China land soil moisture EnKF data assimilation based on satellite remote sensing data

作     者：SHI ChunXiang XIE ZhengHui QIAN Hui LIANG MiaoLing YANG XiaoChun 

作者机构：National Satellite Meteorological Center China Meteorological Administration Beijing 100081 China Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Institute of Geology Chinese Academy of Geological Sciences Key Geodynamics Laboratory the Ministry of Land and Resources Beijing 100037 China National Meteorological Center China Meteorological Administration Beijing 100081 China 

出 版 物：《Science China Earth Sciences》 (中国科学（地球科学英文版）)

年 卷 期：2011年第54卷第9期

页      面：1430-1440页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 09[农学] 0903[农学-农业资源与环境] 0706[理学-大气科学] 090301[农学-土壤学] 

基　　金：supported by National High Technology Research and Development Program of China (Grant Nos. 2007AA12Z144, 2009AA12Z129) Chinese COPES Project (Grant Nos. GYHY200706005, GYHY200806014) China Meteorological Administration New Technology Promotion Project (Grant No. CMATG2008Z04) 

主　　题：EnKF land data assimilation AMSR-E soil moisture FY2C geostationary satellite high-resolution precipitation surface incident solar radiation 

摘      要：Soil moisture plays an important role in land-atmosphere interactions. It is an important geophysical parameter in research on climate, hydrology, agriculture, and forestry. Soil moisture has important climatic effects by influencing ground evapotranspi ration, runoff, surface reflectivity, surface emissivity, surface sensible heat and latent heat flux. At the global scale, the extent of its influence on the atmosphere is second only to that of sea surface temperature. At the terrestrial scale, its influence is even greater than that of sea surface temperatures. This paper presents a China Land Soil Moisture Data Assimilation System (CLSMDAS) based on EnKF and land process models, and results of the application of this system in the China Land Soil Moisture Data Assimilation tests. CLSMDAS is comprised of the following components: 1) A land process mo del—Community Land Model Version 3.0 (CLM3.0)—developed by the US National Center for Atmospheric Research (NCAR); 2) Precipitation of atmospheric forcing data and surface-incident solar radiation data come from hourly outputs of the FY2 geostationary meteorological satellite; 3) EnKF (Ensemble Kalman Filter) land data assimilation method; and 4) Observa tion data including satellite-inverted soil moisture outputs of the AMSR-E satellite and soil moisture observation data. Results of soil moisture assimilation tests from June to September 2006 were analyzed with CLSMDAS. Both simulation and assimila tion results of the land model reflected reasonably the temporal-spatial distribution of soil moisture. The assimilated soil mois ture distribution matches very well with severe summer droughts in Chongqing and Sichuan Province in August 2006, the worst since the foundation of the People’s Republic of China in 1949. It also matches drought regions that occurred in eastern Hubei and southern Guangxi in September.