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Monsoons and Climate Change Presentation made at WCRP Workshop, Lille, France 16 June, 2010 K. Krishna Kumar Indian Institute of Tropical Meteorology, Pune (krishna@tropmet.res.in). - PowerPoint PPT Presentation
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Monsoons and Climate Change
Presentation made at WCRP Workshop, Lille, France16 June, 2010
K. Krishna KumarIndian Institute of Tropical Meteorology, Pune
(krishna@tropmet.res.in)
Motivation
Is Climate Change Impacting Agriculture and Food-grain
Production in water-limited tropical crop lands including monsoon dominated regions like India?
3
Over the last decade, 31 out of 41 countries that hold 90% of the water-limited croplands show a decline in annual average growth rate of food grain production.
Food grain: cereals+coarse grains+pulsesData from FAOSTAT
Change (%) in rate of food grain production in 1996-2006 relative
to 1966-1996
Milesi C, A Samanta, H Hashimoto, K Krishna Kumar, S Ganguly, PS Thenkabail,
AN. Srivastava, RR Nemani, RB Myneni
Remote Sensing, 2010
% change in vegetation greenness during 1996-2006 compared to 1982-1992
as calculated from GIMMS-G NDVI
45% of the water-limited tropical croplands show a decline in relative growth of integrated NDVI over
the last decade
NDVI = NIR – RED / NIR+RED
5
Change (%) in rate of
food grain production
in 1996-2006 relative
to 1966-1996
Change (%) in trend
of peak annual
precipitation in 1996-
2006 relative to 1966-
1996
Spatio-temporal deceleration in food grain production in India
Wet season Dry season
Kharif
Mean annual T =27.1 °C
Rabi
Mean annual T =22.5 °C
Impact of Growing Season Rainfall and Impact of Growing Season Rainfall and Night time Temps on Rice Yields in IndiaNight time Temps on Rice Yields in India
Tmin (°C)
SRES A2
Baseline
Krishna Kumar et al, 2010 Krishna Kumar et al, 2010
Goswami et al., Dec., 2006
Changes in the Frequency Distribution of Extremes during 1951-1970 and 1980-2000
Error doubling Time for the last two quarters (1953-1978 and 1979-2004)
(18N-27N, 73E -85E)
Change in predictability of Indian summer monsoon on weather scales
Neena Mani et al, Geophys.Res. Letts (2009)
First Lyapunov exponent First Lyapunov exponent
Multi Model Ensemble vs. Best sub-set
Metrics for selection of best sub-set of models
•Mean Monsoon features•ENSO and its teleconnections•Intra-seasonal variability
Performance of GFDL as an examplePerformance of GFDL as an example
Obs
GFDL2.1
GFDL2.0
Mean Monsoon rainfall Monsoon-ENSO Tropical waves/MJO
Some Aspects of Asian Summer Monsoon Rainfall and Its ENSO Some Aspects of Asian Summer Monsoon Rainfall and Its ENSO Teleconnections as simulated by AR4 Models in 20Teleconnections as simulated by AR4 Models in 20 thth Century Century
Lin et al. 2006, J. Lin et al. 2006, J. ClimateClimate
Mean Monsoon RainfallMean Monsoon Rainfall Monsoon and ENSOMonsoon and ENSO Tropical Waves; MJOsTropical Waves; MJOs
Expected Future Changes in Rainfall and Temperature over India under IPCC SRES A1B GHG Scenarios
Krishna Kumar et al, 2010
Future (A1b-20C) Global Rainfall/SST
Precipitation
SSTa
Column integrated Moisture
Monsoon Circulation Strength
Krishna Kumar et al, 2010
Other Expected Changes in Monsoon Features
Annual Cycle
Length ofSeason
Monsoon &ENSO
MonsoonVariability
Krishna Kumar et al, 2010
Dynamical Downscaling at IITM(Resolution: 50km)
Evaluation experiment using LBCs derived from ERA-15 (1979-93)
LBCs from Hadley Centre Models
• Baseline (1961-90) – 3 members• A2 scenario (2071-2100) -3 members• B2 scenario (2071-2100)• 3 Members of QUMP (1961-2100) – A1b
LLBCs from ECHAMBaseline 1961-1990; A2 scenario :1991-2100; B2 scenario : 1991-2100
PRECIS
PRECIS captures important regional
information on summer monsoon
rainfall missing in its parent GCM simulations.
HadCM3HadCM3 PRECISPRECIS
Possible Climate Change impacts are examined in the:
• Extremes in rainfall and temperature
• Onset and advance of Monsoon
• Active/break cycles• Intensity and frequency
of Monsoon Depressions
Projections of Regional Tmax and Daily Rainfall ChangesProjections of Regional Tmax and Daily Rainfall Changes
Highest dailyHighest dailyTmax (C) inTmax (C) in
The BaselineThe BaselinePeriodPeriod
Expected Expected changechangein Tmax in in Tmax in FutureFutureunder A2under A2
Expected Expected changechangein Rainfallin RainfallIntensity inIntensity ina rainy daya rainy dayin futurein future
ExpectedExpectedchangechange
in No. ofin No. ofRainy DaysRainy Days
In futureIn futureunder A2under A2
Krishna Kumar et al, 2010Krishna Kumar et al, 2010
Plans under CORDEX at IITMRun 3 RCMs (PRECIS, WRF and RegCM3) using LBC from at least 5 CMIP5 models
To accomplish the above taskit will take 1000 days of computer time with 64 processors and300TB of storage for each RCP
New HPC System at IITM • IBM P6 with 117 nodes and 3744
cores (4.7GHz) with a peak performance of 70.2TF
• 2 Peta bytes of Storage with a 3 Tier Architecture
West Asia
Issues on which a Scientific Consensus has not yet been arrived
• On the future projected strength of monsoon On the future projected strength of monsoon circulation and the quantum of rainfallcirculation and the quantum of rainfall
• Projected changes of sub-seasonal monsoon Projected changes of sub-seasonal monsoon behavior (eg. Onset, ISOs, Monsoon behavior (eg. Onset, ISOs, Monsoon Depressions, Extremes etc.) – Partly Limited by Depressions, Extremes etc.) – Partly Limited by Resolution of CMIP3 and limited RCM runsResolution of CMIP3 and limited RCM runs
• The response of ENSO to Global WarmingThe response of ENSO to Global Warming• The future strength of ENSO-Monsoon linkThe future strength of ENSO-Monsoon link
A lot more needs to be done…
• In improving the current generation of global and regional climate models in their ability to simulate the regional features of climate such as monsoon rainfall etc.
• In quantifying the uncertainties of projected climate and related impacts
• In enhancing the interaction between groups that are generating climate inputs and those using them for impact/adaptation assessments
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