85th AMS Annual Meeting

Wednesday, 12 January 2005
Global SST prediction system with a multi-model ensemble
Jong-Seong Kug, KORDI, Ansan, South Korea; and I. S. Kang and J. Y. Lee
Recently, there has begun to emerge a need for global sea surface temperature forecasts for initialing boundary conditions of atmospheric GCMs in long-range forecasting as a two-tier system, In addition, climate variabilities of many local areas are significantly affected by the regional ocean SST rather than the tropical Pacific SST. In this study, Global SST prediction system was developed at Climate Environment System Research Center (CES). The Global SST predictions are made by a multi-model ensemble process. In order to get an ensemble SST prediction, four prediction models were utilized. They consist of one dynamical model, two statistical models, and persistence. The optimal ensemble procedure is introduced, and its forecast skill is examined

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