摘要
土壤湿度是影响气候的至关重要的变量之一。利用数据同化方法反演大规模高精度土壤湿度数据是目前土壤水分研究的一个重要方向。结合国内外土壤湿度遥感估算研究现状,总结了土壤水分同化算法主要应用进程,梳理了目前实现土壤水分反演且应用广泛的陆面过程模型,Noah模型、通用陆面过程模型CLM、简单生物圈模型Si B2、北方生产力模拟模型BEPS,介绍了大范围卫星土壤水分数据集,包括陆面同化系统数据集、ASCAT数据集、AMSR-E数据集及SMOS数据集,最后探讨了遥感土壤水分同化过程中存在的问题及发展方向。
Soil moisture is one of the critical variables that affect climate. Retrieving large-scale and high-precision soil moisture data with data assimilation technology is an important issue to study soil moisture. Combining with research status at home and abroad in estimating soil moisture,we sum up the major application process of assimilation algorithm in soil moisture,introduce the widely used land surface model which can retrieve the soil moisture,Noah,Common Land Model（ CLM）,Simple Biosphere Model（ Si B2）,North productivity simulation model（ BEPS）,introduce a wide range of soil moisture satellite data sets including the land surface data assimilation system data sets,ASCAT data sets,AMSR-E data sets and SMOS data sets,and finally discuss the problems and development direction of soil moisture in the process of assimilation.
出处
《地球科学进展》
CAS
CSCD
北大核心
2015年第6期668-679,共12页
Advances in Earth Science
基金
"十二五"国家科技支撑计划项目"村镇环境快速检测与动态监测装备研发"(编号:2012BAJ24B02)资助
关键词
数据同化
土壤湿度
陆面过程模型
遥感数据集
Data assimilation
Soil moisture
Land surface process model
Remote sensing data sets
