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《Chinese Journal of Atmospheric Sciences》 2006-01
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Effect of Chinese Doppler Radar Data on Nowcasting Output of Mesoscale Model

SHENG Chun-Yan~(1,2,3),PU Yi-Fen~(1),and GAO Shou-Ting~(1)1 Laboratory of Cloud-Precipitation Physics and Severe Storms,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 1000292 Shandong Meteorological Center,Jinan 2500313 Graduate University of Chinese Academy of Sciences,Beijing 100039  
The Advanced Regional Prediction System(ARPS) is a multi-scale model developed by the Center for(Analysis) and Prediction of Storms(CAPS),the complex cloud analysis system in the ARPS data analysis system(ARPSDAS or ADAS) can construct a three-dimensional cloud in the initial field with Doppler radar reflectivity,cloud base and fraction,and satellite image data to adjust the initial cloud and rain water,and ADAS still can adjust the initial wind field directly with radar radial velocity.In order to test the effect of Doppler radar data on mesoscale model,a North China torrential rain event is studied with Chinese Doppler radar data only.Four control experiments are conducted.The 1st experiment is performed without Chinese Doppler radar data analysis,the 2nd is done with Doppler radar reflectivity only to construct a three-dimensional cloud analysis,the 3rd is conducted with radar radial velocity only to adjust the initial wind field,and the last experiment is done with both radar reflectivity and radial velocity.The main results are as follows: 1) The wind components u,v,and w in the initial field adjusted by Doppler radial velocity can be modified under 10 km near the radar observing range,and the most drastic modification of u,v happens in the central troposphere.2) Assimilation of Doppler radar reflectivity can increase the cloud and moisture contents in the strong reflectivity region of the initial field.The adjustment of the water vapor mixture ratio(q_(v)) is mainly below 3 km, the rainfall mixture ratio(q_(r)) below 4 km,cloud vapor mixture ratio(q_(c)) in the troposphere(below 10 km level) and cloud ice(q_(i)) and snow(q_(s)) mixture ratio at around 49 km level in the tro-(posphere.) Diabatic initialization of ADAS will adjust the temperature to balance the cloud microphysical adjustment.3) The comparison between simulated hourly rainfall and observations shows that the assimilation of both reflectivity and radial velocity can improve rainfall forecasting significantly,especially within 3 hours;while the comparison of simulated hourly streamline fields shows that radar radial velocity can increase the mesoscale wind circles in the initial fields and mitigate the model's spin-up time significantly.4) Comparison between radar radial velocity and reflectivity assimilation on the initial field and the simulation shows that Doppler radar radial velocity assimilation can mainly improve the initial wind field while radar reflectivity assimilation can increase the cloud and water contents in the initial field and adjust the temperature.Simulated 6-h rainfall indicates that radar reflectivity assimilation has greater positive effects than radial velocity on the rainfall simulation,although adding radial velocity data results in further improvement in the rain simulation.
【Fund】: 国家自然科学基金资助项目40433007和40333034;; 中国科学院奥运科技项目KACX1-02;; 山东省气象局气象科学技术研究项目2005sdqxz19
【CateGory Index】: P456.2
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