The impact of GMS (Geostationary Meteorological Satellite) data inthe GDAPS (Global Data Assimilation and Prediction System)

摘要

Due to the extensive calculations, running a global model requiresa high performance computer. The global model and analysis system,called GDAPS, has been set up in a Cray C9O environment. The five-dayglobal forecast was made available twice a day. In order to improve theforecast performance, the assimilation with satellite cloud informationis investigated. Since moisture data over the ocean is very sparse, manymeteorologists have attempted to retrieve the moisture profile fromother sources, such as satellite data, to supplement the sparsity of themoisture field. Using the supplementary data, they improved the NWPmodel forecast, especially the forecast of rainfall intensity. The KoreaMeteorological Administration (KMA) have tried to supplement themeagerness of the moisture field over the ocean following the methoddeveloped by Baba (1987), which uses the GMS retrieved data assupplementary moisture data. KMA have used the method since May 1, 1996with the help of the Satellite Division. The authors investigate theimpact of GMS retrieved data on GDAPS