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《大气和海洋科学快报(英文版)》 2014-06
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A Case Study of Impact of FY-2C Satellite Data in Cloud Analysis to Improve Short-Range Precipitation Forecast

LIU Rui-Xia;CHEN Hong-Bin;CHEN De-Hui;XU Guo-Qiang;Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite,National Satellite Meteorological Center,China Meteorological Administration;Laboratory for Middle Atmosphere and Global Environment Observation (LAGEO),Institute of Atmospheric Physics,Chinese Academy of Sciences;Numerical Prediction Center,China Meteorological Administration;  
Chinese FengYun-2C(FY-2C) satellite data were combined into the Local Analysis and Prediction System(LAPS) model to obtain three-dimensional cloud parameters and rain content. These parameters analyzed by LAPS were used to initialize the Global/Regional Assimilation and Prediction System model(GRAPES) in China to predict precipitation in a rainstorm case in the country. Three prediction experiments were conducted and were used to investigate the impacts of FY-2C satellite data on cloud analysis of LAPS and on short range precipitation forecasts. In the first experiment, the initial cloud fields was zero value. In the second, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS without combining the satellite data. In the third experiment, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS including satellite data. The results indicated that the FY-2C satellite data combination in LAPS can show more realistic cloud distributions, and the model simulation for precipitation in 1–6 h had certain improvements over that when satellite data and complex cloud analysis were not applied.
【Fund】: supported by the National Natural Science Foundation of China (41375025 41275114 and 41275039);; the National High Technology Research and Development Program of China (863 Program 2012AA120903);; the Public Benefit Research Foundation of the China Meteorological Administration (GYHY201106044 and GYHY201406001);; the China Meteorological Administration Torrential Flood Project
【CateGory Index】: P457.6
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