the observedfeatures over the station with decadal variability of (minus215 plusmn62)mm and (+393 plusmn 39)mm respectively (Figures 14and 15) Analysis by considering initial rainfall values (atthe beginning year on the fitted straight line) of SouthWest monsoon North East monsoon corresponding slopeof them as 817822mm 296535mm minus215mmdecade and
(year)
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Rain
fall
(mm
)
dydx = minus6149r = minus0721
Figure 16 South West monsoon rainfall over Kerala
0
100
200
300
400
500
600
700
800
900
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010(year)
Rain
fall
(mm
)
r = 0737
dydx = 3430
Figure 17 North East monsoon rainfall over Kerala
393mmdecade respectively shows the likelihood exceedof North East monsoon rainfall over South West monsoonover this region after the year 2050 if the current trendcontinues Similar analyses are carried out on the slot 1965to 2007 for the Kerala meteorological subdivision from thelongest instrumental rainfall series of the Indian regions(1813ndash2006) ([34] httpwwwtropmetresin) The actualrainfall amount over Kerala during 2007 is obtained from the
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
14 Journal of Climatology
10070100751008010085100901009510100
Pres
sure
(mb)
dydx = 00061r = 04452
(a)
101214161820
1976 1980 1984 1988 1992 1996 2000 2004 2008100012501500175020002250
Standard deviationNumber of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 18 (a) Interannual variability in surface pressure for SouthWest monsoon season along with (b) standard deviation andnumber of observations
100801008510090100951010010105101101011510120
Pres
sure
(mb)
dydx = minus0010r = minus0616
(a)
10
15
20
25
1976 1980 1984 1988 1992 1996 2000 2004 2008500700900110013001500
Standard deviationNo of observations
(year)
Stan
dard
de
viat
ion
(mb)
No
of o
bser
vatio
ns
(b)
Figure 19 (a) Interannual variability in surface pressure for NorthEastmonsoon season alongwith (b) standard deviation and numberof observations
quarterly journal theMAUSAM (July 2008 andOctober 2008issues) Decadal variations show a decreasing trend in SWmonsoon by (minus615 plusmn 93)mm and increasing trend in NEmonsoon by (+340 plusmn 49)mm (Figures 16 and 17)
Interannual variability in surface pressure was derivedand depicted for SW monsoon (Figure 18) and NE monsoon(Figure 19) For this every hourly data available since 1973
was subjected to mean monthly value computation Numberof observations available ranges from 1100 to 2245 in SWmonsoon and 500 to 1495 in NE monsoon respectivelyand provided along with the standard deviation values inthe above figures Since atmospheric pressure is a highlystabilized property over a region for a particular season thedecadal trend variability observed is (+006 plusmn 002)mb and(ndash010plusmn002)mb for SWmonsoon andNEmonsoon respec-tively The positive (increase) and negative (decrease) inter-annual trends observed in SW monsoon and NE monsoonrespectively might have contributed possible implications inthe development of associated synoptic scale meteorologicalsystems (position and orientation of troughsridges and lowpressures) and thereby corresponding decrease and increasein SWmonsoon and NE monsoon rainfall trends
4 Conclusion
Long-term surface meteorological records from TERLS werecollected and analysed to study the long-term changes inoverall climatology climatology pertained to a particulartime of observation mean daily climatology in temperatureinterannual variability in temperature interannual variabilityin SW andNEmonsoon rainfall andmeanmonthly anomalystructure in temperature Results on various analyses showstrong and vivid features contributed by climate change Thesalient features observed contributed by climate change are asfollows
(1) All the temperatures show increase in their behaviourwith slight decrease in RH between the presentclimatology and past climatology
(2) Steadiness of wind decreases especially in non-SWmonsoon months which gives an indirect signatureof possible modifications in meso-scale systems
(3) High cloud climatology increases and thereby proba-ble modifications in radiation budget time of occur-rence of maximum and minimum temperatures
(4) Daily statistics for 365 days show more than 80exceedance in present climatology in comparison topast in minimum maximum andmean temperature
(5) Interannual variability analysis in mean temperaturefor this tropical coastal station shows +13∘C100 yearswhich is same as that of global ocean rate
(6) Observed interannual rainfall variability in SWmon-soon and North East monsoon shows decrease intrend by ndash2145mmdecade and increase in trendby +393mmdecade respectively Prognosis on thisobservation points out the likelihood exceedance ofNE monsoon rainfall over the South West monsoonafter the year 2050 for the station But it is prejudicialto infer that the rainfall increase in NE monsoon cancompensate the forecasted decrease in SWmonsoonsince NE monsoon is mostly of heavy rainfall innature as a result of meso-scale convective systemsSuch rainfall runoff is very fast than the slow waterinfiltration feature in association with SW monsoon
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Journal of Climatology 15
rainfall which is essential for irrigation and agricul-tural needs
(7) Decadal variability in surface pressure has shown+006mb and minus010mb for SW monsoon and NEmonsoon respectively
The imprints due to climate change on various meteoro-logical parameters over this coastal station proved that theregion also faces vulnerable situation due to the phenom-ena and therefore necessary engineeringmethodssocioeco-nomic steps are to be undertaken
Acknowledgments
The availability of this unique data for a continuous periodof 45 years is the outcome of concerted and whole heartedefforts put in by the staffs of TERLSIndia MeteorologicalDepartment It is a pleasure to acknowledge with esteemedgratitude the team that worked since 1963 at the TERLSThumba whose efforts have yielded the voluminous uniquedata bank which is available for investigations The authorsare extremely grateful to Dr K Krishnamoorthy DirectorSpace Physics Laboratory VSSC and the reviewers for theirvaluable comments that helped to improve the paper to thefinal form
References
[1] N Oreskes ldquoThe scientific consensus on climatic changerdquoScience vol 306 p 1686 2004
[2] H Ayyar Effect of Pollution on Weather Science ReporterCouncil of Scientific and Industrial Research (CSIR) 1973
[3] K Rupa Kumar A K Sahai K Krishna Kumar et al ldquoHigh-resolution climate change scenarios for India for the 21stcenturyrdquo Current Science vol 90 no 3 pp 334ndash345 2006
[4] P Brohan J J Kennedy I Harris S F B Tett and P DJones ldquoUncertainty estimates in regional and global observedtemperature changes a new data set from 1850rdquo Journal ofGeophysical Research D vol 111 no 12 Article IDD12106 2006
[5] T M Smith and R W Reynolds ldquoA global merged land-air-sea surface temperature reconstruction based on historicalobservations (1880ndash1997)rdquo Journal of Climate vol 18 no 12 pp2021ndash2036 2005
[6] K M Lugina P Y Groisman K Y Vinnikov V V Koknaevaand N A Speranskaya ldquoMonthly surface air temperature timeseries area-averaged over the 30-degree latitudinal belts of theglobe 1881-2004 In Trends a compendium of data on globalchangerdquo Carbon Dioxide Information Analysis Centre OakRidge National Laboratory US Department of Energy OakRidge TennUSA 2005 httpcdiacesdornlgovtrendstempluginaluginahtml
[7] J Hansen R RuedyM Sato et al ldquoA closer look atUnited Statesand global surface temperature changerdquo Journal of GeophysicalResearch D vol 106 no 20 pp 23947ndash23963 2001
[8] S Solomon D Quin M Manning et al ldquoContribution ofworking group I to the Fourth Assessment Report of the IPCCrdquoTech Rep IPCC-AR4 2007
[9] R C Balling Jr and S W Brazel ldquoRecent changes in PhoenixArizona summertime diurnal precipitation patternsrdquo Theoreti-cal and Applied Climatology vol 38 no 1 pp 50ndash54 1987
[10] R Bornstein and Q Lin ldquoUrban heat islands and summertimeconvective thunderstorms in Atlanta three case studiesrdquoAtmo-spheric Environment vol 34 no 3 pp 507ndash516 2000
[11] P G Dixon and T L Mote ldquoPatterns and cause of Atlandarsquosurban heat island-initiated precipitationrdquo Journal of AppliedMeteorology vol 42 pp 1273ndash1284 2003
[12] F Fujibe ldquoLong-term surface wind changes in the Tokyometropolitan area in the afternoon of sunny days in the warmseasonrdquo Journal of the Meteorological Society of Japan vol 81no 1 pp 141ndash149 2003
[13] T Inoue and F Kimura ldquoUrban effects on low-level cloudsaround the Tokyo metropolitan area on clear summer daysrdquoGeophysical Research Letters vol 31 no 5 Article ID L051032004
[14] JM ShepherdH Pierce andA J Negri ldquoRainfallmodificationby major urban areas observations from spaceborne rain radaron the TRMM satelliterdquo Journal of Applied Meteorology vol 41no 7 pp 689ndash701 2002
[15] C Price SMichaelides S Pashiardis and P Alpert ldquoLong termchanges in diurnal temperature range in Cyprusrdquo AtmosphericResearch vol 51 no 2 pp 85ndash98 1999
[16] H N Singh S D Patil S D Bansod and N Singh ldquoSeasonalvariability in mean sea level pressure extremes over the Indianregionrdquo Atmospheric Research vol 101 no 1-2 pp 102ndash111 2011
[17] J Kingwell J Shimizu K Narita H Kawabata and I ShimizuldquoWeather factors affecting rocket operations a review and casehistoryrdquo American Meteorological Society vol 72 pp 778ndash7931991
[18] R E Turner and C K Hill Terrestrial Environment (Climatic)Guidlines for Use in Aerospace Vehicle Development 1982 Revi-sion Technical Memor 82473 National Aeronautics and SpaceAdministration 1982
[19] ldquoSpace Research in Indiardquo in Proceedings of the 38th COSPARMeeting pp 199ndash204 Bremen Germeny 2010
[20] P V Joseph and A Simon ldquoWeakening trend of the southwestmonsoon current through peninsular India from 1950 to thepresentrdquo Current Science vol 89 no 4 pp 687ndash694 2005
[21] S K Dash J R Kumar and M S Shekhar ldquoOn the decreasingfrequency of monsoon depressions over the Indian regionrdquoCurrent Science vol 86 no 10 pp 1404ndash1411 2004
[22] K N Krishnakumar G S L H V Prasada Rao and C SGopakumar ldquoRainfall trends in twentieth century over KeralaIndiardquo Atmospheric Environment vol 43 no 11 pp 1940ndash19442009
[23] National Council of Educational Research and Training(NCERT) India Text book of physicsmdashpart I for class 11 2006
[24] K E Trenberth ldquoRecent observed interdecadal climate changesin the Northern Hemisphererdquo Bulletin of the American Meteo-rological Society vol 71 no 7 pp 988ndash993 1990
[25] T K Karl H F Diaz and G Kukla ldquoUrbanization its detectionand effect in the United States climate recordrdquo Journal ofClimate vol 1 pp 1099ndash1123 1988
[26] M Rebetez andM Beniston ldquoChanges in sunshine duration arecorrelated with changes in daily temperature range this centuryan analysis of Swiss climatological datardquo Geophysical ResearchLetters vol 25 no 19 pp 3611ndash3613 1998
[27] K V S Namboodiri P K Dileep and K Mammen ldquoWindsteadiness up to 35 km and its variability before the SouthWestMonsoon onset and the withdrawalrdquoMausam vol 63 pp 275ndash282 2012
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
16 Journal of Climatology
[28] PMinnis A J Kirk P Rabindra and P Dung ldquoContrails cirrustrends and climaterdquo Journal of Climate vol 17 pp 1671ndash16852004
[29] C S Zerefos K Eleftheratos D S Balis P Zanis G Tselioudisand C Meleti ldquoEvidence of impact of aviation on cirrus cloudformationrdquoAtmospheric Chemistry and Physics vol 3 no 5 pp1633ndash1644 2003
[30] K Eleftheratos C S Zerefos C Varotsos and I KapsomenakisldquoInterannual variability of cirrus clouds in the tropics in elnino southern oscillation (ENSO) regions based on interna-tional satellite cloud climatology project (ISCCP) satellite datardquoInternational Journal of Remote Sensing vol 32 no 21 pp 6395ndash6405 2011
[31] K E Trenberth P D Jones and P Ambenje ldquoObservationssurface and climate changerdquo in Climate Change 2007 ThePhysical Science Basis Contribution of working group I to theFourth Assessment Report of the Intergovernmental Panel onClimate Change S Solomon D Qin and M Manning EdsCambridge University Press Cambridge UK 2007
[32] K R Kumar K K Kumar and G B Pant ldquoDiurnal asymmetryof surface temperature trends over Indiardquo Geophysical ResearchLetters vol 21 no 8 pp 677ndash680 1994
[33] T R Sivaramakrishnan and P S Prakash Rao ldquoSea-breezefeatures over Sriharikota Indiardquo Meteorological Magazine vol118 no 1400 pp 64ndash67 1989
[34] NA SontakkeN Singh andHN Singh ldquoInstrumental periodrainfall series of the Indian region (AD 1813ndash2005) revisedreconstruction update and analysisrdquoHolocene vol 18 no 7 pp1055ndash1066 2008
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
Submit your manuscripts athttpwwwhindawicom
Forestry ResearchInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental and Public Health
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EcosystemsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Marine BiologyJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Environmental Chemistry
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Waste ManagementJournal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
BiodiversityInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of