The Effects of Air-Sea Coupling on the MJO Forecasting Vary Event-by-Event during the DYNAMO/CINDY Period

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Wednesday, 7 January 2015: 5:15 PM
224A (Phoenix Convention Center - West and North Buildings)
Joshua Xiouhua Fu, Univ. of Hawaii, Honolulu, HI; and W. Wang, J. Y. Lee, B. Wang, K. Kikuchi, J. Xu, J. Li, and S. Weaver

Previous observational analysis and modeling studies indicate that air-sea coupling plays an essential role in improving MJO simulations and extending MJO forecasting skills. However, whether the SST-feedback plays an indispensable role for the existence of the MJO remains controversial, and the precise physical processes through which the SST-feedback may lead to better MJO simulations and forecasts remain elusive.

The DYNAMO/CINDY field campaign recently completed over Indian Ocean reveals a new perspective and provides better data to improve our understanding of the MJO. It is found that among the five MJO events occurred during the DYNAMO/CINDY field campaign, only two MJO events (Nov. and Mar. ones) have robust SST anomalies associated with them. For the other three MJO events (Oct., Dec., and Jan. ones), no coherent SST anomalies are observed. This observational scenario suggests that the roles of air-sea coupling on the MJO vary greatly from event to event.

To elucidate the varying roles of air-sea coupling on different MJO events, a suite of forecasting experiments was conducted with a particular focus on the Oct. and Nov. MJO events. Our numerical results confirm that the Oct. MJO is largely controlled by atmospheric internal dynamics, while the Nov. MJO is strongly coupled with underlying ocean. For the Nov. MJO event, the positive SST anomalies significantly improve MJO forecasting by enhancing the response of a Kelvin-Rossby-wave couplet, which prolongs the feedback between convection and large-scale circulations, and thus favors the development of stratiform rainfall, in turn, facilitating the production of eddy available potential energy and significantly amplifies the intensity of the model Nov. MJO.