Abstract
This study analyzes factors affecting the predictability of seasonal-mean precipitation over the tropical Indian Ocean. The analysis focuses on the contributions from the local sea surface temperature (SST) forcing in the Indian Ocean, the remote SST forcing related to ENSO in the tropical eastern Pacific, and the role of local air–sea coupling. To understand the impacts of the individual factors, the prediction skill over the tropical Indian Ocean for four model simulations, but with different treatments for the ocean, are compared. The seasonality in precipitation skill, the local precipitation–SST relationship, and prediction skill related to Indian Ocean dipole mode (IODM) are examined. It is found that the importance of the accuracy of local SST and the presence of local air–sea coupling in the Indian Ocean has a strong seasonal dependence. Accurate local SSTs are important during the boreal fall season, whereas the local air–sea coupling is important during the boreal spring. The precipitation skill over the Indian Ocean during boreal winter is primarily from ENSO. However, ENSO impacts are better realized with the inclusion of an interactive ocean. For all four seasons, the simulation without the interannual variations of local SST in the Indian Ocean shows the least precipitation skill and a much weaker seasonality. It is also found that, for the simulation where the global SSTs are relaxed to the observations and hence maintain some level of active air–sea coupling, the observed seasonal cycle of precipitation–SST relationship is reproduced reasonably well. In addition, the analysis also shows that simulations with accurate SST forcing display high precipitation skill during strong IODM events, indicating that IODM SST acts as a forcing for the atmospheric variability.
