摘要
积雪是冰冻圈中最活跃的要素之一,被动微波遥感具有高时间分辨率且能够迅速覆盖全球,在积雪时空变化监测中作用突出.总结分析了积雪被动微波遥感的主要模型,并对其方法、特点和适用性进行了较详细评述,重点介绍了NASA算法在雪深和雪水当量反演中的应用、反演结果的不确定性以及对它的改进.讨论新兴的积雪数据同化方法,介绍了同化被动微波观测以改进雪深和雪水当量反演精度的研究案例.评述了我国积雪被动微波遥感的进展,并且对未来可能的研究方向做出展望.
The passive microwave remote sensing is the most reliable method to retrieve snow depth and snow water equivalent globally. In this paper, the development of this well--established technology is reviewed. The most accepted and frequently used models of passive microwave remote sensing of snow include the National Aeronautics and Space Administration （NASA） algorithm, Microwave Emission Model of Layered Snowpacks （MEMLS）, Helsinki University of Technology （HUT） model, and the snow model derived from the dense medium radiative transfer equation. The theoretical formulations, advantages, disadvantages, and applicabilities of these models are discussed. The evolution of NASA algorithm from Chang＇s early work to the model that has the ability to quantify the uncertainties resulted from the effects of snow grain size and forest fraction are presented in details. The new emerging snow data assimilation method, which is a promising way to combine the remote sensing and snow modeling information in an optimal sense, is reviewed by introducing a few case studies. The research work on passive microwave remote sensing of snow in China is also reviewed, particularly the efforts to solve the problem of snow depth overestimation on the Tibetan Plateau.
出处
《冰川冻土》
CSCD
北大核心
2007年第3期487-496,共10页
Journal of Glaciology and Geocryology
基金
中国科学院寒区旱区环境与工程研究所知识创新工程项目(2003102)
中国科学院创新团队国际合作伙伴计划项目(CXTD-Z2005-2)
国家自然科学基金项目(40601065)资助
关键词
积雪
雪深
雪水当量
积雪数据同化
被动微波遥感
snow cover
snow depth
snow water equivalent
snow data assimilation
passive microwave remote sensing
