Development of a Land Data Assimilation System for Assimilating AMSR-E Brightness Temperature Observations

被引：0

作者：

Li, Xin ^{[1
]}

Koike, Toshio ^{[2
]}

Graf, Tobias ^{[2
]}

Yang, Kun ^{[2
]}

Hirai, Masayuki ^{[3
]}

机构：

[1] Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China

[2] Univ Tokyo, Dept Civil Engn, Tokyo 1138654, Japan

[3] Numer Predi Div Japan Meteorol agency, Tokyo, Japan

来源：

2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 | 2006年

关键词：

land data assimilation system; soil moisture; AMSR-E; land surface modeling;

D O I：

10.1109/IGARSS.2006.752

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

A land data assimilation system (LDAS) which is capable of assimilating satellite-borne passive microwave remote sensing observations into land surface models is developed. The model operator used in the system is the JMA (Japan Meteorological Administration) new SiB. The observation operators are radiative transfer models of land surface states such as snow and soil. The data assimilation methods employed is the ensemble Kalman filter, which is a Monte Carlo based sequential filter method. The system was tested using observations collected at a semi-arid region site, CEOP Mongolia reference. The results showed that the system can estimate land surface states more reasonable than uncontrolled modeling by merging the brightness temperature observations into land surface dynamics.

引用

页码：2927 / +

页数：2

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