APPLICATION EXPERIMENT OF ASSIMILATING RADAR-RETRIEVED WATER VAPOR IN SHORT-RANGE FORECAST OF RAINFALL IN THE ANNUALLY FIRST RAINY SEASON OVER SOUTH CHINA

A scheme of assimilating radar-retrieved water vapor is adopted to improve the quality of NWP initial field for improvement of the accuracy of short-range precipitation prediction. To reveal the impact of the assimilation of radar-retrieved water vapor on short-term precipitation forecast, three par...

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Published inJournal of Tropical Meteorology Vol. 22; no. 4; pp. 578 - 588
Main Author 张诚忠 陈子通 万齐林 林振敏 黄燕燕 戴光丰 丁伟钰
Format Journal Article
LanguageEnglish
Published Guangzhou Guangzhou Institute of Tropical & Marine Meteorology 01.12.2016
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ISSN1006-8775
DOI10.16555/j.1006-8775.2016.04.012

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Summary:A scheme of assimilating radar-retrieved water vapor is adopted to improve the quality of NWP initial field for improvement of the accuracy of short-range precipitation prediction. To reveal the impact of the assimilation of radar-retrieved water vapor on short-term precipitation forecast, three parallel experiments, cold start, hot start and hot start plus the assimilation of radar-retrieved water vapor, are designed to simulate the 31 days of May, 2013 with a fine numerical model for South China. Furthermore, a case of heavy rain that occurred from 8-9 May 2013 over the region from the southwest of Guangdong province to Pearl River Delta is analyzed in detail. Results show that the cold start experiment is not conducive to precipitation 12 hours ahead; the hot start experiment is able to reproduce well the first6 hours of precipitation, but badly for subsequent prediction; the experiment of assimilating radar-retrieved water vapor is not only able to simulate well the precipitation 6 hours ahead, but also able to correctly predict the evolution of rain bands from 6 to 12 hours in advance.
Bibliography:44-1409/P
ZHANG Cheng-zhong;CHEN Zi-tong;WAN Qi-lin;LIN Zhen-min;HUANG Yan-yan;DAI Guang-feng;DING Wei-yu;Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction,CMA;Guangxi Region Meteorological Observatory
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ISSN:1006-8775
DOI:10.16555/j.1006-8775.2016.04.012