【摘要】 本文利用PSU/NCAR的MM5数值预报模式及其伴随模式,以我国1999年6月23日~6月24日的一次梅雨锋暴雨过程为个例,作了两组试验:控制试验和同化试验,并对两组试验的降水预报效果以及初始场进行对比分析,结果表明:四维变分资料同化方法可以将各种不同类型、不同时次的观测资料同化到模式中,将这些资料中有用的中尺度信息引入到模式初始场,有效改善初始场,从而提高暴雨预报水平。更多还原

【Abstract】 In the paper,using a nonhydrostatic version of the Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model(MM5) and its adjoint model,two sets of experiments,control experiment and assimilation experiment,for the Mei-Yu front rainstorm of 23～24 June 1999 were performed.The effects of rainstorm forecast and the initial fields of different experiments were compared.It is showed that,integrating all kinds of different type and different time data into numerical model,Four-Dimensional Variational(4DVAR) Data Assimilation method can produce an optional initial field and improve greatly the Mei-Yu front rainstorm forecast.更多还原