1. Dynamical Prediction of Indian Monsoon Rainfall and the Role of Indian Ocean K. Krishna Kumar CIRES Visiting Fellow, University of Colorado, Boulder Dynamical Prediction of Indian Monsoon Rainfall and the Role of Indian Ocean K. Krishna Kumar CIRES Visiting Fellow, University of Colorado, Boulder kkrishna@colorado.edu Martin P. Hoerling Climate Diagnostics Center, Boulder and Balaji Rajagopalan University of Colorado, Boulder

2. Current Practices of Dynamical Monsoon Rainfall Prediction  2-tiered approach wherein SSTs are predicted first using a coupled model and then the AGCMs are forced using these SST fields  Use persistent SSTs to run AGCMs  Dynamical Downscaling using Regional Climate Models taking lateral boundary values from AGCM Simulations

3. Skills of the Present Generation of AGCMs (Reproduced from the IRI Website)

4. We set out to examine the skills of monsoon rainfall in detail by involving long simulations made using observed SSTs with a suite of multi-model, multi-member ensemble runs.

5. Research Questions..?  How skillful are the AGCMs in simulating Monsoon Rainfall over the Indian region?  Is specifying SSTs a constraint on realistic monsoon simulations?  How sensitive are monsoon simulations to initial conditions?  What is the impact of coupling on Monsoon-ENSO relationships?  Are the ENSO related western Indian Ocean SSTs acting as negative feed-back on Monsoon-ENSO relations?

6. Details of AGCMs Used S.No.ModelResolution Ens. Size Run Length 1ECHAM42.8x2.8241950-2002 2ECHAM32.8x2.8101950-1999 3GFDL2.5x2.0101951-2002 4NASA2.8x2.891950-2002 5ECPC1.8x1.871950-2001 6MRF (NCEP)2.8x2.8131951-1994 7ARPEGE2.8x2.881948-1997 8CCM32.8x2.8121950-1999 9CAM22.8x2.8151950-2001

7. Climatology of Monsoon Rainfall

10. Monsoon-ENSO Relation in AGCM Simulations

11. PDFs of Correlations (1) Obs. Vs. Model ENS (2) PERPROG

12. Impact of Initial Conditions on Monsoon Simulations

13. Monsoon-ENSO Teleconnections: Coupled vs. Uncoupled Models

14. GOGA: Obs SSTs globally DTEPOGA: Obs SSTs in Deep Tropical East Pacific and Climatological SSTs elsewhere DTEPOGA_MLM: Same as DTEPOGA but a Mixed Layer Model used in the Indian Ocean

15. Progressive Improvement in Monsoon Rainfall Simulation Skills: Progressive Improvement in Monsoon Rainfall Simulation Skills: 1. Un-coupled AMIP 2.Un-coupled AMIP only in eastern tropical Pacific and Climatological SSTs elsewhere 3.AMIP in the Pacific and Mixed Layer Model in the Indian Ocean

17. Summary  The skills of current generation AGCMs in simulating monsoon rainfall in India even when forced with observed SSTs are very low.  However, there appears to be much higher predictive potential as evidenced by the large PERPROG skills.  No clear hint of higher skills either for models with better monsoon climatology or when multi-model-super ensembles are involved.  Specification of SSTs in the Indian Ocean appears to be the main reason for the low-skills.  An interactive ocean-atmosphere in the Indian Ocean (using even a simple mixed layer ocean model) produces more realistic monsoon simulations compared to specifying actual or climatological SSTs.  General belief that the ENSO related SSTs in the Indian Ocean (particularly the western Indian Ocean and the Arabian Sea) might act as a negative feedback on Monsoon-ENSO teleconnections appears to be wrong based on the above observations.Indian Ocean  In general the monsoon-ENSO links are much stronger in fully coupled models compared to the AGCMs forced with observed/predicted SSTs.  The 2-tiered approach currently being pursued in seasonal forecasting needs immediate revision to achieve higher forecast skills for the Indian region. We also believe, this might be true for some other countries located in the warm pool region in the west Pacific and the Indian Ocean.