大气科学2025,Vol.49Issue(4):1020-1029,10.DOI:10.3878/j.issn.1006-9895.2506.25071
静止轨道微波卫星大气探测能力分析和观测仿真
Atmospheric Sounding Capability Analysis and Observation Simulation of the Fengyun-4 Geostationary Microwave Satellite
摘要
Abstract
Geostationary orbit microwave sounding satellites carrying microwave sounders leverage the relatively stationary characteristics of the platform,as well as the microwave's ability to penetrate clouds and rain,to achieve high-frequency,all-day,and all-weather atmospheric observations.Thus,these satellites provide high-value data for numerical weather forecasting and disaster weather research.This study analyzes the sounding capability of the Chinese Fengyun-4 geostationary orbit microwave satellite,which is currently under development.The observation method and product system are introduced in this paper.The submillimeter wave sounder enables the 55 GHz microwave hyperspectral frequency band and the 380-425 GHz terahertz channel,which are not available on existing low-orbit satellites,greatly expanding the ability of the sounder to observe atmospheric status and cloud parameters.The unique observation geometry characteristics of the satellite are explained through simulation technology in this study.Furthermore,the brightness temperatures of typical channels for detecting temperature and humidity,as well as the terahertz channels,are simulated using the ARMS fast mode and atmospheric backgrounds under a typhoon background.The simulations display the observational characteristics of the microwave satellite and provide references for future applications.关键词
静止轨道微波卫星/大气探测/微波高光谱/太赫兹/观测仿真Key words
Geostationary microwave satellite/Atmosphere sounding/Microwave hyperspectral/Terahertz/Observation simulation分类
天文与地球科学引用本文复制引用
毕研盟,张德军,杨军,窦芳丽,韩阳,王嘉琛,李小青,徐榕焓,胡菊旸,廖蜜..静止轨道微波卫星大气探测能力分析和观测仿真[J].大气科学,2025,49(4):1020-1029,10.基金项目
国家重点研发计划项目2022YFF0801302,国家自然科学基金项目42175167 National Key Research and Development Program of China(Grant 2022YFF0801302),National Natural Science Foundation of China(Grant 42175167) (Grant 2022YFF0801302)