Application of ATOVS radiance assimilation to numerical simulation of a mesoscale heavy rainfall

H. Bing, Bai Jie, Li Wei, Xiaoting Wang
{"title":"Application of ATOVS radiance assimilation to numerical simulation of a mesoscale heavy rainfall","authors":"H. Bing, Bai Jie, Li Wei, Xiaoting Wang","doi":"10.1117/12.910435","DOIUrl":null,"url":null,"abstract":"Based on ATOVS data and conventional sounding data, two assimilation experiments are performed to simulate a heavy rainfall over the middle-lower reaches of Yangtze River and the east of southwest China from June 22 to 24 in 2004 by using model MM5. In the NOATOVS experiment, only conventional sounding data are assimilated based on the successive correction scheme, while in the ATOVS experiment, the ATOVS radiance data are assimilated by using the GRAPES (Global and Regional Assimilation and Prediction System) 3D-Var system. The effect of the radiance data on the background field is analyzed. It indicates that direct assimilation of ATOVS radiance data could improve the temperature, humidity and wind fields within the troposphere. Moreover, the comparison between the results of the two experiments shows that ATOVS experiment can not only simulate the circulation pattern well, but also describe the intensity and the distribution of the rainfall better than the NOATOVS experiment.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Symposium on Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.910435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Based on ATOVS data and conventional sounding data, two assimilation experiments are performed to simulate a heavy rainfall over the middle-lower reaches of Yangtze River and the east of southwest China from June 22 to 24 in 2004 by using model MM5. In the NOATOVS experiment, only conventional sounding data are assimilated based on the successive correction scheme, while in the ATOVS experiment, the ATOVS radiance data are assimilated by using the GRAPES (Global and Regional Assimilation and Prediction System) 3D-Var system. The effect of the radiance data on the background field is analyzed. It indicates that direct assimilation of ATOVS radiance data could improve the temperature, humidity and wind fields within the troposphere. Moreover, the comparison between the results of the two experiments shows that ATOVS experiment can not only simulate the circulation pattern well, but also describe the intensity and the distribution of the rainfall better than the NOATOVS experiment.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
ATOVS辐射同化在一次中尺度暴雨数值模拟中的应用
基于ATOVS资料和常规探测资料,利用MM5模式对2004年6月22 ~ 24日长江中下游及西南东部地区的一次强降水进行了同化试验。在NOATOVS实验中,仅基于逐次校正方案同化常规探测数据,而在ATOVS实验中,使用GRAPES (Global and Regional Assimilation and Prediction System) 3D-Var系统同化ATOVS辐射数据。分析了辐射度数据对背景场的影响。结果表明,直接同化ATOVS辐射数据可以改善对流层内的温度、湿度和风场。两种试验结果的对比表明,ATOVS试验不仅能较好地模拟环流型,而且能较好地描述降水的强度和分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on optimal path planning algorithm of task-oriented optical remote sensing satellites On-orbit geometric calibration and validation of Optical-1 HR Effectiveness analysis of ACOS-Xco2 bias correction method with GEOS-Chem model results Research on geometric rectification of the Large FOV Linear Array Whiskbroom Image Temporal and spatial analysis of global GOSAT XCO2 variations characteristics
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1