1. CENSAM Annual Workshop, 29 June 2015 Regional Climate Analyses over Southeast Asia Dr. Sri Raghavan Mr.Liu Jiandong, Dr.Nguyen Ngoc Son, Dr.Vu Minh Tue, Dr.Liong Shie-Yui Dr.Chien Wang CENSAM, SMART

2. Mean Annual Rainfall 1986-2005 (mm/day) TRMM 1998-2010 CRU UDEL APHRODITE GPCC CPC

3. Precipitation Annual Cycle 1986-2005 HANOI BANGKOK KUALA LUMPUR MANILA PHNOM PENHSINGAPORE VIENTIENNEYANGON

4. CMIP5 Global Climate Models NoGCMAtmospheric Resolution Country 1BCC CSM1.1 2.8° × 2.8°China 2NCAR CCSM4 0.9° × 1.3°USA 3CNRM CM5 1.4° × 1.4°France 4CSIRO MK3.6 1.9° × 1.9°Australia 5UKMO HadGEM2 1.3° × 1.9°UK 6IPSL CM5A 1.9° × 3.8°France 7JAMSTEC MIROC5 1.4° × 1.4°Japan 8MPI ESM-MR 1.9° × 1.9°Germany 9MRI CGCM3 0.6° × 0.6°Japan 10NCAR CESM CAM5 0.9° × 1.3°USA

5. CNRM CSIRO MK 3.6 IPSL CM5 MRI-CGCM3 CRU Mean Annual Rainfall 1986-2005 (mm/day) CCSM4 CNRM CM5 MRI CGCM3 ENSEMBLE CRU

6. Mean Annual Rainfall 1986-2005 (mm/day) - Hovmoller TRMMBCC CSM CNRM CM5 HadGEM2 MPI ESM MR MRI CGCM3

8. Mean Annual Cycles 1986-2005 (mm/day) – SEAsian Cities BANGKOK HANOI YANGON KUALA LUMPUR MANILA VIENTIENNE

9. Seasonal average rainfall (land only), 1986-2005, mm/day, Southeast Asia (95E to 130E; 10S to 25N)

10. Seasonal average rainfall (land only), 1986-2005, mm/day, Southeast Asia (95E to 130E; 10S to 12N)

11. Interann Var. 1986-2005 (mm/day) TRMM CRU MRI CGCM3 IPSL CM5 BCC CSM CNRM CM5

12. EOF1

13. EOF2

14. FINAL WORDS… Objective is not to rank the best or worst Despite higher resolutions, the CMIP5 GCMs’ ability to reproduce regional representation of rainfall is rather poor Ensemble of GCMs – not bad, but depends on purpose of application EOFs suggest that the dominant features yet need to be improved Next stage will analyze synoptic circulation features A feedback to the GCM community on such regional representation may not be inappropriate