Dynamic channel selection based on vertical sensitivities for the assimilation of FY‐4A geostationary interferometric infrared sounder targeted observations

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Yonghui Li, Wei Han, Wansuo Duan
{"title":"Dynamic channel selection based on vertical sensitivities for the assimilation of FY‐4A geostationary interferometric infrared sounder targeted observations","authors":"Yonghui Li, Wei Han, Wansuo Duan","doi":"10.1002/qj.4760","DOIUrl":null,"url":null,"abstract":"Target observations have garnered significant attention owing to their successful applications in enhancing forecasting skills of extreme weather events, particularly tropical cyclone (TC) events. The key step of implementing target observation is to determine the sensitive area in advance. Previous studies often obtained the sensitive areas for TC forecasting by vertically integrating the energy of optimal perturbation and taking the horizontal area of large energy, in an attempt to use it to represent roughly the sensitivity of the whole atmospheric layer. The advent of the geostationary interferometric infrared sounder on the FY‐4A satellite and then corresponding satellite data assimilation have opened up a new possibility for identifying the vertical sensitivity for TC forecasting to improve the forecasting skill. This article proposes a targeting satellite channel (TSC) approach to accurately capture the sensitivity along vertical directions of the atmosphere that allows one to preferentially select the channels whose observations locate on the sensitive vertical atmospheric layers. Numerical experiments demonstrate that, when preferentially assimilating the channel observations obtained from the TSC approach, the TC tracks achieve a considerably smaller forecast error than the information entropy channel selection approach. The TSC approach, therefore, has the potential for the satellite data assimilation to improve TC track forecasting skill very effectively, which can also provide guidance to targeting observations in field campaigns for TC forecasting.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quarterly Journal of the Royal Meteorological Society","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1002/qj.4760","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Target observations have garnered significant attention owing to their successful applications in enhancing forecasting skills of extreme weather events, particularly tropical cyclone (TC) events. The key step of implementing target observation is to determine the sensitive area in advance. Previous studies often obtained the sensitive areas for TC forecasting by vertically integrating the energy of optimal perturbation and taking the horizontal area of large energy, in an attempt to use it to represent roughly the sensitivity of the whole atmospheric layer. The advent of the geostationary interferometric infrared sounder on the FY‐4A satellite and then corresponding satellite data assimilation have opened up a new possibility for identifying the vertical sensitivity for TC forecasting to improve the forecasting skill. This article proposes a targeting satellite channel (TSC) approach to accurately capture the sensitivity along vertical directions of the atmosphere that allows one to preferentially select the channels whose observations locate on the sensitive vertical atmospheric layers. Numerical experiments demonstrate that, when preferentially assimilating the channel observations obtained from the TSC approach, the TC tracks achieve a considerably smaller forecast error than the information entropy channel selection approach. The TSC approach, therefore, has the potential for the satellite data assimilation to improve TC track forecasting skill very effectively, which can also provide guidance to targeting observations in field campaigns for TC forecasting.
基于垂直灵敏度的动态信道选择,用于同化 FY-4A 地球静止干涉红外探测仪目标观测数据
目标观测在提高极端天气事件,特别是热带气旋(TC)事件的预报能力方面的成功应用引起了人们的极大关注。实施目标观测的关键步骤是提前确定敏感区域。以往的研究通常通过对最优扰动的能量进行垂直积分,取能量较大的水平区域,试图以此大致代表整个大气层的敏感性,从而获得热带气旋预报的敏感区域。FY-4A 卫星上地球静止干涉红外探测仪的出现以及随后相应的卫星数据同化为确定 TC 预报的垂直敏感性以提高预报技能提供了新的可能。本文提出了一种精确捕捉大气垂直方向敏感性的卫星信道定位(TSC)方法,可以优先选择观测点位于大气垂直敏感层的信道。数值实验证明,当优先同化 TSC 方法获得的信道观测数据时,TC 轨道的预报误差比信息熵信道选择方法小得多。因此,TSC方法具有卫星数据同化的潜力,能非常有效地提高TC轨迹预报技能,这也能为TC预报野外活动中的目标观测提供指导。
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 求助全文
来源期刊
CiteScore
16.80
自引率
4.50%
发文量
163
审稿时长
3-8 weeks
期刊介绍: The Quarterly Journal of the Royal Meteorological Society is a journal published by the Royal Meteorological Society. It aims to communicate and document new research in the atmospheric sciences and related fields. The journal is considered one of the leading publications in meteorology worldwide. It accepts articles, comprehensive review articles, and comments on published papers. It is published eight times a year, with additional special issues. The Quarterly Journal has a wide readership of scientists in the atmospheric and related fields. It is indexed and abstracted in various databases, including Advanced Polymers Abstracts, Agricultural Engineering Abstracts, CAB Abstracts, CABDirect, COMPENDEX, CSA Civil Engineering Abstracts, Earthquake Engineering Abstracts, Engineered Materials Abstracts, Science Citation Index, SCOPUS, Web of Science, and more.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信