Seasonal climate predictability with Tier-one and Tier-two prediction systems

In this study seasonal predictability of Tier-one and Tier-two predictions are evaluated and compared. Through the comparison of these two predictions, it is demonstrated that the air–sea coupled process is an important factor not only for climatological simulation but also for seasonal predictability. In particular, the air–sea coupling plays a crucial role over the warm pool region, as the atmosphere tends to lead the ocean in anomalous variability. In this region, the Tier-one prediction has better climatology compared to the Tier-two prediction despite the presence of a climatological SST bias. Furthermore, the Tier-one has a relatively higher seasonal predictive skill than that of the Tier-two although its SST prediction skill is relatively poor. It is suggested that the air–sea coupled process plays a role to reduce both the climatological and anomalous biases in the uncoupled AGCM by means of the negative feedback of the SST-heat flux-precipitation loop. Using the CliPAS and DEMETER seasonal prediction data, the robustness of these results are demonstrated in the multi-model frame works. This paper is a contribution to the AMIP-CMIP Diagnostic Sub-project on General Circulation Model Simulation of the East Asian Climate, coordinated by W.-C. Wang.

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In-Sik KangEmail: