Effect of climatic variabulity on Indian summer monsoon rainfall

Credit seminar on
Effect of climatic variability on Indian
summer monsoon rainfall
By
Medida Sunil Kumar
BAD-14-06
Department of Agronomy
Agricultural College, Bapatla
1

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
2

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.
3

Fig-1:Thermal concept of the origin of monsoon by Halley (1686)
4

Fig-3: Global surface & upper air circulation
Fig-2: Surface global circulations of air
5

Fig-4: Origin of monsoon by modified Flohn’s (1951) concept
6

Fig-5: Propagation of south east trade winds as south west
trade winds after crossing equator
7

Evolution of earth’s atmosphere
1. Earliest Atmosphere:
 Primarily H, water vapor, CHand NHlike Jupiter and Saturn.
24 4 2. Second Atmosphere:
Consisting largely of N, COand inert gases, was produced by volcanism
22 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 Ocontaining atmosphere began to develop, apparently produced
2 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
9

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)
11

I. Inter-annual
varIabIlIty
12

Fig-6: Inter-annual variability of all India June rainfall
Pattanaik, 2012
13
Excess+20= 21y
Excess+40=3y
Deficit -20=22y
Deficit-40=4y
Normal=164.7 mm (18.5%)
Chapter-2, Indian Monsoon variability, Monsoon monograph, Tyagi et al., (edit) Vol-2, Chapter-2, Pp 35-77, IMD.

Fig-7: Change in Indian summer monsoon rainfall of June month in mm
during 100 year for 36 meteorological sub-divisions
Guhathakurta & Rajeevan, 2007
14
IMD, Pune

Fig-8: Inter-annual variability of all India July rainfall
Pattanaik, 2012
15
Excess+20 = 6 y Deficit -20 = 11 y
Deficit-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
16
IMD, Pune

Fig-10: Inter-annual variability of All India August rainfall
Pattanaik, 2012
17
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
18
IMD, Pune

Fig-12: Inter-annual variability of All India September rainfall
Pattanaik, 2012
19
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
20
IMD, Pune

Fig-14:Inter-annual variability of all India summer monsoon
rainfall (AISMR) during the period from 1875 to 2010
Pattanaik, 2012
21
Flood years= Mean rainfall 1041mm
Flood years= 19
Drought years= Mean rainfall 739 mm
Drought years= 24

Fig-15: Change in Indian summer monsoon rainfall in mm during
100 year for 36 meteorological subdivisions. Guhathakurta and Rajeevan, 2007
22
IMD, Pune

Fig-16: Mean coefficient of variability (%) of all India
summer monsoon rainfall in cm from 1951-2003
Pattanaik, 2012
23

Fig-17: Average frequency (intensity) of occurrence of rainfall events during
summer monsoon season (951 to 2005) along with the linear trend line
Pattanaik and Rajeevan, 2010
24
Meteorological applications. 17: 88–104

Table-1: Mean percentage of rainfall amount under
different categories of rainfall events (1951-2005)
25
Meteorological Applications. 17: 88–104

Fig-18:Inter-annual variability of Indian summer monsoon rainfall (mm)
in different district of erstwhile Andhra Pradesh (1971-2009)
Rao et al., 2011
El Niño Effect on Climatic Variability and Crop Production: A Case Study for Andhra Pradesh; Res. Bull.
No. 2/2011, CRIDA
26

Fig-19: Climatologically daily rainfall anomalies averaged over the all India, central and
peninsular India during summer monsoon rainfall period (1966–2010).
Prasanna, 2014
27
J. Earth System Science,123 (5),1129–1145

II. Intra-annual varIabIlIty
28

Fig-20: Daily mean (mm) and daily coefficient of variability
(%) of all India monsoon rainfall (1951-2000). Pattanaik, 2012
29

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.
33

Fig-24: Average percentage of frequency of no rain days during June to
September from 1951 to 2005
34

Table-2:Frequency distribution of the duration of break
spells in per cent (1951–2007)
Duration
Rajeenvan et al
1950-2007
3-4 40
5-6 28
7-8 19
9-10 3
11-12 4
13-14 3
>15 3
Rajeevan et al., 2010
35 J. 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 15
1961-1970 12 20
1971-1980 12 20
1981-1990 13 17
1991-2000 15 17
2001-2007 12 12
36
J. Earth System Science.119 (3), 229–247

Fig-25: Mean rainfall anomaly during the break spells(1951-2004)
37

Fig-26:Composite of rainfall anomaly (mm/day)for
active & break spells (1951-2004) Rajeevan et al., 2010
Break spell Active Spell
38

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.
39
Courtesy of NOAA Climate Prediction Center

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
40
National Climate Centre, Research Report No: 4/2009

Fig-29: Effect of Indian ocean dipole summer monsoon rainfall
41

Fig-30:The frequency of monsoon depressions in each
monsoon season of 1891 to 2007 Joseph, 2012
43
Chapter-1, Synoptic systems during monsoon season, Monsoon monograph, Tyagi et al (Edt.),vol-2, 1-34

Global teleconnections of Indian monsoon
44

Table-4: Details of parameters used in new long range
forecasting
S. No Parameter Period of data
Correlation
coefficient with
AISMR (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
4 Nino-3 SST anomaly (Previous
year) July to September 0.42
5 South Indian ocean SST index March 0.47
6 East Asian pressure February + March 0.61
7 50hPa Wind pattern January + February -0.50
8 Europe pressure gradient January 0.42
9 South Indian Ocean zonal wind
at 850 hPa June -0.45
10 Nino 3.4 SST tendency AMJ-JFM -0.46
April-16 45

Table-5:Details of eight parameters used in new
forecasting model
S. No Predictor Used for forecast
Correlation
coefficient with
AISMR
(1971-2000)
1 NW 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
4 Equatorial SE Indian ocean sea surface
temperature April & June 0.59
5 East Asia mean sea level pressure April & June -0.31
6
Central Pacific Sea surface temperature
tendency (Mar+Apr+May) –
(Dec+Jan+Feb)
June -0.49
7 North Atlantic mean sea level pressure June -0.46
8 North Central Pacific wind at 1.5 km
above sea level June -0.44
46

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.
47

Fig-31: Normal conditions over Pacific ocean
48

Fig-32: Events of El Niño and La Niño
TSW=+0.5oC
Thermocline= 3-6oC
49

Fig-33: El Niño and La Niño events
50

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
Gadgil and Francis, 2012
Indian Summer Monsoon Rainfall
Deficit
< - 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 86
La Nino
(Nino -3<-
0 0 7 7 10 24
1.0)
Total 21 18 51 21 17 128
52
Chapter-4, Oceans and Indian monsoon, Monsoon monograph, Tyagi et al., (edit) Vol-2, Chapter-2, Pp 129-188, IMD.

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

Fig-36:Average percentage of frequency of rainfall more than 124.4
mm/day during the monsoon season from 1951 to 2005.
55
June July
August September

Fig-37: Number of heavy rainfall events from 1950 to 2010
56

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.
58

Fig-38:Projections of future climate of India under four Special
Report on emission scenarios of IPCC emission scenario
Murari Lal et al., 2001
A1= Rapid economic growth Globalisation
B1=Regionally oriented economic development
A2=Global environmental sustainability Regionalisation
B2= Local environmental sustainability 59
Current Science, 81 (9&10), 1196-1207

Fig-39: Projected future changes in mean monsoon precipitation (%) with
respect to baseline period of 1961–1990.
Krishna Kumar et al., 2012
60
Current Science, 101(3), 312-326

Fig-40: Projected future changes in the number of rainy days with respect
to the baseline (1961–1990).
61
Current Science, 101 (3), 312-326

Fig-41:Projected changes in the intensity of rainfall on a rainy day
(mm/day) with respect to the baseline (1961–1990)
62
Current Science, 101 (3), 312-326

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
63

Effect of climatic variabulity on Indian summer monsoon rainfall

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