气候变化领域集成服务门户(CCPortal): A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature

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DOI	10.1029/2008JD011600
	A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature
	Tian, Xiangjun; Xie, Zhenghui; Dai, Aiguo; Shi, Chunxiang; Jia, Binghao; Chen, Feng; Yang, Kun
通讯作者	Tian, XJ (通讯作者)
发表日期	2009
ISSN	2169-897X
EISSN	2169-8996
卷号	114
英文摘要	To overcome the difficulties in determining the optimal parameters needed for a radiative transfer model (RTM), which acts as the observational operator in a land data assimilation system, we have designed a dual-pass assimilation (DP-En4DVar) framework to optimize the model state (volumetric soil moisture content) and model parameters simultaneously using the gridded Advanced Microwave Scanning Radiometer-EOS (AMSR-E) satellite brightness temperature data. This algorithm embeds a dual-pass (the state assimilation pass and the parameter optimization pass) optimization technique based on an ensemble-based four-dimensional variational assimilation method and a shuffled complex evolution approach (SCE-UA). The SCE-UA method optimizes the parameters using observational information, thereby leading to improved simulations. The RTM is used to estimate brightness temperature from surface temperature and soil moisture. This algorithm is implemented differently in two phases: the parameter calibration phase and the pure assimilation phase. Both passes are applied in each assimilation time window during the parameter calibration phase. However, only the state assimilation pass is used in the pure assimilation phase after the parameters are determined during the parameter calibration phase. Several experiments conducted using this framework coupled partially with a land surface model (the NCAR CLM3) show that volumetric soil moisture content can be significantly improved to be comparable with in situ observations by assimilating only daily satellite brightness temperature. Furthermore, the improvement in surface soil moisture also propagates to lower layers where no observations are available.
关键词	LAND-SURFACE MODEL SCREEN-LEVEL PARAMETERS RETRIEVAL EMISSION FIELD
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:000269244800001
来源期刊	JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/257683
推荐引用方式 GB/T 7714	Tian, Xiangjun,Xie, Zhenghui,Dai, Aiguo,et al. A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature[J]. 中国科学院青藏高原研究所,2009,114.
APA	Tian, Xiangjun.,Xie, Zhenghui.,Dai, Aiguo.,Shi, Chunxiang.,Jia, Binghao.,...&Yang, Kun.(2009).A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,114.
MLA	Tian, Xiangjun,et al."A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 114(2009).