A comparison of full-field and anomaly initialization for seasonal prediction of Indian Ocean basin mode

Abstract

The full-field initialization (FI) and anomaly initialization (AI) are two currently existing initialization techniques for seasonal climate predictions. Knowledges on the skill dependence of seasonal predictions of Indian Ocean basin mode (IOBM) on these two initialization approaches are important but remains unknown. In this study, we try to fill in the knowledge gap by performing hindcasts with a near-term climate prediction system named IAP-DecPreS. We find that anomaly initialized hindcasts (Hindcast-A) show higher skill than full-field initialized hindcasts (Hindcast-F) in the predictions of IOBM. Initialized from November, both the types of hindcasts reasonably predict the Indian Ocean basin-wide warming during ENSO mature winter, but only the Hindcast-A successfully reproduces the persistence of the IOBM to the following summer. The differences in the hindcast skill arise in developing stage of the IOBM, during which the Hindcast-F underestimates the warming tendency in the southern tropical Indian Ocean (TIO). The discrepancy is associated with both ENSO remote forcing and local air-sea interaction processes. ENSOs predicted by Hindcast-F decay faster than those in the observations and the Hindcast-A, leading to an underestimation of ENSO forcing to the Indian Ocean. In addition, both the positive downward shortwave radiative flux and latent heat flux anomalies over the southern TIO are underestimated by the Hindcast-F due to the modulations of the model climatology. These results imply that the FI scheme is unable to maintain the inherent physical processes responsible for the IOBM formation in the coupled model, although it can improve model climatology in the Indian Ocean.