星载主动遥感测云现状与展望
Status and prospect of cloud measurement by satellite active remote sensing
- 2023年27卷第9期 页码：2041-2059
纸质出版日期： 2023-09-07
DOI： 10.11834/jrs.20221080
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摘要
云是表征天气和气候变化的重要指标，在大气的能量分配、辐射传输等中起着重要作用。卫星遥感探测以其覆盖范围广、信息量大、重复频率高等诸多优势，成为研究云的主要手段。目前星载测云主动遥感技术主要包括毫米波雷达和激光雷达技术。本文介绍了星载毫米波雷达和激光雷达测云技术发展及数据应用研究现状，重点分析了CloudSat搭载的云廓线雷达CPR和CALIPSO搭载的云—气溶胶激光雷达CALIOP协同观测的成果和进一步发展需求。从全球云三维结构参数的需求分析，探讨了太赫兹雷达、高光谱激光雷达、多传感器数据融合等测云新技术发展和应用潜能，以及多星系统及单星多载荷等协同观测新模式的技术关键和轨道高度对探测性能的影响，提出多传感器共平台协同观测及数据融合研究三维云结构信息的设想。
Abstract
Cloud is an important indicator of weather and climate change
and it is of great importance to atmospheric energy distribution and radiative transfer. Satellite remote sensing has become an indispensable technology for cloud research due to its global coverage
multiple types of information
and high repetitive frequency. In this work
the development of cloud measurement technology and the data application research of current spaceborne millimeter-wave radar and lidar are summarized. The future development requirements and trend are then proposed according to the progress of current cloud measurement technology and applications.
First
the technology research and data typical application status of spaceborne millimeter-wave radar and lidar are introduced and summarized
in which the key technologies and important application of Cloud Profile Radar (CPR) on CloudSat and cloud aerosol lidar (CALIOP) on CALIPSO are highlighted. The achievements of collaborative observation by CPR and CALIOP as well as the aspects to be improved are then summarized emphatically. Based on the requirement analysis of obtaining the 3D fine structure of global cloud
the development and application potential of novel measurement technologies such as terahertz radar
high-spectral-resolution lidar
and multisensor data fusion are provided. Furthermore
the key technologies of the new cooperative observation modes
such as multisatellite system and multiple payloads on single satellite platform
are discussed. The influence of orbit altitude on the detection performance is deliberated based on the analysis of the relationship between the received intensity of echo signal and the orbit altitude.
The cloud load performance of active remote sensing
cooperative observation mode
cooperation with passive remote sensing instruments
and multisource data retrieval and fusion for spaceborne cloud measurement still need to be improved according to the research status of spaceborne cloud radar and lidar. The latest advanced technology of spaceborne active remote sensing can be fully utilized for observing more accurate cloud parameters and more microphysical information
such as multiwavelength
multipolarization
Doppler technology
terahertz radar
hyperspectral lidar
and multisensor data fusion method. The collaborative observation of microwave radar
lidar
and other sensors on the same platform is necessary for better understanding the formation and evolution of cloud
to improve the ability of weather forecasting and climate monitoring further.
Satellite active remote sensing for cloud measurement is employed to observe the macroscopic and microphysical characteristics of cloud accurately. Its high-quality data have been widely applied to cloud physics
weather forecasting
environment monitoring
and climate change. Moreover
it plays an important role in improving the accuracy of numerical weather forecasting and climate research. With the continuous progress of active remote sensing technology
more cloud parameters and higher performance can be realized for spaceborne cloud measurement. In addition to the high-technology applications in spaceborne cloud remote sensing
collaborative observation is an important development trend. A future perspective is then projected on the cooperative observation mode of multiple sensors with common platform and new data fusion methods.
关键词
星载测云主动遥感星载毫米波雷达星载激光雷达协同观测数据融合
Keywords
satellite cloud measurementactive remote sensingspaceborne millimeter wave radarspaceborne lidarcooperative observationdata fusion
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南京信息工程大学,大气物理学院
南京信息工程大学气象灾害预警与评估协同创新中心,气象灾害教育部重点实验室,气候与环境变化国际合作联合实验室,中国气象局气溶胶与云降水重点实验室
南宁师范大学 地理与规划学院
北京师范大学 地理科学学部 遥感科学国家重点实验室
湖南师范大学 地理科学学院
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