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基于“上升-平漂-下降”探空资料的长江中下游暴雨同化试验

Assimilation Experiment of Rainstorm in the Middle and Lower Reaches of the Yangtze River Based on "Up-Drift-Down" Sounding Data

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【作者】 张旭鹏郭启云杨荣康马旭林曹晓钟

【Author】 ZHANG Xupeng;GUO Qiyun;YANG Rongkang;MA Xulin;CAO Xiaozhong;Key Laboratory of Meteorological Disaster of Ministry of Education,Nanjing University of Information Science and Technology;CMA Meteorological Observation Centre;

【通讯作者】 郭启云;

【机构】 南京信息工程大学气象灾害教育部重点实验室中国气象局气象探测中心

【摘要】 为进一步讨论新型"上升-平漂-下降"探空数据在资料同化与数值预报中的应用效果,基于WRF(Weather Research and Forecast)模式及WRFDA(WRF data assimilation)同化系统进行同化对比试验。在对新型探空试验数据进行质量评估和稀疏化的基础上,将下降段资料与常规观测资料组合同化,并讨论其对于长江中下游地区暴雨预报质量的影响及原因。主要试验结果包括:通过与FNL资料、业务同站探空数据交叉对比验证最新试验数据准确性;使用特性层与规定层结合的方案对新型探空上升、下降段进行稀疏化处理可以得到较优效果;同化下降段数据能够在一定程度上提高暴雨预报技巧;风场及湿度场的调整是暴雨预报技巧有所提高的重要原因之一。

【Abstract】 In order to further discuss the application effect of a new type of "up-drift-down" sounding data to data assimilation and numerical prediction,assimilation comparisons were carried out based on the WRF(Weather Research and Forecast) model and WRFDA(WRF data assimilation) system.In this paper,based on the quality evaluation and sparseness of the new radiosonde data,the descending data are combined and assimilated with the conventional observation data.The influence and causes of the simulated data on the rainstorm forecast quality in the middle and lower reaches of the Yangtze River are discussed.The main test results include that the accuracy of the latest test data is verified by cross-comparison of the test data with the FNL data and sounding data from the same station.The scheme of combining the characteristic layers with the specific layers can be used to sparse the ascending and descending segments of the new radiosonde,which can get better results.The rainstorm forecasting technique can be improved to some extent by assimilating the data in the descending section.The adjustment of wind field and humidity field is one of the important reasons for the improvement of rainstorm forecasting skills.

【基金】 国家重点研发计划(2018YFC1506201、2018YFC1506204)共同资助
  • 【分类号】P412.2
  • 【被引频次】2
  • 【下载频次】66
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