Introduction - INFLIBNET Centreshodhganga.inflibnet.ac.in/bitstream/10603/6304/12/12...Introduction western half of the Ladakh in Jammu-Kashmir. Severe heat waves are also not so far

Chapter 1

Introduction

In simple words, climate of a place is known as the average of the weather

components including the frequency of extreme events. As per the current practice

weather parameters over a period of at least 30 years constitutes the climate. There are

continuous interactions between the components of climate system such as atmosphere,

biosphere, cryosphere, land and ocean. Natural variation in climate can occur due to

volcanic eruption, continental drift and built up of mountains, changes in tilt angle of

earth’s orbit, sun’s radiation intensity and the slow but large scale ocean circulation etc.

However, changes in greenhouse gas (GHG) concentrations, aerosol emissions and

urbanization give rise to the anthropogenic climate change. Today, climate change is one

of the major issues on the earth system and its impact has already been realized in several

geographical locations and sectors in the society (IPCC 2007). There is a worldwide

concern about the anthropogenic climate change, particularly during the last two decades.

Most important visible changes are those in temperature, snow/ice melt and precipitation

extremes. Before understanding any scientific study on Indian climate, it is essential to

know some of the important diversities in Indian weather and climate.

1.1 Weather and climate of India

India is a south Asian country which lies to the north of the equator between 8.4o

and 37.6o north latitude and 68.7o and 97.25o east longitude. This tropical country is

surrounded by water bodies on three sides, Arabian Sea towards the West, Bay of Bengal

towards the East and Indian Ocean towards the South. India is having unique

geographical features with complex topography. Mountain range such as the Himalayas

broadens in the north and northeast. The Vindhyas separate the Indo Gangetic plain from

the Deccan Plateau. The Satpura, Aravalli and Sahyadri cover the eastern fringe of the

TERI University‐Ph.D. Thesis, 2012 1

Introduction

West Coast plains. The coasts of southern parts of India are known as Western and

Eastern Ghats. Eastern Ghats are irregularly scattered and forms the boundary of the East

Coast plains. Tibetan plateau towards the north of the foothills of Himalayas also

influences Indian summer monsoon. On the northwest part of India, Thar desert extends

from the edge of the Rann of Kachchh of Gujarat up to the frontier of Rajasthan.

Classification of climate for any region is the organization of climate information

for analysis and communication. India is a vast country with diversities in its weather and

climate. Wladimir Köppen, a German botanist and climatologist is most widely known

for the descriptive climate classification system which he first proposed in 1884. After

several modifications, world map of climatic classification by Köppen was introduced in

1936. It combines the average of annual and monthly temperature and precipitation, and

the seasonality of precipitation. According to the Köppen climate classification system,

Indian climate can be divided into six major subtypes. Desert or arid climate regions are

in the west and beyond that there is semi-arid climate. Semi-arid climate can also be

observed between Eastern and Western Ghats. Alpine tundra and glaciers are found in the

north and over the Himalayan ranges. Humid subtropical regions are in the north of

central and eastern India. Tropical wet climate regions are the Western Ghats and Island

territories. Parts of peninsular India experience tropical wet and dry climate.

In India there are four distinct seasons, pre-monsoon (April-May), summer

monsoon (June-July-August-September), post-monsoon (October-November) and winter

(December-January-February). India is a tropical country with hot weather conditions

that varies from region to region. In the pre-monsoon months vast land portion of India is

dominated by intense solar heating which leads to heat wave conditions. Similarly cold

wave conditions during winter season occur due to the intense high pressure cells and

passing of western disturbances. There is no absolute definition for heat or cold wave

events. The term is relative to the average weather condition of a region of study.

According to a study by Raghavan (1967), severe cold waves develop very often in situ

within the country itself and account for the higher incidence in certain isolated regions.

Irrespective of the intensity, severe cold wave are mostly confined to either eastern or the


Introduction

western half of the Ladakh in Jammu-Kashmir. Severe heat waves are also not so far

been observed to migrate from the neighboring countries Raghavan (1966). They develop

in situ within the country itself and expand from West Pakistan to affect Northwest India.

He further concluded that available statistics do not suggest any periodicity in the

incidence of extreme temperature conditions in any region or in the country as a whole.

He considered the persistency of the waves over different subdivisions where they

dissipate or wherefrom they migrate to adjacent regions. In India more than 70% of its

population relying on agriculture directly or indirectly and thus the impact of extreme

weather events is critical. In the last two decades India has been affected by successive

extreme temperature events, monsoons flooding and droughts (De et al. 2005). Snow is

also an important component of the hydrological cycle. Major contribution of many parts

of the world snow is in the form of precipitation or total annual water supply. The

allocation of limited water resources has significant economic and policy consequences.

Eurasian, Tibetan and Himalayan snow in winter and spring may affect the Indian

summer monsoon circulation and rainfall. It may influence both river basin runoff and

climate change dynamics. It has been revealed that snow cover/depth variations during

winter in Eurasia are not only associated with monsoon rainfall in Southeast Asia but also

recognized as an effective source of freshwater flowing to the Arctic Ocean (Rogers et al.

2001), and may thus be linked to the global thermohaline circulation (Walsh et al. 1998),

which is a major determinant of the global climate.

In India two major monsoon systems are observed, southwest/summer monsoon

from June to September and northeast/winter monsoon from October to November.

Monsoon is produced by differences between land and sea temperatures in eastern and

southern Asia. It is a seasonally varying wind system, e.g. in the Indian Ocean winds are

southwesterly with moist air and high precipitation in summer, northeasterly with dry air

and clear skies in winter. During the post-monsoon months northeast monsoon dominates

over the southern parts of Peninsular India particularly in Andhra Pradesh, Rayalaseema,

Tamilnadu and Pondicherry. The principal components of northeast monsoon system are

Siberian high pressure system, northeasterly lower tropospheric flow, wind surges carried

by the northwesterly monsoon flow along the western shores of South China Sea, the


Introduction

monsoon trough located near to the north of the equator in December and south of the

equator in January and February, the west Pacific high and the subtropical jet stream of

winter. At the beginning of October, a trough of low pressure develops over the south of

Bay of Bengal and equatorial maritime air moves towards the southern India that causes

northeast monsoon rainfall (Kripalani and Kumar, 2004). They found that Indian Ocean

dipole positive phase also enhances the rainfall activity of northeast monsoon and

negative phase suppresses. Dhar and Rakecha (1983) and Singh and Sontakke (1999)

identified enhancement in northeast monsoon rainfall during El Niño events.

1.2 Indian summer monsoon main features

The weather and climate of India are dominated by the summer monsoon, which

returns with remarkable regularity in each summer and provides the rainfall needed to

sustain over a billion of people. The vastness of Indian sub-continent and the unique

configuration of the east African highlands and the Tibetan plateau mean that the Indian

summer monsoon is the most vigorous and influential of all the monsoon circulation over

the globe (Boucher 1998). It lasts from June to September and about 80% of the total

annual precipitation is received over a large part of the country except in Jammu &

Kashmir and Tamil Nadu. The economy of India is largely based on agriculture which in

turn depends on the temporal and spatial variation of rainfall especially during Indian

summer monsoon season.

Broadly, the monsoon is an atmospheric phenomenon in which there is seasonal

reversal of the mean surface wind. Southwesterly surface winds of the summer monsoon

reverses its direction to northeasterly surface winds of the winter monsoon. The principal

components of south Asian summer monsoon are the Mascarene high of the southern

hemisphere, intense low over Pakistan, monsoon trough over North-central India, Tibetan

high, Tibetan anti-cyclone, tropical easterly jet stream at the upper level, cross-equatorial

low-level jet over coastal Africa, Somali jet, southwesterly monsoon flow over the

Arabian sea monsoon disturbances and cloud cover which leads to rainfall. South Asian


Introduction

monsoon is expected to be driven by seasonal variations in land–sea temperature contrast

between Asian landmass and adjacent ocean. It is well known that seasonal reversal in

wind direction is related to large scale heat sources and sinks. In the case of south Asian

summer monsoon, belt of strong convective heating is observed over the major part of the

northern India. Tibetan Plateau also acts as an elevated heat source in summer resulting

in sensible heat fluxes. Heat sink of the Asian summer monsoon resides majorly over the

Mascarene High.

Every year, onset of Indian summer monsoon occurs over Kerala, the southwest

coast of India. Onset of monsoon generally starts near to the first week of June. It is a

crucial event which indicates the beginning of rainy season in India. After that rapid

substantial and continuous progress in rainfall is noticed over Indian land that extends

towards the north. However, Indian monsoon system is highly irregular and variable at

intra-seasonal, annual, biennial and inter-annual timescales. The northward progression

of the monsoon is symptomatic of a large scale transition of a deep convection from the

equatorial to continental regions (Webster et al. 1998, Pai and Rajeevan 2007). By middle

of July, monsoon covers the whole country. Uneven distribution of rainfall can adversely

affect the agricultural sector. Variability in Indian summer monsoon can be studied on the

basis of active and break spells. Active spell leads to continuous and good amount of

rainfall whereas breaks are the discrete rainfall process that results in lower amount of

rain. Long and intense break spells can influence monsoon rainfall up to a large extent

(Gadgil and Joseph 2003). Frequent and prolonged break conditions can lead to drought

condition. Recently, Rajeevan et al. (2010) have proposed new method to define active

and break conditions. Only July and August are considered by them for active and break

spells in which the normalized anomaly of the rainfall over the monsoon core zone

exceeds 1 or is less than −1.0 respectively, provided the criterion is satisfied for at least

three consecutive days. They observed longer life span of breaks than active using

observed gridded daily data for period 1951-2007. The progress of summer monsoon

from northern Australia towards the eastern foothills of Himalayas and its reverse in the

annual cycle is an important component of the monsoon. The dates of the withdrawal of

the Indian monsoon are the reverse propagation of the last monsoon rainfall that moves


Introduction

from northwest towards southeast. Withdrawal of Indian summer monsoon is more

variable than its onset. Syroka and Toumi (2004) defined withdrawal of Indian summer

monsoon in terms of wind fields at 850hPa. The retreat in monsoon follows a period of

enhanced convective activity over the Indian subcontinent and is associated with a dry

phase of the intraseasonal oscillation.

ISMR has large spatial and temporal variations and there are several occasions

when some parts of the country receive heavy rainfall while at the same time some other

parts have serious rainfall deficiency (Mooley and Parthasarathy 1984; Parthasarathy et.

al. 1995; Dash et al. 2002). Parthasarathy et al. (1995) calculated and analyzed summer

monsoon rainfall in India as a whole. Statistical analysis of ISMR over different regions

by Dash et al. (2002) shows a large spatial variations from region to region. They

observed minimum and maximum variations in rainfall over Northeast and Northwest

India respectively.

The study of changes in the spatial and temporal distribution of rainfall in India

has great relevance in the context of planning policy formulation especially in the context

of global warming. Also, the distribution of ISMR has a large variability and therefore it

is always a challenging task for scientists to predict and detect extremes either using

observational data or model simulated data. Simulation of rainfall and its variability by a

global model at different time scale is difficult due to coarse resolution of the model. The

global models are unable to capture extremes of rainfall with good confidence. Now-a-

days, the regional models are being used worldwide by scientists for rainfall simulation

due to their comparative high resolution and better physics. Detection of rainfall extremes

using regional model simulation during ISM season would be helpful to assess the

damage due to extremes of rainfall.

A number of studies on Indian summer monsoon are made by different

researchers with the help of GCMs. Under Monsoon Numerical Experimentation Group

(MONEG), a set of seasonal integrations was carried out using a number of GCMs all

over the world (WMO 1992 & 1993). Gadgil and Sajani (1998) extensively examined the

results of 30 GCMs during the period from January, 1979 to December, 1988 under


Introduction

Atmospheric Model Intercomparison Project (AMIP) and inferred the short comings of

dynamical models in simulating ISMR. Most of the GCMs poorly simulate the rainfall

along the West Coast, North Bay of Bengal and North East India with large bias in mean

monsoon rainfall (Kripalani et al. 2007; Rajeevan and Nanjundiah 2009). The effects of

regional forcing or non-linear steep topography of Himalayas and Western Ghats may not

be fully captured by the GCMs because of their coarser resolutions. In order to resolve

regional features at finer scale, performance of a high resolution GCM at 20km horizontal

resolution was observed by Rajendran and Kitoh (2008). After analysis of present and

future climate both at 10 years time scale, they indicate better performance in simulation

of ISMR from higher resolution GCM. However, such high resolution GCMs require a

large number of good quality computational resources.

Today, regional models are increasingly used by scientists all over the world to

better resolve the weather systems of high resolutions. Bhaskaran et al. (1996) simulated

the Indian summer monsoon for four years using a regional climate model with a

horizontal resolution of 50 km nested with global atmospheric GCM. Their study showed

that regional model derived precipitation is higher by 20% than GCM due to stronger

vertical motions arising from finer horizontal resolution. Using regional Eta model of

National Centers for Environmental Prediction, nested in the GCM of Center for Ocean-

Land-Atmosphere (COLA), Ji and Vernekar (1997) verify its performance for two

contrasting summer monsoons in 1987 and 1988. Their comparative studies showed that

Eta simulations were closer to the observations than GCM over India and southeast

China. Their comparative studies showed that for 1987, the Eta model simulates deficient

summer monsoon rainfall over northern and peninsular India and the Indonesian region

and excess rainfall over southeast China, Burma and the sub-Himalayan region compared

to 1988. Due to increase in the availability of computational resources, now-a-days

longer simulations are performed by the scientists. Rupa Kumar et al. (2006) used a high

resolution regional climate model PRECIS (Providing Regional Climates for Impacts

Studies) which was developed by Hadley Centre for Climate Prediction and Research to

study the climate change scenarios for present (1961–1990) and a future period (2071–

2100) and observed significant improvement in representation of the spatial pattern of


Introduction

ISMR compared to that simulated by the GCM. The skills of seasonal precipitation

predictions can also studied using multi-model ensemble (Kar et al. 2006; Sahai et al.

2008). Mesoscale models are also used to study the characteristics of Indian monsoon

(Dudhia 1989; Bhaskar Rao et al. 2004).

The regional climate model (RegCM) of Abdus Salam International Centre for

Theoretical Physics (ICTP) has been successfully used by several researchers to examine

atmospheric circulation features at different temporal and spatial scales. It is increasingly

used to examine the circulation and precipitation patterns (Chow et al. 2006; Dash et al.

2006b; Abiodun et al. 2008; Gao et al. 2008; Davis et al. 2009; Ratnam et al. 2009),

regional climate change (Mearns et al. 1995; Pal et al. 2004; Diffenbaugh et al. 2005;

Giorgi and Coppola 2007; Im et al. 2008, 2010) and seasonal climate variability

(Rauscher et al. 2006; Seth et al. 2007) over several parts of the world. Rauscher et al.

(2006) performed the downscaling technique using RegCM3 over tropical and sub–

tropical South America for two test seasons during El Niño and La Niña years. Their

studies show that NCEP/NCAR reanalysis and GCM simulations driven with RegCM3 is

able to replicate the distribution of daily rainfall intensity in most of the regions. Chow et

al. (2006) applied some convection suppression criteria to MIT–Emanuel cumulus

parameterization scheme. Their study shows some significant improvement in RegCM3

to simulate Asian summer monsoon precipitation, particularly the precipitation over

southeastern China and the Mei–yu rain band over the East Asia region. Davis et al.

(2009) customized their study for the precipitation processes over the tropical regions of

eastern Africa and the Indian Ocean using RegCM3 with all the existing convective

schemes for determining the most realistic spatial distribution of rainfall and partitioning

of convective/stratiform rainfall. Their results suggest that the convective schemes of

Grell with Arakawa–Schubert (AS) and Fritch–Chappel (FC) closures scheme

underpredicted the rainfall rates over the land, while over the ocean FC overestimates and

AS underestimates the convective rainfall MIT–Emanuel scheme provided the most

realistic spatial distribution of convective rainfall despite the tendency for overestimating

total rainfall. Sylla et al. (2009) examined the present day integrations (1981–2000) using

RegCM3 with both NCEP/NCAR reanalysis data and output from a coupled


Introduction

atmospheric–ocean general circulation model (AOGCM) nested over West Africa.

Spatial distributions of RegCM3 simulations are shown to be realistic when compared

with observations and also offered some improvements compared to the AOGCM driving

fields. The relationship between rainfall changes and monsoon dynamics in multidecadal

experiments over West Africa was performed by Sylla et al. (2010) using the RegCM3 at

40km resolution for the recent past (1981–2000) and for the late 20th century (2081–

2100) climate conditions under increased greenhouse gas forcing (A1B scenario) driven

by the global climate model European Center/Hamburg 5 (ECHAM5). With respect to

the recent past climate, late 20th century scenarios show drier conditions over the Sahel

and wetter conditions over the orographic areas. Sahel drying may be associated with

changes in the wind circulation pattern and is similar to the conditions found in the late

twentieth century observed drought over the region.

Using RegCM, relatively few researchers have focused on Indian sub–continent

(Liu et al. 2004; Shekhar and Dash 2005; Landman et al. 2005; Dash et al. 2006b; Singh

et al. 2007; Ratnam et al. 2009 and Ashfaq et al. 2009). Sensitivity experiments using

RegCM and Tibetan snow as one of the boundary condition were conducted by Liu et al.

2004 and Shekhar and Dash 2005. Liu et al. 2004 demonstrated the effect of anomalous

snow cover over the Tibetan plateau with the South Asian summer monsoon by

numerical simulations using the RegCM2. They found that the heavier snow cover over

the plateau can reduce the intensity of the South Asian summer monsoon and rainfall to

some extent, but the influence is only obvious in early summer and almost disappear in

later stages. Shekhar and Dash 2005 tested RegCM3 to study the effect of Tibetan

snowfall in the month of April on the Indian summer monsoon circulation and associated

seasonal rainfall. Their sensitivity experiment shows that Tibetan snow results in weak

lower level monsoon westerlies and upper level easterlies therefore the Indian summer

monsoon rainfall reduced over entire India and its five homogenous zones. RegCM3

ability over the southwestern Indian Ocean to reproduce observed cyclones and their

land–falling tracks was performed by Landman et al. 2005. Their results show that the

regional model can produce cyclone–like vortices and their tracks up to some extent.

Singh et al. 2007 investigate the impact of Indian Ocean sea–surface temperature


Introduction

anomaly on ISMR using RegCM3. They observed that regional warming of SST over the

Indian Ocean enhanced the monsoon precipitation mainly over south and west Peninsular

India, Indian Ocean and reduced precipitation over northeast India. Ratnam et al. (2009)

coupled the RegCM3 with Regional Ocean Modeling System (ROMS) and show more

realistic spatial and temporal distribution of ISMR compared to the uncoupled

atmosphere–only model.

Over the Indian domain, performance of RegCM driven with reanalysis data at

their boundaries was demonstrated in few studies (Dash et al. 2006b; Ashfaq et al. 2009).

RegCM3 has been successfully integrated by Dash et al. (2006b) to simulate the salient

features of summer monsoon circulation with a horizontal resolution of 55km over a

South Asia domain for period April–September of the years 1993 to 1996. Their study

shows that, the Grell convection precipitation scheme has performed better than other

available convection schemes in simulating both summer monsoon circulation and

rainfall. Their study also indicates that RegCM3 can be effectively used to study the

monsoon processes over the south Asia region. Using RegCM3, Ashfaq et al. 2009 show

the simulated dynamical features of the summer monsoon are comparable with reanalysis

data. They have used a high resolution nested climate modeling system to investigate the

response of South Asian summer monsoon dynamics to anthropogenic increases in

greenhouse gas concentrations. Further they found that there is an overall suppression of

summer precipitation, a delay monsoon onset and an increase in the occurrence of

monsoon break periods.

Next to the sea surface temperature (SST), snow cover/depth is the most

important surface condition to affect the Indian summer monsoon rainfall (ISMR). Along

with the temperature of snow surface, sensible heat flux and latent heat flux are the

important factors that define surface energy balance. Albedo and related sensible heat

flux are associated with snow cover while snow depth significantly affects both sensible

and latent heat flux. There is weakening of sensible heat flux due to high albedo from

large areal extent of snow cover that leads to reflect more solar radiation while moisture

content of soil from snow melt utilises some amount of solar energy in evaporation


Introduction

(latent heat flux) process. Thus, when there is more snow cover/depth, relatively a small

part of solar energy is utilised in heating continental landmass during summer prior to

monsoon. The sensible heat flux at the higher altitude like in the case of the Tibetan

Plateau is one of the important factors in land–sea heating contrast. It is further enhanced

due to the latent heat released in the troposphere. Excessive snowfall during the winter

delays melting of snow in spring and consequently furthers delay in buildup of land–sea

temperature contrast which drives the monsoon. The relationship between Indian summer

monsoon and snow cover/depth has been studied extensively by several scientists in the

past based on observed data as well as using numerical models. The following paragraphs

give brief review of these studies.

1.3 Observational studies on snow-monsoon relationship

Long back Blanford (1884) based on the study of weather reports suggested

negative influence of Himalayan snow on the summer monsoon of India and Burma. Luo

and Yanai (1984), He et al. (1987) and Murakami (1987) summarised that the high

elevated Tibetan Plateau acts as a heat source in summer and heat sink in winter, in

addition to its acting as a mechanical barrier that affects flow pattern around it. Further, in

summer a temperature gradient develops in the upper troposphere between Tibetan

Plateau and equatorial Pacific which is further associated with the onset of South Asian

summer monsoon (He et al. 1987; Li and Yanai 1996; Shaman and Tziperman 2005;

Yanai and Wu 2006). Zhang et al. (2004) observed interdecadal increase in spring snow

depth in Tibetan Plateau after late 1970s in his study of the period 1962–1993. This

excessive snowfall is concurrent with excessive precipitation over northern India,

northwestern China and Western Asia and with drought over Central Asia during March–

April. The increase of the snow depth is also related to the excessive summer rainfall

over the Yangtze River valley and the drought conditions in southeastern and

northeastern China and the Indochina peninsula.

The negative relationship between Tibetan snow and ISMR has been extended to

that between Eurasian snow cover/depth and ISMR. Studies of Hahn and Shukla (1976),


Introduction

Dey and Bhanu Kumar (1982), Dickson (1984), Barnett et al. (1989) and Sankar Rao et

al. (1998) based on observational data have inferred the negative relationship between

Eurasian snow cover and ISMR. Bamzai and Shukla (1999) and Kripalani and Kulkarni

(1999) reexamined the relationship and found significant inverse correlation for West

Eurasian region while positive correlation for East Eurasian region. Bamzai and Shukla

(1999) after analyzing areal extent of snow concluded that winter and spring snow covers

of southern Eurasia and the Himalayas have high interannual variability and are poorly

correlated with the subsequent monsoon rainfall. They used satellite-derived snow cover

data for 22 years (1973–1994) and studied the frequency of occurrence of snow at grid

points over Eurasia and correlated December, January, February and March mean snow

cover anomalies for four regions with the subsequent ISMR. Using Historical Soviet

Daily Snow Depth (HSDSD) version-1 dataset, Kripalani and Kulkarni (1999) studied the

monthly climatology and variability of snow depth and its interaction with ISMR. Instead

of taking Eurasia as whole as in earlier studies, they converted the monthly snow depth

data for 284 stations into 70 uniform blocks and correlated it with ISMR time series.

They conjectured the existence of a mid-latitude long wave pattern with an anomalous

ridge (trough) over the Eastern Siberia during the winter prior to a strong (weak)

monsoon. They also identified reversal in correlations between pre-monsoon and post-

monsoon months over West and East Eurasia. This reversal in correlation could be

associated with mid-latitude circulation pattern and support the theory proposed by

Meehl (1997) that monsoon plays an active part in the tropospheric biennial oscillation.

He further inferred that snow cover anomaly may be an artifact of the mid-latitude

circulation pattern associated with convective heating anomalies, rather than an

independent forcing. The physical mechanism behind the snow-monsoon relationship has

also been examined by several other authors (Liu and Yanai 2002; Ueda et al. 2003;

Yasunari 2006). Liu and Yanai (2002) have examined the large scale mid-latitude

circulation pattern associated with Eurasian snow cover/depth and Asian summer

monsoon. They observed northerly wind anomaly during the high snow year leading to

weaker monsoon over East Asia. During heavy spring snow cover in northwestern

Eurasia, the cooling centre of the cyclonic anomaly in the lower troposphere leads to a


Introduction

Rossby-wave-train-like circulation response. That makes atmospheric disturbances to

propagate from Europe to Asia. Ueda et al. (2003) based on northern Eurasia spring snow

cover variations and its relation with atmospheric circulation mechanism identified that

retreat of snow in spring is controlled by winter-spring circulation anomalies along with

northward warm advection anomalies. Fasullo (2004) using satellite observations shows

that the areas with larger variability in snow cover in southwestern Asia, Himalayan and

Tibetan Plateau and Eurasia as a whole have weak correlation with all India rainfall.

However, during weak El Niño southern oscillation (ENSO) years this negative

correlation is strong in southwestern Asia, Himalayan and Tibetan regions. During an El

Niño event, the perturbation to the development of troposphere temperature anomalies

over the southern Eurasia is observed in a study by Xavier et al. (2007). This remote

climatic phenomenon over the Eurasia region may also influence ISMR.

Dash et al. (2004b) examined the number of days with different snow depths and

found those with 5–50 cm in the months of winter and spring in West Eurasia (East

Eurasia) having significant negative (positive) correlation with ISMR. Further using

HSDSD-II data set, Dash et al. (2005) statistically examined the empirical relationship

between the anomalies in winter/spring snow depth over west (25–70oE, 35–65oN) and

east (70–140oE, 35–65oN) Eurasia and ISMR for the period 1951–1994. Their results

show that 57% of heavy snow events and 24% of light snow events over West Eurasia are

followed by deficient and excess ISMR, respectively. They concluded that large scale

changes in mid latitude circulation pattern arising due to West Eurasian snow anomaly

could be used as indicators of weak/strong monsoon circulation and deficient/excess

ISMR. Ye et al. (2005) used HSDSD-II data set along with monthly gridded global

precipitation and statistically analyzed the connection between the early snow onset dates

over northern Eurasia and the following year’s summer monsoon over Southeast Asia.

They undertook and reported that when the onset of snow in the northeastern Siberia is

earlier than normal, there is more snow cover during the early season, more moisture

coverage, higher prevalence of southwesterly monsoon winds and late monsoon

withdrawal over Southeast Asia.


Introduction

1.4 Modeling studies on snow-monsoon relationship

Zwiers (1993) and Vernekar et al. (1995) using global climate models and Dash et

al. (2006a) using regional climate model RegCM3 demonstrated the negative influence of

Tibetan snow depth in spring on the next summer monsoon rainfall. Sensitivity studies

over Eurasia with general circulation models (GCMs) such as those of Barnett et al.

(1989) and Vernekar et al. (1995) have shown that when large, spatially coherent,

positive snow anomalies are imposed in winter/spring, the monsoon circulation in the

following summer is weaker than average in Southeast Asia. Vernekar et al. (1995), after

conducting model experiments concluded that February snowfall results deficient rainfall

in the following Indian summer monsoon months. Dash et al. (2006b) used observed

Eurasian snow depth values as one of the boundary conditions in a spectral GCM and

integrated the model for 6 months to examine the influence of Eurasian snow depth on

the monsoon circulation. They designed the model experiments for contrasting years of

snow depth values of April over Eurasia followed by contrasting ISMR years. The

model-simulated mean monsoon circulation features for high and low snow depth years

were compared with the corresponding years of NCEP/NCAR reanalyzed fields. In their

study, the evolution of weak/strong monsoon circulation from the mid-latitude circulation

in response to high/low Eurasian snow depth during summer monsoon was indicated.

Turner and Slingo (2010) using a coupled climate model HadCM3 reexamined the

negative relationship to monsoon rainfall exists from both northern West Eurasia and

Himalayan/Tibetan Plateau in the absence of ENSO conditions. They demonstrated that

in this model forcing from Himalayan region dominates and reduce the heating of the

troposphere over the Tibetan Plateau. Using historical coupled ocean–atmosphere

simulations of the coupled model intercomparison project3 (CMIP3) database and

observations of snow cover and snow depth data, Peings and Douville (2010) further re-

examined the snow-monsoon relationship. They found the East–West dipole pattern of

snow cover anomalies over Eurasia using observational data which is not confirmed by

model simulations. Some models which indicate strongest snow-monsoon relationship

also show an unrealistic impact of ENSO on both winter snow cover and summer

monsoon.


Introduction

1.5 Climate change evidences in India

There are a number of different types of extreme weather events that include

temperature extremes such as heat waves and cold waves, rainfall extremes like intense

rainfall, drought, intra-seasonal and inter-annual monsoon variability, cyclones, wind

storms, snow storms and other events like fog and snowfall. These events can be defined

on the basis of their frequency of occurrences, persistence and magnitude at spatial and

temporal scales and their widespread impacts on society. Statistical techniques can be

used for the analysis of extremes and their trends. Scientific explanation can be given

behind the causes of extreme events and their association with circulation and physical

processes. IPCC reports projected that there is 90-99% chance of rise in the intensity of

maximum surface air temperature and precipitation. The World Meteorological

Organisation (WMO) and Indian Meteorological Organisation (IMD) latest reports on

climate change have also concluded the most anticipated effects of climate change are

possible increase in the intensity and frequency of extremes especially temperature and

rainfall. These extreme weather events are not mutually exclusive. Loss of life in India

due to the extreme weather events is frequently high. The recent occurrences of extreme

weather events in India and their unusual intensities and duration are matters of concern

for scientists and society. These events include extremes such as rainfall events leading

to flooding in Mumbai during the last couple of monsoon seasons also severe heat waves

in the summers in Orissa in 1998, 1999 and 2000 and Andhra Pradesh in 2003. These

events resulted in considerable loss of lives and property.

Several scientists have examined extreme temperature events in India which

include those conducted by Raghavan (1966, 1967), De and Mukhopadhyay (1998), Pai

et al. (2004) and De et al. (2004, 2005). They have used available meteorological

measurements at several places in the country. Pai et al. (2004) found significant increase

in the frequency, persistence and spatial coverage of extreme temperature events in the

decade 1991-2000 compared to the two earlier decades 1971-1980. The effect of

urbanization in fifteen cities in India during the second half of the last century was

examined by Prakasa Rao et al. (2004) in terms of changes in the respective


Introduction

meteorological parameters. They concluded that the frequency of occurrence of summer

time maximum temperature more than 35oC has decreasing trend in north India and

increasing trend in south India. They also inferred that winter time minimum temperature

less than 10oC has increasing trend in northern Indian cities. However, their results are

not statistically significant for all the cities considered. Dash et al. (2007) and Dash and

Hunt (2007) based on observational data have examined the changes in the characteristics

of surface air temperatures during the last century over seven homogeneous regions in

India. Dash et al. (2007) identified relatively maximum increase in the daily maximum

temperature in the West Coast as compared to other homogeneous regions. They have

further highlighted the heat wave conditions that occurred at seven stations in the East

Coast of India during the period 19 May to 10 June in the year 2003. Their study has

identified four stations in the East Coast of India where the maximum temperatures

crossed their respective hundred year maximum values by about 1oC or so. Similar

unusual severe heat waves occurred in a large part of India in second half of May 1998

and affected millions. Maximum numbers of heat wave conditions were reported between

the years 1980 and 1998. These occurrences of heat wave conditions were comparatively

higher than those in the previous decade 1979-1988 (De and Mukhopadhyay, 1998). Cold

wave conditions observed in the hilly regions in the north India and adjoining plains are

usually influenced by the weather systems called the Western Disturbances. These

systems are transient winter disturbances in the mid latitude westerlies which often have

weak frontal characteristics. De et al. (2005) based on observations from various sources

have inferred that the occurrence of cold wave conditions in the last century was

maximum in the Jammu & Kashmir region followed by Rajasthan and Uttar Pradesh.

Results of Pai et al. (2004) further show that cold wave conditions were most experienced

in the west Madhya Pradesh in the decade 1971-1980, in Jammu & Kashmir in 1981-

1990 and in Punjab in 1991-2000.

Extreme temperature events can be categorized under different types depending

on their intensity and duration. Usually heat/cold wave conditions with large intensity

spanning over a number of days get noticed due to their widespread impacts on society in

terms of loss of life. However, there are also other categories of warm/cold exceedences


Introduction

which may affect sectors such as health and agriculture. Abrupt and frequent temperature

changes may give rise to more vectors and diseases. Working hours may also be reduced

due to heat stress (Kjellstrom et al. 2009). Small changes in temperature may adversely

affect the growth of crops and hence agricultural products to a large extent (Attri and

Rathore 2003; Peng et al. 2004). Hence, it is essential to categorize the changes in day

and night temperatures depending on their intensity and duration and then critically

examine those at regional as well as national levels.

It is a known fact that precipitation is affected by the strength of the monsoonal

flows and amount of water vapor transported. In an experiment based on quadrupling of

CO2 using a GCM, Knutson and Manabe (1995) found that the monsoonal flow and the

tropical large-scale circulation weaken in the warming atmosphere. There is emerging

consensus that in a warmer atmosphere, the effect of enhanced moisture convergence in a

warmer atmosphere dominates over weakening of the monsoon circulation resulting in

increased monsoonal precipitation (Douville et al. 2000; Giorgi et al. 2001a, b;

Stephenson et al. 2001). Douville et al. (2000) find a significant spread in the summer

monsoon precipitation anomalies despite a general weakening of the monsoon circulation

and conclude that the changes in atmospheric water content, precipitation and land

surface hydrology under greenhouse forcing could be more important than the increase in

the land-sea thermal gradient for the future evolution of monsoon precipitation.

Stephenson et al. (2001) propose that the consequences of climate change could manifest

in different ways in the physical and dynamical components of monsoon circulation.

Kang et al. (2002) commented the lack of scientific shortcoming on mean monsoon

climate and its variation on different time scale restricted them to draw any meaningful

conclusions. The monsoon flow through Peninsular India in the lower troposphere is

dominated by the low level jet stream (Joseph and Sijikumar 2004). Rao et al. (2004)

found strong decreasing trend in the tropical easterly jet strength during the Asian

summer monsoon seasons in recent years. Weakening of monsoon circulation in terms of

the decrease in its horizontal and vertical wind shears is observed in a study by Dash et

al. (2004a). Goswami et al. (2006) observed insignificant change in the mean monsoon

rainfall in India. However, they observed significant increase in the frequency and


Introduction

magnitude of extreme rain events and decrease in moderate events over central India.

Dash et al (2009) further suggested weakening of the summer monsoon circulation over

India in the study on changes in the frequencies of different categories of rain events.

This hypothesis of a weakening of monsoon circulation is supported by significant

reduction in the 850hPa wind fields in the National Centers for Environmental Prediction

(NCEP)/National Center for Atmospheric Research (NCAR) reanalyzed data. Further,

they indicate significant rise in short and dry spells whereas long spells show decreasing

trend. Ashfaq et al. (2009) used a high resolution climate model to study the monsoon

pattern in changing climate and shows the overall weakening of the summer monsoon

precipitation over South Asia.

It is reported in the IPCC AR4 (2007) that the pattern and magnitude of ISMR

will be changed under warmer climate that is based on simulations of IPCC models under

different forced scenarios. The most emission scenarios suggest that future changes in

regional climate are still likely to be dominated by increasing greenhouse gas forcing

rather than changes in sulphate and absorbing aerosols, at least over the South Asian

region (IPCC 2007). The variability of monsoon circulation under changing content of

carbon dioxide is studied by Degtyarev (2008) using numerical model and analyzed

monsoon circulation indices calculated from the zonal-wind speeds simulated in the

upper and lower troposphere and model precipitation rates. The skill of predicting the

seasonal mean monsoon rainfall by almost all the global climate models remains very

small. The most emission scenarios suggest that future changes in regional climate are

still likely to be dominated by increasing greenhouse gas forcing rather than the changes

in sulphate and absorbing aerosols, at least over the South Asian region. Number of

scenarios generated by Atmosphere-Ocean General Circulation Models (AOGCMs)

under IPCC can be used to investigate the potential consequences of climate change and

weather for the environment and society over the global. Further studies are needed for

understanding changes in monsoon circulation pattern that could lead to increase

vulnerability due to the impact of climate change. The skill of predicting the seasonal

mean monsoon rainfall by almost all the global climate models remains very small. In

warming climate, variations of the Himalayan/Tibetan/Eurasian snow and ground surface


Introduction

temperature and links with IMSR are not clear, although some progress has been made in

analyzing snow depth and surface temperature over the western Himalaya under a

doubling CO2 scenario (Parth Sarthi et al. 2011).

1.4 Background and scope of this thesis

Indian summer monsoon has its own characteristics of evolution such as onset,

active, break and withdrawal phases which have been studied extensively. However, the

evolution of Eurasian snow is yet to be examined. Further, it is interesting to explore the

characteristics of evolution of snow over the different regions of Eurasia and their

relationship with the evolution characteristics of summer monsoon. In this thesis, a

detailed examination has been done on the starting and the ending dates of snowfall over

different regions of Eurasia and attempts have been made to explore any relationship with

onset of ISMR. It is also essential to know the detailed temporal and spatial distributions

of snow depth over Eurasia and precipitation over Indian landmass in order to make use

of these findings in long range monsoon prediction.

The regional climate model of the ICTP has been successfully used by several

researchers such as those by Dash et al. (2006b), Giorgi et al. (2007) and Im et al. (2010)

to examine atmospheric circulation features of different temporal and spatial scales. In

the earlier study of Dash et al. (2006b), RegCM3 has been successfully integrated to

simulate the salient features of summer monsoon circulation from 1993-1996. Their study

indicates that RegCM3 can be used to study the monsoon processes over the south Asia

region. In order to understand and reduce the model bias for Indian summer monsoon,

detail analysis need to be done using long term RegCM3 integrations.

Extreme temperature events always influence ecosystem and human society. Rise

in global mean temperature and increase in the number of warmer years during the past

two decades have been investigated by a number of researchers (Jones and Briffa, 1992;

Mann et al. 1998; De et al. 2005). Studies suggest that extreme temperature events are

changing over the world. Similar inference over India has been based on observed


Introduction

temperature values. However, these observations are not uniform in space and time

duration. Currently, a good quality dataset of daily maximum and minimum temperatures

for the period 1969-2005 is prepared by the India Meteorological Department (IMD) at a

resolution of 1ox1o over the Indian land points. It provides a good scope to study the

changes in different categories of temperature extremes in India. Depending on intensity

and duration, moderate and intense temperature events need to be categorized and

studied.

Kripalani et al. (2007) examined south Asian summer monsoon precipitation

variability in models of IPCC AR4. They found that out of 22 models, 19 could able to

capture maximum rainfall during the summer monsoon season. In order to capture more

regional features of Indian summer monsoon the higher horizontal resolution of the IPCC

models are considered in this study. Only those important models are considered whose

average latitudinal surface resolution varies from 1.1 to 2.0 degree approximately. Based

on this criteria five models are selected that are CCSM3, ECHAM5, GFDL2.1,

MIROC3.2 (hires) and UKMO-HadGEM1. The simulations of these models can be used

to investigate the changes in precipitation, temperature and wind circulation pattern in

future climate with respect to the present climate.

Based on the above discussion, the present thesis has the following specific objectives:

1. To study the characteristics of Eurasian snow depth with respect to Indian summer

monsoon rainfall.

2. To analyze of Indian summer monsoon rainfall and temperature characteristics

using long term integration of RegCM3 and observed data.

3. To re-examine the snow-monsoon relationship using the IITD T80L18 GCM

simulations

4. To compare IPCC AR4 models simulated Indian summer monsoon characteristics


Introduction

The thesis has been organized into six chapters. This chapter 1 introduces the topic and

deals briefly with the discussion on the important issues based on earlier literature.

Chapter 2 provides a detailed discussion on the characteristics of Eurasian snow and its

relationship with ISMR. The connections of snow starting dates with monsoon onset

dates at Kerala Coast are examined in detail. Also, the strength of snow depth in different

regions in Eurasia is related with strength of summer monsoon rainfall in five

homogeneous rainfall regions in India.

Chapter 3 presents the experimental work using ICTP regional climate model, RegCM3.

A brief analysis of summer monsoon features simulated by RegCM3 such as seasonal

climatology, intra-seasonal and inter-annual variations and compared those with

observations. Extreme rainfall years are also considered for further verifications.

Chapter 4 proposes the study on spatial and temporal changes in the characteristics of

maximum and minimum temperatures and their extremes in India as a whole as well in

its seven homogeneous temperature regions using IMD observational data. Temperatures

are categorized based on their intensity and duration and analyzed on interannual and

interdecadel time scales.

Chapter 5 is aimed to know the possible changes in ISMR, temperature wind circulation

pattern in warmer climate under forced emission scenarios. Therefore, 20th century

control run (20C3M) and forced scenarios A2, B1 and A1B are considered using the

simulations of IPCC AR4 coupled climate models.

Finally, in Chapter 6, the results of the previous chapters (2 to 5) have been summarized,

and conclusion of the thesis is presented. This chapter also includes the scope to

incorporate new ideas and improvement in present work for future developments.


Introduction


Documents

Introduction - INFLIBNET Centreshodhganga.inflibnet.ac.in/bitstream/10603/6304/12/12...Introduction western half of the Ladakh in Jammu-Kashmir. Severe heat waves are also not so far