1. On Climate Predictability of the Summer Monsoon Rainfall Bin Wang Department of Meteorology and IPRC University of Hawaii Acknowledging contribution from Q. H. Ding, X. H. Fu, I.-S. Kang, J.-Y. Lee, K. Jin

2. MCZ: BOB-SCS-PS JJA precipitation, 850 hPa winds, 200hPa STR

3. Source of predictability for EASM Wang, Wu and Lau 2001 Why do we care about the rainfall in MCZ?

4. Assessment of 11 AGCMs ensemble simulations of summer monsoon rainfall Data: CLIVAR/ Monsoon panel Intercomparison project) (Kang et al. 2002) AMIP type design 10-member ensemble Focus on 1997 ElNino (Sept 1 1996- August 31 1998)

5. AGCMs climatology is poor in WNP heat source region ISM (5-30N, 65-105E) WNPSM (5-25N, 110-150E)

6. AAM and El Nino domain

7. Wang, Kang, Lee 2003, JC El Nino region A-AM region

9. MCZ Rest of A-AM

10. Prediction skill for JJA rainfall (2 years) 11-model ensemble mean

11. Prediction skill for JJA rainfall (21 years) 5-model ensemble mean

12. Why do Nearly All Atmospheric Models Fail to Simulate Seasonal Rainfall Anomalies in Summer Monsoon Convergence Zones? Bad model? Poor strategy?

13. Fig.3 Observed Rainfall-SST correlation (1979-2002) Rainfall Leads SST by 1-month SST leads Rainfall by 1-month Concurrent

14. Fig.4 Rainfall-SST correlation from Coupled model ) Simultatious Rainfall Leads SST by 1-month SST leads Rainfall by 1-month

15. Fig.5 Rainfall-SST correlation from AMIP-type run Concurrent Rainfall Leads SST by 1-month SST leads Rainfall by 1-month

16. Are MJO or boreal summer ISO reproducible in forced AGCM simulations (AMIP-type)? How important is the air-sea interaction in prediction of ISO? Predictability of the ISO

17. 1979

18. CMAP Rainfall Coupled Daily Forced Mean Forced

19. Phase Relationships between Rainfall and SST Arabian Sea Bay of Bengal

20. Kemball-Cook and Wang (2001)

21. Summary AGCM alone can not reproduce realistic seasonal rainfall anomalies in summer Monsoon Convergence Zone (MCZ). Caution should be taken when validating model or determining upper limit of predictability using AMIP approach. Two-tier approach may be inherently inadequate for monsoon rainfall anomalies. Atmospheric only model may loss significant amount of predictability on MJO. Coupled and forced ISO solutions are two distinguished solutions. Chaos can be induced by both IC and BC errors.

22. Thank You

23. Main Points Current AGCMs forced by SSTA have little skill in simulation and prediction of seasonal rainfall anomalies over summer Monsoon Convergence Zone (MCZ). Cautions must be taken when validating model or determining the upper limit of the predictability using AMIP approach. Two-tier approach may be inherently inadequate for monsoon rainfall anomalies. Atmospheric only model may loss significant amount of predictability of MJO.

24. Fig.2

25. Is ISO a noise or signal? Cadet 1986 Monsoon climate prediction must deal with ISO

26. Anomalous SST-Model precipitation Correlation OBS-Model correlation: sample size 22

27. Correlation coefficients: Local SST-Precipitation Anomalies In the MCZ region: sample size: 222 or 2220 OBS 11- COM POS. COLADNMGEOSGFDLIAPIITMMRINCARNCEPSNUSUNY JJA 97 -0.15 0.59 0.420.490.380.190.020.150.490.430.390.360.33 SON 97 -0.33 0.71 0.590.70.50.350.450.490.440.660.370.340.37 JJA 98 -0.45 0.56 0.190.770.240.520.590.440.50.510.57-0.120.38 TO- TAL -0.350.58 0.330.650.320.42 0.370.470.510.470.040.35

28. Anomalous SST-Model precipitation Correlation OBS-Model correlation: sample size 22

29. Prediction Skill of JJA Precipitation during 21 years (a) MME1(Model Composite) (d) NASA (b) SNU (e) NCEP (c) KMA (f) JMA Temporal Correlation with Observed Rainfall

30. Fig. 4. Same as in Fig. 2 except the results are obtained from MME (5-model) output for the period 1979-1999.

32.  Atmospheric Model: ECHAM4.6 T30 (3.75 o ).  Ocean Model: UH 2.5-layer Intermediate Model, 2 o x1 o  Coupling: daily, Full, No flux correction; Warm pool only Regional Coupled Model: ECHAM-UHIO

33. UH 2.5 layer Ocean Model (Wang, Li, Chang 1995, JPO; Fu and Wang 2001, JC)