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地基云遥感反演进展及挑战 被引量:6

Progress and challenges of ground-based cloud remote sensing
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摘要 云在地球系统能量平衡和水循环中扮演着至关重要的作用,其特征的准确获取对于理解大气物理过程、改进天气和气候模拟具有重要意义。地基云遥感反演是了解云特征、评估卫星云观测能力的重要手段。自20世纪80年代以来,地基云遥感反演获得快速发展,各种地基云遥感反演方法涌现,在2010年前后达到一个相对瓶颈期,已有的地基云遥感反演方法有几十种之多。从遥感手段上来说,地基云遥感包括主动遥感和被动遥感。从遥感对象上来说,地基云遥感包括宏观特征遥感反演和微观特征遥感反演。就宏观特征来说,可以分为三个类别:云识别或云量的探测方法、云边界的确定方法以及云相态的反演方法。就微观特征来说,地基云遥感反演方法基本分为两大类型,最优化求解法和经验参数化方法。任何一种云遥感反演方法都有其相对优势和不足,对其进行b了总结归纳,论述地基云遥感反演的进展。不同地基云遥感反演产品直接存在着巨大差异,远大于单个遥感反演方法所给定的不确定性信息,表明现有地基云遥感反演仍然存在巨大挑战,归纳提出了云遥感反演中存在的若干挑战,以期为未来云遥感的发展提供了方向参考。 Clouds play essential roles to the Earth’s energy balance and hydrological cycle,accurate cloud properties are important for un⁃derstanding the atmospheric physical processes,and improving the weather and climate model simulation.Ground-based cloud remote sens⁃ing is one method to obtain cloud properties and validate the satellite remote sensing.It has been developed first since 1980s and a variety of ground-based retrieval algorithms have been proposed.The ground-based remote sensing includes both active and passive remote sensing,and can be used for obtaining both cloud macro-and micro-physical properties.For cloud macrophysical properties,the retrievals can be simply divided into three types based on the purposes,which are cloud detection or cloud amount observation method,cloud boundary identi⁃fication method,and cloud phase determination method.For cloud microphysical properties,the ground-based cloud retrieval algorithm can be generally classified into two types,the optical retrieval algorithm and the empirical parameterization algorithm.Each retrieval algorithm has its merits and disadvantages.This study provides an overview of existing ground-based remote sensing and retrieval algorithms.The cloud properties from different retrieval algorithms could have significant discrepancies,which are even larger than the uncertainties of cloud properties indicated by the retrieval algorithm.The large discrepancies imply that there are still grand challenges in the ground-based cloud retrievals,which have also been summarized and proposed in this study.
作者 赵传峰 杨以坤 ZHAO Chuanfeng;YANG Yikun(College of Global Change and Earth System Science,Beijing Normal University,Beijing 100875)
出处 《暴雨灾害》 2021年第3期243-258,共16页 Torrential Rain and Disasters
基金 国家自然科学基金项目(41925022,91837204) 河北省社会发展科技处重点研发计划民生科技专项(20375402D) 国家重点研发专项(2017YFC1501403,2019YFA0606803)。
关键词 宏观特征 微观特征 云反演方法 地基遥感 Clouds macro-physical properties micro-physical properties cloud retrieval algorithm ground-based remote sensing
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