Rethinking Indian monsoon rainfall prediction in the context of the recent global warming
Tuesday, June 16, 2015: 11:00 AM
Bin Wang, University of Hawaii at Manoa, Department of Meteorology, and International Pacific Research Center, Honolulu, HI, United States; NUIST Nanjing University of Information Science and Technology, Earth System Modeling Center, Nanjing, China
Abstract:
Prediction of Indian summer monsoon rainfall (ISMR) is at the heart of the monsoon prediction. Despite enormous progress made in predicting ISMR since 1886, the operational forecasts during recent decades (1989-2012) have little skill. Here we show, with both dynamical and physical-empirical (P-E) models, that the recent failure is largely due to models’ inability to capture new predictability sources emerging during the recent global warming. The P-E model that captures three new predictors foreshadowing the development of the central-Pacific El Nino-Southern Oscillation (CP-ENSO), the strengthening of the North and South Pacific Highs and the Asian Low, can produce an independent forecast correlation skill of 0.51 for 1989-2012 and a 92-y retrospective forecast skill of 0.64 for 1921-2012. The low skills of the dynamical models in the recent period are attributed to deficiencies in capturing developing CP-ENSO and anomalous Asian Low. The results reveal a considerable gap between ISMR prediction skill and predictability.
