摘要
卫星遥感资料对于改善气候模式的强迫场,改进相关物理参数,提高数值模式模拟的准确性具有重要作用。目前,全球已经积累了多年的卫星遥感资料,并且已有多种陆面参量遥感产品。然而,卫星遥感资料在气候模式中的应用还非常有限。充分利用卫星遥感资料,对于提高气候模式模拟能力具有重要作用。选择植被覆盖度(Fractional Vegetation Cover,FVC)、叶面积指数(Leaf Area Index,LAI)和地表反照率(Albedo)3个关键陆面参量的遥感估算方法进行评述,并分析了陆面参量真实性检验的尺度转换问题,还以WRF(Weather Research and Forecasting model)为例,阐述了遥感估算的陆面参量应用于模式的表达方式。最后讨论了关键陆面参量遥感估算的不确定性和遥感参量应用于气候模式的尺度匹配等亟待解决的问题,并对这些问题的未来改进方向进行了展望。
Satellite remote sensing data play an important role in the improvement of climate models forcing field, relevant physical parameters and simulation accuracy. At present, there are many years of satellite remote sensing data and a variety of products about land surface attributes. However, the application of satellite remote sensing data to climate models is still vel7 limited. Fully using satellite remote sensing data is important to impro- ving the simulation ability. In the paper, remote sensing estimates methods of three key land surface parameters in- cluding Fractional Vegetation Coverage ( FVC ), Leaf Area Index (LAI) and surface albedo (Albedo) is reviewed and up-or down-scaling land surface variables in validation process is analyzed. Secondly, taking WRF (Weather Re- search and Forecasting)model as an example, three parameters in climate model are described. Finally, the key problems of using remote sensing data in climate models are discussed, which comprise the uncertainties and scales of remote sensing estimation parameters and the future direction is prospected.
出处
《地球科学进展》
CAS
CSCD
北大核心
2014年第1期56-67,共12页
Advances in Earth Science
基金
国家重点基础研究发展计划项目"全球典型干旱半干旱地区年代尺度气候变化的机理及其影响研究"(编号:2012CB956202)
中国科学院战略性先导科技专项"应对气候变化的碳收支认证及相关问题"项目九"过去百年气候增暖及成因"第二课题"近代变暖中的城市化效应"(编号:XDA05090200)资助
关键词
气候模式
陆面参量
卫星遥感
Climate model
Land surface parameter
Satellite remote sensing.