基于温湿廓线反演的风云三号D星微波探测仪云区资料同化试验  

Experimental Research of FY-3D Microwave Detector Cloudy Data Assimilation Based on Temperature and Humidity Profile Retrieval

作　　者：金子琪 张恒[3] 鲍艳松[1] 成巍 崔伟[3] 官元红[5] 李欢 茆佳佳[7] JIN Zi-qi;ZHANG Heng;BAO Yan-song;CHENG Wei;CUI Wei;GUAN Yuan-hong;LI Huan;MAO Jia-jia(School of Atmospheric Physics,Nanjing University of Information Science&Technology,Nanjing 210044,China;Zhejiang Institute of Meteorological Sciences,Hangzhou 310008,China;Shanghai Satellite Engineering Institute,Shanghai 200240,China;Beijing Institute of Applied Meteorology,Beijing 100082,China;School of Mathematics and Statistics,Nanjing University of Information Science&Technology,Nanjing 210044,China;Computational Aerodynamics Institute of China Aerodynamics Research and Development Center,Mianyang 621000,China;Meteorological Observation Center of China Meteorological Administration,Beijing 100081,China)

机构地区：[1]南京信息工程大学大气物理学院,南京210044 [2]浙江省气象科学研究所,杭州310008 [3]上海卫星工程研究所,上海200240 [4]北京应用气象研究所,北京100082 [5]南京信息工程大学数学与统计学院,南京210044 [6]中国空气动力研究与发展中心计算空气动力研究所,绵阳621000 [7]中国气象局气象探测中心,北京100081

出　　处：《科学技术与工程》2023年第13期5429-5443,共15页Science Technology and Engineering

基　　金：高分辨率对地观测系统重大专项(GFZX0404120315);上海航天科技创新基金(SAST2019-046)。

摘　　要：为了探究云区卫星微波资料的同化应用,利用中国风云三号D星(Fengyun-3D,FY-3D)微波温度计二型(microwave temperature sounder-2,MWTS2)和微波湿度计二型(microwave humidity sounder-2,MWHS2)资料,基于人工神经网络算法研制了云区温湿廓线反演模型,建立了云区资料的间接同化方案。于2019年6月开展晴空和云区同化试验,评估加入云区MWTS2和MWHS2资料对区域模式预报的影响。试验结果表明:MWTS2和MWHS2资料的同化对温湿度预报场有改善,主要体现在模式中高层均方根误差和平均偏差的减小,云区同化的改善幅度比晴空同化更大;同化MWTS2和MWHS2资料对于提高降水预报技巧有积极影响,云区同化对降水预报的改善主要体现在同化后的12~24 h,较晴空同化更明显。针对强降水个例分析表明,MWTS2和MWHS2资料对温度场、湿度场、水汽通量散度场的调整有利于降水预报的改善,而云区同化能够直接对天气系统的初始场进行调整,降水的位置与强度预报效果更好。In order to explore the assimilation application of cloud-affected satellite microwave observations,the inversion model of atmospheric temperature and humidity profile in cloudy condition based on the artificial neural network algorithm was developed by using Fengyun-3D(FY-3D)microwave temperature sounder-2(MWTS2)and microwave humidity sounder-2(MWHS2)data and the indirect assimilation scheme of cloudy data was established.One-month continuous experiments and real-case study about clear-sky and cloudy assimilation were performed in June 2019 to illustrate the influence of MWTS2 and MWHS2 cloudy observations on regional numerical weather prediction model.The results show that the assimilation of MWTS2 and MWHS2 data improves the predicted temperature and humidity field,which is mainly reflected in the reduction of bias and root mean square error in the high layer of the model.The improvement rate of cloudy assimilation is higher than that of clear-sky assimilation.Assimilating MWTS2 and MWHS2 data has a positive effect on improving precipitation prediction skills.The improvement of cloudy assimilation on precipitation prediction is mainly reflected in 12~24 h after assimilation,which is more obvious than that of clear-sky assimilation.The real-case study of heavy precipi-tation shows that the adjustment of temperature,humidity and moisture flux divergence field by MWTS2 and MWHS2 data is conducive to improve precipitation forecast skill,while cloudy assimilation can adjust the initial field of weather system directly,having better pre-diction effect of precipitation position and intensity.

关 键 词：FY-3D MWTS2 MWHS2 温湿廓线反演 云区资料同化 

分 类 号：P457.6[天文地球—大气科学及气象学]