Quantitative Applications of Weather Satellite Data for Nowcasting:Progress and Challenges

扫码查看

原文链接

国家科技期刊平台
NETL
NSTL
万方数据

外文摘要：Monitoring and predicting highly localized weather events over a very short-term period,typically ranging from minutes to a few hours,are very important for decision makers and public action.Nowcasting these events usually re-lies on radar observations through monitoring and extrapolation.With advanced high-resolution imaging and sound-ing observations from weather satellites,nowcasting can be enhanced by combining radar,satellite,and other data,while quantitative applications of those data for nowcasting are advanced through using machine learning techniques.Those applications include monitoring the location,impact area,intensity,water vapor,atmospheric instability,pre-cipitation,physical properties,and optical properties of the severe storm at different stages(pre-convection,initiation,development,and decaying),identification of storm types(wind,snow,hail,etc.),and predicting the occurrence and evolution of the storm.Satellite observations can provide information on the environmental characteristics in the pre-convection stage and are very useful for situational awareness and storm warning.This paper provides an overview of recent progress on quantitative applications of satellite data in nowcasting and its challenges,and future perspectives are also addressed and discussed.

外文关键词：

weather satellitequantitative applicationsnowcastingpre-convection

作者：

Jun LI、Jing ZHENG、Bo LI、Min MIN、Yanan LIU、Chian-Yi LIU、Zhenglong LI、W.Paul MENZEL、Timothy J.SCHMIT、John L.CINTINEO、Scott LINDSTROM、Scott BACHMEIER、Yunheng XUE、Yayu MA、Di DI、Han LIN

展开 >

作者单位：

Innovation Centre for Fengyun Meteorological Satellite(FYSIC),National Satellite Meteorological Centre,China Meteorological Administration,Beijing 100081,China

School of Atmospheric Sciences and Guangdong Province Key laboratory for Climate Change and Natural Disaster Studies,Sun Yat-sen University and Southern Laboratory of Ocean Science and Engineering,Zhuhai 519082,China

Key Laboratory of Geographic Information Science (Ministry of Education),East China Normal University,Shanghai,200241,China

Research Center for Environmental Changes,'Academia Sinica',Taipei 11529,China

Cooperative Institute for Meteorological Satellite Studies,University of Wisconsin-Madison,WI 53706,USA

Sensors and Calibration Branch,STAR/NESDIS,WI 53706,USA

Wuxi University,Wuxi 214105,China

School of Computer Science,Chengdu University of Information Technology,Chengdu 610225,China

Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science&Technology,Nanjing 210044,China

Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education,National and Local Joint Engineering Research Center of Satellite Geospatial Information Technology,Fuzhou University,Fuzhou 350108,China

展开 >

基金：

National Natural Science Foundation of ChinaNational Natural Science Foundation of China

项目编号：

U214220142175086

出版年：

2024

DOI：

10.1007/s13351-024-3138-6

气象学报(英文版)

中国气象学会

气象学报(英文版)

CSTPCD

影响因子：0.57

ISSN：0894-0525

年,卷(期)：2024.38(3)