气候变化领域集成服务门户(CCPortal): Optimal Exploitation of AMSR-E Signals for Improving Soil Moisture Estimation Through Land Data Assimilation

CCPortal

DOI	10.1109/TGRS.2012.2198483
	Optimal Exploitation of AMSR-E Signals for Improving Soil Moisture Estimation Through Land Data Assimilation
	Zhao, Long; Yang, Kun; Qin, Jun; Chen, Yingying
通讯作者	Zhao, L (通讯作者)
发表日期	2013
ISSN	0196-2892
EISSN	1558-0644
起始页码	399
结束页码	410
卷号	51 期号:1
英文摘要	Regional soil moisture can be estimated by assimilating satellite microwave brightness temperature into a land surface model (LSM). This paper explores how to improve soil moisture estimation based on sensitivity analysis when assimilating Advanced Microwave Scanning Radiometer for the Earth Observing System brightness temperatures. By assimilating a lower and a higher frequency combination, the land data assimilation system (LDAS) used in this paper estimates first model parameters in a calibration pass and then estimates soil moisture in an assimilation pass. The ground truth of soil moisture was collected at a soil moisture network deployed in a semiarid area of Mongolia. Analyzed are the effects of assimilating different polarizations, frequencies, and satellite overpass times on the accuracy of the estimated soil moisture. The results indicate that assimilating the horizontal polarization signal underestimates soil moisture and assimilating the daytime signal overestimates soil moisture. The former is due to improper parameter estimation perhaps caused by high sensitivity of the horizontal polarization to land surface heterogeneity, and the latter is due to the effective soil temperature for microwave emission in the daytime being close to the one at a soil depth of several centimeters but not to the surface skin temperature simulated in the LSM. Therefore, assimilating the nighttime vertical polarizations in the LDAS is recommended. A further analysis shows that assimilating different frequency combinations produces different soil moisture estimates, and none is always superior to the others, because different frequency signals may be contaminated by varying clouds and/or water vapor with different degrees. Thus, an ensemble estimation based on frequency combinations was proposed to filter off, to some extent, the stochastic frequency-dependent biases. The ensemble estimation performs more robust when driven by different forcing data.
关键词	SURFACE PARAMETERIZATION SIB2 MICROWAVE EMISSION ATMOSPHERIC GCMS KALMAN FILTER MODEL RETRIEVAL SATELLITE SYSTEM SMOS POLARIZATION
英文关键词	Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E); frequency-based ensemble; land data assimilation system (LDAS); soil moisture
语种	英语
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000314021300004
来源期刊	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
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/258107
推荐引用方式 GB/T 7714	Zhao, Long,Yang, Kun,Qin, Jun,et al. Optimal Exploitation of AMSR-E Signals for Improving Soil Moisture Estimation Through Land Data Assimilation[J]. 中国科学院青藏高原研究所,2013,51(1).
APA	Zhao, Long,Yang, Kun,Qin, Jun,&Chen, Yingying.(2013).Optimal Exploitation of AMSR-E Signals for Improving Soil Moisture Estimation Through Land Data Assimilation.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,51(1).
MLA	Zhao, Long,et al."Optimal Exploitation of AMSR-E Signals for Improving Soil Moisture Estimation Through Land Data Assimilation".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 51.1(2013).