Effect of climatic variabulity on Indian summer monsoon rainfall

Effect of climatic variability on Indian summer monsoon rainfall

Department of AgronomyAgricultural College, Bapatla

Credit seminar on

By Medida Sunil Kumar BAD-14-06

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Contents of presentation

Introduction on monsoon & Indian summer monsoon

Climatic variability & factors affecting variability

Effect of climatic variability on Indian summer monsoon

Future projections of Indian summer monsoon variability

Conclusion

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Introduction Word “monsoon” is derived from the Arabic word for season.

Monsoon is defined as seasonally reversing wind system

accompanied by seasonal changes in atmospheric circulation

and precipitation.

Indian summer monsoon is a branch of Asiatic monsoon.

Primary theories behind the cause of monsoon is the

differential heating of ocean and land (Halley, 1686) and

shifts in inter tropical conversion zone.

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Fig-1:Thermal concept of the origin of monsoon by Halley (1686)

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Fig-3: Global surface & upper air circulation

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Fig-2: Surface global circulations of air

Fig-4: Origin of monsoon by modified Flohn’s (1951) concept

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Fig-5: Propagation of south east trade winds as south west trade winds after crossing equator

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Climate of Earth

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1. Earliest Atmosphere:

Primarily H2, water vapor, CH4 and NH4 like Jupiter and Saturn.

2. Second Atmosphere:

Consisting largely of N2, CO2 and inert gases, was produced by volcanism

Initial period Sun’s out put was 30% lower solar radiance associated one cold glacial

phase about 2.4 billion years ago

Late Archaean eon O2 containing atmosphere began to develop, apparently produced

by photosynthesizing cyanobacteria

3. Third Atmosphere:

Movement of plate tectonics and volcanism released CO2

Free oxygen did not exist in the atmosphere until about 2.4 billion years ago

The amount of oxygen in the atmosphere has fluctuated over the last 600 million years,

significantly higher than today's 21%.

Natural green house effect

Evolution of earth’s atmosphere

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Causes & consequences of climate change

Natural Causes

Volcanoes

Solar Output

Earth's Orbit around the Sun

Human Induced Causes Fossil Fuels

Industrial Revolution

Change in Land use

Increase in green house gases

Global warming

Climate variabulity & change 10

Effect of climatic variability on Indian summer monsoon

Inter-annual monsoon variability

Intra-seasonal monsoon variability

Decadal monsoon variability

Active and break spells

Cyclonic disturbances

El Nino southern oscillation (ENSO)

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I. Inter-annual varIabIlIty

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Chapter-2, Indian Monsoon variability, Monsoon monograph, Tyagi et al., (edit) Vol-2, Chapter-2, Pp 35-77, IMD.

Fig-6: Inter-annual variability of all India June rainfallPattanaik, 2012

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Excess+20= 21yExcess+40=3y

Deficit -20=22yDeficit-40=4y

Normal=164.7 mm (18.5%)

Fig-7: Change in Indian summer monsoon rainfall of June month in mm during 100 year for 36 meteorological sub-divisions

Guhathakurta & Rajeevan, 2007

IMD, Pune14

Fig-8: Inter-annual variability of all India July rainfall

Pattanaik, 2012

Chapter-2, Indian Monsoon variability, Monsoon monograph, Tyagi et al., (edit) Vol-2, Chapter-2, Pp 35-77, IMD.15

Excess+20 = 6 y Deficit -20 = 11 yDeficit-40 = 3y

Normal = 293.7 mm (33 %)

Fig-9: Change in Indian summer monsoon rainfall of July month in mm during 100 year for 36 meteorological sub-divisions

IMD, Pune


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Fig-10: Inter-annual variability of All India August rainfall

Pattanaik, 2012


Excess+20 = 13 y Deficit -20 = 10 y

Normal = 262.5 mm (29.5 %)

Fig-11: Change in Indian summer monsoon rainfall of August month in mm during 100 year for 36 meteorological sub-divisions


IMD, Pune18

Fig-12: Inter-annual variability of All India September rainfallPattanaik, 2012


Excess+30 = 11 y Deficit -30 = 12 y

Normal = 169.1 mm (19 %)

Fig-13: Change in Indian summer monsoon rainfall of September month in mm during 100 year for 36 meteorological sub-divisions


IMD, Pune20

Fig-14:Inter-annual variability of all India summer monsoon rainfall (AISMR) during the period from 1875 to 2010

Pattanaik, 2012


Flood years= Mean rainfall 1041mmFlood years= 19

Drought years= Mean rainfall 739 mmDrought years= 24

Fig-15: Change in Indian summer monsoon rainfall in mm during 100 year for 36 meteorological subdivisions. Guhathakurta and Rajeevan, 2007

IMD, Pune22

Fig-16: Mean coefficient of variability (%) of all India summer monsoon rainfall in cm from 1951-2003

Pattanaik, 2012


Fig-17: Average frequency (intensity) of occurrence of rainfall events during summer monsoon season (951 to 2005) along with the linear trend line

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Pattanaik and Rajeevan, 2010

Meteorological applications. 17: 88–104

Table-1: Mean percentage of rainfall amount under different categories of rainfall events (1951-2005)

25Meteorological Applications. 17: 88–104


Fig-18:Inter-annual variability of Indian summer monsoon rainfall (mm) in different district of erstwhile Andhra Pradesh (1971-2009)

El Niño Effect on Climatic Variability and Crop Production: A Case Study for Andhra Pradesh; Res. Bull. No. 2/2011, CRIDA

Rao et al., 2011

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Fig-19: Climatologically daily rainfall anomalies averaged over the all India, central and peninsular India during summer monsoon rainfall period (1966–2010).

J. Earth System Science,123 (5),1129–1145

Prasanna, 2014

II. Intra-annual varIabIlIty

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Fig-20: Daily mean (mm) and daily coefficient of variability (%) of all India monsoon rainfall (1951-2000). Pattanaik, 2012


III. DecaDal varIabIlIty

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Fig-22:-Decadal composite anomalies of AISMR based on IMD observed rainfall during last 11 decades from 1901-2010. Pattanaik, 2012


Fig-23: Decadal composite anomalies of AISMR based on IMD observed rainfall during last 11 decades from 1901-2010

Pattanaik, 2012


IV. Active & break spells

Periods in which the normalized anomaly of the rainfall over

the monsoon zone exceeds 1 or is less than -1.0 respectively,

provided the criterion is satisfied for at least three consecutive

days.

Break spell of more than 10 days in monsoon period is due to

synoptic convective systems and Madden Julian oscillation.

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Fig-24: Average percentage of frequency of no rain days during June to September from 1951 to 2005

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Meteorological Applications. 17: 88–104

Table-2:Frequency distribution of the duration of break spells in per cent (1951–2007)

DurationRajeenvan et al

1950-2007

3-4 405-6 287-8 199-10 311-12 413-14 3>15 3

Rajeevan et al., 2010

35J. Earth System Science.119 (3), 229–247

Table-3:Decadal variabulity of active & break spells (1951-2007)

Period No of Break spell No of Active spell

1951-1960 6 151961-1970 12 201971-1980 12 201981-1990 13 171991-2000 15 172001-2007 12 12

Rajeevan et al., 2010

J. Earth System Science.119 (3), 229–24736

Fig-25: Mean rainfall anomaly during the break spells(1951-2004)Rajeevan et al., 2010


Fig-26:Composite of rainfall anomaly (mm/day)for active & break spells (1951-2004) Rajeevan et al., 2010

Active SpellBreak spell


Fig-27: Madden Julian Oscillation spatial structure and evolution: a schematic illustrating the large-scale nature and eastward shifting over time. The cloud (sun) icons represent the enhanced (suppressed) phase and the blue arrows indicate the eastward movement.

Courtesy of NOAA Climate Prediction Center39

Fig-28: Composite rainfall anomaly (mm) in respect of 8 strong phases and the weak category of MJO derived using data for the period 1974-2008

Pai et al., 2009

National Climate Centre, Research Report No: 4/200940

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Fig-29: Effect of Indian ocean dipole summer monsoon rainfall

V. Cyclonic Disturbances

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Fig-30:The frequency of monsoon depressions in each monsoon season of 1891 to 2007 Joseph, 2012

Chapter-1, Synoptic systems during monsoon season, Monsoon monograph, Tyagi et al (Edt.),vol-2, 1-34 43

Global teleconnections of Indian monsoon

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S. No Parameter Period of data

Correlation coefficient withAISMR (1971-2000)

1 Arabian sea surface temperature January + February 0.55

2 Eurasian snow cover December -0.46

3 North West Europe temperature January 0.45

4Nino-3 SST anomaly (Previous year)

July to September 0.42

5 South Indian ocean SST index March 0.476 East Asian pressure February + March 0.61

7 50hPa Wind pattern January + February -0.508 Europe pressure gradient January 0.42

9South Indian Ocean zonal wind at 850 hPa

June -0.45

10 Nino 3.4 SST tendency AMJ-JFM -0.46

Table-4: Details of parameters used in new long range forecasting

April-16 45

S. No Predictor Used for forecast

Correlation coefficient with

AISMR(1971-2000)

1NW Europe land surface air temperature April -0.51

2 Equatorial pacific warm water volume April 0.43

3 North Atlantic sea surface temperature April & June 0.36

4Equatorial SE Indian ocean sea surface temperature April & June 0.59

5 East Asia mean sea level pressure April & June -0.31

6Central Pacific Sea surface temperature tendency (Mar+Apr+May) – (Dec+Jan+Feb)

June -0.49

7 North Atlantic mean sea level pressure June -0.46

8North Central Pacific wind at 1.5 km above sea level June -0.44

Table-5:Details of eight parameters used in new forecasting model

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VI. El Niño southern oscillation

• Defined as oscillation / fluctuations in air pressure

between the tropical eastern and the western Pacific

Ocean waters.

• Oceanic component called El Niño or La Niña and the

atmospheric component is Southern Oscillation.

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Fig-31: Normal conditions over Pacific ocean

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TSW=+0.5oCThermocline= 3-6oC

Fig-32: Events of El Niño and La Niño

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Fig-33: El Niño and La Niño events

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Fig-34: Oceanic Nino regions

Courtesy by www.intechopen.com

Fig-34:

Table-6:El Niño /La Niño association with all-India summer monsoon rainfall anomalies during 1880-2008.

Parameter

Indian Summer Monsoon RainfallDeficit < - 1.0

Below Normal

- 0.5 to 0.5

Near Normal-0.5 to 0.5

Above Normal

0.5 to 1.0

Excess> 1.0

Total

El Nino(Nino -3> 1.0) 7 5 5 0 1 18

Normal 14 13 39 14 6 86La Nino(Nino -3<-1.0)

0 0 7 7 10 24

Total 21 18 51 21 17 128

Gadgil and Francis, 2012

Chapter-4, Oceans and Indian monsoon, Monsoon monograph, Tyagi et al., (edit) Vol-2, Chapter-2, Pp 129-188, IMD.52

Fig-35: All-India summer monsoon rainfall (1871-2001)(Based on IITM homogeneous monthly rainfall data set)

Flood years: Mean 1041mm Drought years: Mean 739 mm

Courtesy by http://www.tropmet.res.in/~icrp/icrpv11/icrp6.html

VII. Rainfall extremes

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Fig-36:Average percentage of frequency of rainfall more than 124.4 mm/day during the monsoon season from 1951 to 2005.

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June July

August September


Meteorological Applications. 17: 88–104

Fig-37: Number of heavy rainfall events from 1950 to 2010

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Future projections

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Emissions Scenarios of IPCC• A1:- World of very rapid economic growth, low population growth, and the rapid

introduction of new and more efficient technologies with a substantial reduction in regional differences in per capita income. The A1 scenario family develops into four groups based technological change in the energy system.

• A2:- Heterogeneous world. The underlying theme is self-reliance and preservation of local identities and high population growth with regional Economic development

• B1:- Storyline and scenario family describes a convergent world with the same low population growth as in the A1 storyline, but emphasis is on global solutions to economic, social, and environmental sustainability, including improved equity, but without additional climate initiatives.

• B2:- World in which the emphasis is on local solutions to economic, social, and environmental sustainability with moderate population growth, intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 storylines. While the scenario is also oriented toward environmental protection and social equity, it focuses on local and regional levels.

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Fig-38:Projections of future climate of India under four Special Report on emission scenarios of IPCC emission scenario

Murari Lal et al., 2001

Current Science, 81 (9&10), 1196-1207

A1= Rapid economic growth GlobalisationB1=Regionally oriented economic developmentA2=Global environmental sustainability RegionalisationB2= Local environmental sustainability 59

Fig-39: Projected future changes in mean monsoon precipitation (%) with respect to baseline period of 1961–1990.

Krishna Kumar et al., 2012

Current Science, 101(3), 312-32660

Fig-40: Projected future changes in the number of rainy days with respect to the baseline (1961–1990).


Current Science, 101 (3), 312-32661

Fig-41:Projected changes in the intensity of rainfall on a rainy day (mm/day) with respect to the baseline (1961–1990)

Current Science, 101 (3), 312-326


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Conclusions• Climate of the earth changing form its origin.

• Human induced forces accelerated much more than natural forces resulting global warming over a shorter period on earth’s time scale.

• Annual variabulity was influenced by global teleconnections of Indian summer monsoon.

• Intra-annual variabulity was observed highest in the months of June & September.

• Trend in significant increase in intensity of rainfall was observed with regional variations.

• Projections of future mean summer monsoon precipitation will be increased along with rainfall intensity

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thank you

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Education

Effect of climatic variabulity on Indian summer monsoon rainfall