多普勒雷达资料在3D.ppt

24h accumulate rainfall from 20BST,20July1998 to 20BST,21July 1998 Only by conventional observation net and traditional initialization procedure, it is very difficult to get the accurate initial field needed in the meso-scale model, especially the meso-scale systems vital to torrential rain generation. One way improving the initial field of the meso-scale model is assimilating non-traditional data into meso-scale model with variational method. In meso- or micro-scale studies, the assimilation of Doppler radar data, which have relatively high spatiotemporal resolution and contain adequate meso-scale cloud-water, precipitation and wind information, is significant to the improvements of meso-scale initial field. One-Dimensional Variational Assimilation of Radar-Derived Precipitation Data for “98·7” Torrential Rain limited area meso-scale numerical model underη–coordinate with 37km resolution One dimensional variational assimilation system data: radiosonde data and reflectivity observations Retrieval of 1 hour precipitation using reflectivity observations Application: 0~24h rain forecast GRAPeS_3DVAR system On the Three Dimensional Variational Assimilation of Radar Wind Data related to 2003-7-8 Catastrophic Torrential Rain Advanced Regional ?-coordinate Model version 2.1 GRAPES_3dvar system Retrieval wind data from Wuhan and Yichang Doppler radar 3DVAR experiments for “7·8” heavy rain The prescribed results show that in the simulation of an extremely heavy rain on July 8 in middle Yangtze river, the assimilation of retrieved wind from Wuhan and Yichang Doppler radar by 3DVAR greatly improve the initial field which is consistent with model and conducive for strong precipitation generation both in thermodynamics and dynamics with the results that the model reproduces 24h accumulated and hourly rainfall close to observation in the middle Yangtze River. It proves that effective usage of retrieved wind data from Doppler radar can make positive contrib