Change (%) in rate of food grain production in 1996-2006 relative to 1966-1996

1. Monsoons and Climate ChangePresentation made at WCRP Workshop, Lille, France16 June, 2010K. Krishna KumarIndian Institute of Tropical Meteorology, Pune(krishna@tropmet.res.in)

2. MotivationIs Climate Change Impacting Agriculture and Food-grain Production in water-limited tropical crop lands including monsoon dominated regions like India?

3. Change (%) in rate of food grain production in 1996-2006 relative to 1966-1996 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+pulses Data from FAOSTAT Milesi C, A Samanta, H Hashimoto, K Krishna Kumar, S Ganguly, PS Thenkabail, AN. Srivastava, RR Nemani, RB Myneni Remote Sensing, 2010 3

4. 45% of the water-limited tropical croplands show a decline in relative growth of integrated NDVI over the last decade % change in vegetation greenness during 1996-2006 compared to 1982-1992 as calculated from GIMMS-G NDVI 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 5

6. Spatio-temporal deceleration in food grain production in India Dry season Wet season Kharif Mean annual T =27.1 °C Rabi Mean annual T =22.5 °C

7. Impact of Growing Season Rainfall and Night time Temps on Rice Yields in India Baseline SRES A2 Tmin (°C) Krishna Kumar et al, 2010

8. Observed Changes

11. Changes in the Frequency Distribution of Extremes during 1951-1970 and 1980-2000 Goswami et al., Dec., 2006

12. Change in predictability of Indian summer monsoon on weather scales Error doubling Time for the last two quarters (1953-1978 and 1979-2004) First Lyapunov exponent (18N-27N, 73E -85E) Neena Mani et al, Geophys.Res. Letts (2009)

13. Expected Future Changes Under Increased GHG ConditionsIPCC-AR4

14. 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

15. Performance of GFDL as an example Mean Monsoon rainfall Monsoon-ENSO Tropical waves/MJO Obs GFDL2.0 GFDL2.1

16. Some Aspects of Asian Summer Monsoon Rainfall and Its ENSO Teleconnections as simulated by AR4 Models in 20th Century Mean Monsoon Rainfall Monsoon and ENSO Tropical Waves; MJOs Lin et al. 2006, J. Climate

17. Observed and IPCC-AR4 Ensemble mean Monsoon Rainfall and Annual Surface Temperature

18. Expected Future Changes in Rainfall and Temperature over India under IPCC SRES A1B GHG Scenarios Krishna Kumar et al, 2010

19. Future (A1b-20C) Global Rainfall/SST Column integrated Moisture Precipitation SSTa Monsoon Circulation Strength Krishna Kumar et al, 2010

20. Other Expected Changes in Monsoon Features Length of Season Annual Cycle Monsoon Variability Monsoon & ENSO Krishna Kumar et al, 2010

21. Dynamical Downscaling at IITM(Resolution: 50km) PRECIS 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 ECHAM Baseline 1961-1990; A2 scenario :1991-2100; B2 scenario : 1991-2100

22. PRECIS captures important regional information on summer monsoon rainfall missing in its parent GCM simulations. HadCM3 PRECIS

23. 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

24. Projections of Regional Tmax and Daily Rainfall Changes Expected change in Tmax in Future under A2 Highest daily Tmax (C) in The Baseline Period Expected change in No. of Rainy Days In future under A2 Expected change in Rainfall Intensity in a rainy day in future Krishna Kumar et al, 2010

25. Impacts of Climate Change on Monsoon Depression Tracks and Intensity

26. Biases and problems in RCM simulationsStatistical Downscaling Coldest night temperature Frost days

27. Plans under CORDEX at IITM Run 3 RCMs (PRECIS, WRF and RegCM3) using LBC from at least 5 CMIP5 models West Asia 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 To accomplish the above task it will take 1000 days of computer time with 64 processors and 300TB of storage for each RCP

28. Issues on which a Scientific Consensus has not yet been arrived On the future projected strength of monsoon circulation and the quantum of rainfall Projected changes of sub-seasonal monsoon behavior (eg. Onset, ISOs, Monsoon Depressions, Extremes etc.) – Partly Limited by Resolution of CMIP3 and limited RCM runs The response of ENSO to Global Warming The future strength of ENSO-Monsoon link

29. 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

30. Thank you!