关键词: 资料同化, 降水预报, “旋转加强”问题

Abstract: A series of forecast experiments on a heavy Mei-yu precipitation process in July 1991 are performed to reduce the spin-up error of the limited-area numerical weather prediction model by assimilating observation data in four dimensions. Two schemes of assimilation are designed to better initial states for the improvement of the model forecast in the early stage; one is Newtonian relaxation by nudging which is used for assimilating the observations of temperature and wind fields; the other is humidity-modifying scheme for assimilating precipitation observations. The results show: 1) the former is characterized by the initial state with large-scale weather situation and the initial field gains meso-scale information; 2) the latter develops low-pressure system and the initial field gains more and better mesoscale information; 3) As a result, the incorporation of two schemes improves the early 6h precipitation prediction. Newtonian relaxation by nudging is more important to the Mei-yu weather process by forming the large-scale environmental conditions.

Key words: data assimilation, precipitation prediction, spin-up problem