Improving inland precipitation forecast in China through data assimilation of microwave temperature sounding data from a three‐orbit constellation

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-08-01 DOI:10.1002/qj.4802
Yu Huang, Zhengkun Qin, Juan Li, Jiali Mao
{"title":"Improving inland precipitation forecast in China through data assimilation of microwave temperature sounding data from a three‐orbit constellation","authors":"Yu Huang, Zhengkun Qin, Juan Li, Jiali Mao","doi":"10.1002/qj.4802","DOIUrl":null,"url":null,"abstract":"Microwave temperature sounders onboard polar‐orbiting satellites can provide global observation data twice a day, supplying a large amount of temperature information for global data assimilation and serving as a crucial instrument to improve operational numerical forecasts. However, regional numerical forecasts are still subject to a lack of polar‐orbiting satellite data within regional model domains, and even multiple polar‐orbiting satellites may simultaneously miss measurements. Establishing a three‐orbit observation system of polar‐orbiting satellites is crucial to improve the spatiotemporal coverage of polar‐orbiting satellite data. In this study, we investigate the impact of assimilating microwave temperature sounding data from a three‐orbit constellation on precipitation forecasts in inland China based on the data from the US afternoon‐orbit satellite NOAA‐19, the European morning‐orbit satellite Meteorological Operational satellite‐A and the Chinese early‐morning‐orbit satellite Fengyun‐3E (FY‐3E) launched recently. The research results indicate that there are data gaps at 0600 and 1800 UTC in the East Asian region only for the morning‐orbit and afternoon‐orbit satellite observations. The FY‐3E satellite can provide additional microwave temperature sounding observations over the eastern region of China, thus partially compensating for the gap in polar‐orbiting satellite data in China. Moreover, the additional assimilation of the FY‐3E data can further improve numerical forecasts, effectively adjusting the spatial structure and eastward movement of the weather system, thereby considerably increasing the prediction accuracy of rainfall location and intensity. Rolling‐prediction results show that the data from the three‐orbit constellation provide a stable and notable improvement in precipitation forecasts in inland China, especially for forecasts longer than nine hours and amounts of rainfall below 10 mm. These research findings provide valuable insights for optimizing the assimilation application of polar‐orbiting satellite data in regional numerical forecasts.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-08-01","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.4802","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

Microwave temperature sounders onboard polar‐orbiting satellites can provide global observation data twice a day, supplying a large amount of temperature information for global data assimilation and serving as a crucial instrument to improve operational numerical forecasts. However, regional numerical forecasts are still subject to a lack of polar‐orbiting satellite data within regional model domains, and even multiple polar‐orbiting satellites may simultaneously miss measurements. Establishing a three‐orbit observation system of polar‐orbiting satellites is crucial to improve the spatiotemporal coverage of polar‐orbiting satellite data. In this study, we investigate the impact of assimilating microwave temperature sounding data from a three‐orbit constellation on precipitation forecasts in inland China based on the data from the US afternoon‐orbit satellite NOAA‐19, the European morning‐orbit satellite Meteorological Operational satellite‐A and the Chinese early‐morning‐orbit satellite Fengyun‐3E (FY‐3E) launched recently. The research results indicate that there are data gaps at 0600 and 1800 UTC in the East Asian region only for the morning‐orbit and afternoon‐orbit satellite observations. The FY‐3E satellite can provide additional microwave temperature sounding observations over the eastern region of China, thus partially compensating for the gap in polar‐orbiting satellite data in China. Moreover, the additional assimilation of the FY‐3E data can further improve numerical forecasts, effectively adjusting the spatial structure and eastward movement of the weather system, thereby considerably increasing the prediction accuracy of rainfall location and intensity. Rolling‐prediction results show that the data from the three‐orbit constellation provide a stable and notable improvement in precipitation forecasts in inland China, especially for forecasts longer than nine hours and amounts of rainfall below 10 mm. These research findings provide valuable insights for optimizing the assimilation application of polar‐orbiting satellite data in regional numerical forecasts.
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
通过三轨星座微波温度探测数据同化改进中国内陆降水预报
极轨卫星上的微波温度探测仪每天可以提供两次全球观测数据,为全球数据同化提供大量温度信息,是改进业务数值预报的重要工具。然而,在区域模式域内,区域数值预报仍然受到极轨卫星数据缺乏的影响,甚至多颗极轨卫星可能同时漏测。建立极轨卫星三轨观测系统对于提高极轨卫星数据的时空覆盖率至关重要。在本研究中,我们以美国下午轨道卫星 NOAA-19、欧洲早晨轨道卫星 Meteorological Operational Satellite-A 和近期发射的中国凌晨轨道卫星风云三号 E(FY-3E)的数据为基础,研究了三轨星座微波测温数据同化对中国内陆降水预报的影响。研究结果表明,东亚地区仅在上午轨道和下午轨道卫星观测的 0600 和 1800 UTC 时段存在数据缺口。FY-3E 卫星可提供中国东部地区额外的微波测温观测数据,从而部分弥补中国极轨卫星数据的缺口。此外,FY-3E 数据的补充同化可进一步改善数值预报,有效调整天气系统的空间结构和东移方向,从而大大提高降雨位置和强度的预报精度。滚动预报结果表明,三轨星座数据对中国内陆地区的降水预报有稳定而显著的改善作用,特别是对超过 9 小时的预报和 10 毫米以下的降雨量。这些研究成果为优化极轨卫星数据在区域数值预报中的同化应用提供了宝贵的见解。
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
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.
期刊最新文献
Multivariate post‐processing of probabilistic sub‐seasonal weather regime forecasts Relationship between vertical variation of cloud microphysical properties and thickness of the entrainment interfacial layer in Physics of Stratocumulus Top stratocumulus clouds Characteristics and trends of Atlantic tropical cyclones that do and do not develop from African easterly waves Teleconnection and the Antarctic response to the Indian Ocean Dipole in CMIP5 and CMIP6 models First trial for the assimilation of radiance data from MTVZA‐GY on board the new Russian satellite meteor‐M N2‐2 in the CMA‐GFS 4D‐VAR system
×
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