基于FY-3DMWRI的海上大气可降水反演研究  

Research on retrieval for total precipitable water by FY-3D MWRI

作　　者：徐超凡 官元红[1,2,3,4] 鲍艳松[4] 陆其峰[5] 李江涛 XU ChaoFan;GUAN YuanHong;BAO YanSong;LU QiFeng;LI JiangTao(School of Mathematics and Statistics,Nanjing University of Information Science and Technology,Nanjing 210044,China;Center for Applied Mathematics of Jiangsu Province,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangsu International Joint Laboratory on System Modeling and Data Analysis,Nanjing University of Information Science and Technology,Nanjing 210044,China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science and Technology,Nanjing 210044,China;Earth System Modeling and Prediction Center,China Meteorological Administration,Beijing 100081,China)

机构地区：[1]南京信息工程大学数学与统计学院,南京210044 [2]南京信息工程大学江苏省应用数学中心,南京210044 [3]南京信息工程大学江苏省系统建模与数据分析国际合作联合实验室,南京210044 [4]南京信息工程大学气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心,南京210044 [5]中国气象局地球系统数值预报中心,北京100081

出　　处：《地球物理学进展》2024年第5期1723-1733,共11页Progress in Geophysics

基　　金：国家自然科学基金项目(U2242212,41975087);江苏省水利科学研究院自主科研项目(2023z034);水利部重大科技项目(SKS-2022072);江苏省水利科学研究院自主科研项目(2024z007);江苏省水利科技项目(2023022)联合资助。

摘　　要：水汽是大气中重要的组成部分,实现大气中水汽含量的高精度反演对气象研究有着重要意义.本文利用FY-3D卫星微波成像仪(FY-3D/MWRI)在2019—2022年间每年7月份的亮温资料,根据随机森林算法,以太平洋区域ERA5水汽数据为参考,分别建立海上晴空大气可降水的六通道、八通道随机森林反演模型(RF6、RF8).试验结果表明,相较于经验回归反演模型,随机森林反演模型精度有明显提高,其中RF6模型精度提高了约22%,RF8模型精度提高了约28%.进一步,将基于太平洋区域数据训练生成的RF6、RF8反演模型应用于北大西洋与南印度洋的大气可降水反演,也得到了较好的结果.因此,海上晴空大气可降水的随机森林反演模型具有较好的稳定性和普适性,且RF8模型优于RF6模型,RF6模型优于经验回归模型.Water vapor is an important part of the atmosphere,and it is of great significance to realize the high-precision retrieval of water vapor content in the atmosphere for meteorological research.This paper used brightness temperature data of FY-3D/MWRI in July from 2019 to 2022 annually,with the water vapor data of ERA5 on Pacific as references,established six-channel and eight-channel random forest retrieval models(RF6 and RF8)for total precipitable water in maritime clear sky,based on the random forest algorithm.The experimental results indicated that compared to the empirical regression retrieval model,the random forest retrieval model have improved accuracy obviously,with the RF6 model achieving an improvement of about 22%and the RF8 model achieving an improvement of about 28%.Furthermore,when applying the RF6 and RF8 models which trained based on Pacific region data to the North Atlantic and South Indian Ocean,positive retrieval results were also obtained.Considering all factors,the RF8 model outperforms the RF6 model,and the RF6 model outperforms the empirical regression model.

关 键 词：微波成像仪 大气可降水量 反演 随机森林模型 经验回归模型 

分 类 号：P407[天文地球—大气科学及气象学]