CENSAM Annual Workshop, 29 June 2015

Regional Climate Analyses over Southeast AsiaDr. Sri Raghavan

Mr.Liu Jiandong,Dr.Nguyen Ngoc Son, Dr.Vu Minh Tue,

Dr.Liong Shie-Yui

Dr.Chien WangCENSAM, SMART

Mean Annual Rainfall 1986-2005 (mm/day)

TRMM1998-2010

CRU UDEL APHRODITE

GPCC CPC

Precipitation Annual Cycle 1986-2005HANOI BANGKOK KUALA LUMPUR

MANILA PHNOM PENH SINGAPORE

VIENTIENNE YANGON

CMIP5 Global Climate Models

No GCM AtmosphericResolution

Country

1 BCC CSM1.1 2.8° × 2.8° China

2 NCAR CCSM4 0.9° × 1.3° USA

3 CNRM CM5 1.4° × 1.4° France

4 CSIRO MK3.6 1.9° × 1.9° Australia

5 UKMOHadGEM2

1.3° × 1.9° UK

6 IPSL CM5A 1.9° × 3.8° France

7 JAMSTECMIROC5

1.4° × 1.4° Japan

8 MPI ESM-MR 1.9° × 1.9° Germany

9 MRI CGCM3 0.6° × 0.6° Japan

10 NCARCESM CAM5

0.9° × 1.3° USA

CNRM

CSIRO MK 3.6 IPSL CM5

MRI-CGCM3

CRU

Mean Annual Rainfall 1986-2005 (mm/day)

CCSM4 CNRM CM5

MRI CGCM3

ENSEMBLE CRU

Mean Annual Rainfall 1986-2005 (mm/day) - Hovmoller

TRMM BCC CSM CNRM CM5

HadGEM2 MPI ESM MR MRI CGCM3

Mean Annual Cycles 1986-2005 (mm/day) – SEAsian Cities

BANGKOK HANOI YANGON

KUALA LUMPUR

MANILA

VIENTIENNE

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

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

Interann Var. 1986-2005 (mm/day)

TRMM CRU MRI CGCM3

IPSL CM5 BCC CSM CNRM CM5

EOF1

EOF2

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