An Improvement of the Radiative Transfer Model Component of a Land Data Assimilation System and Its Validation on Different Land Characteristics
1
Ministry of Education Key Laboratory for Earth System Modeling, and Center for Earth System Science, Tsinghua University, Beijing 100084, China
2
Joint Center for Global Change Studies, Beijing 100875, China
3
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
4
The Department of Civil Engineering, the University of Tokyo, Tokyo 113-8656, Japan
5
Department of Geological Sciences, The John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, TX 78712, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Yuei-An Liou, Clement Atzberger and Prasad S. Thenkabail
Remote Sens. 2015, 7(5), 6358-6379; https://doi.org/10.3390/rs70506358
Received: 20 March 2015 / Accepted: 18 May 2015 / Published: 21 May 2015
(This article belongs to the Special Issue Earth Observations for the Sustainable Development)
The paper reports the recent progress in the radiative transfer model (RTM) development, which serves as the observation operator of a Land Data Assimilation System (LDAS), and its validation at two Planetary Boundary Layer (PBL) stations with different weather and land cover conditions: Wenjiang station of humid and cropped field and Gaize station of arid and bare soil field. In situ observed micrometeorological data were used as the driven data of LDAS, in which AMSR-E brightness temperatures (TB) were assimilated into a land surface model (LSM). Near surface soil moisture content output from LDAS, together with the one simulated by a LSM with default parameters, were compared to the in-situ soil moisture observation. The comparison results successfully validated the capability of LDAS with new RTM to simulate near surface soil moisture at various environments, supporting that LDAS can generally simulate soil moisture with a reasonable accuracy for both humid vegetated fields and arid bare soil fields while the LSM overestimates near surface soil moisture for humid vegetated fields and underestimates soil moisture for arid bare soil fields.
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MDPI and ACS Style
Lu, H.; Yang, K.; Koike, T.; Zhao, L.; Qin, J. An Improvement of the Radiative Transfer Model Component of a Land Data Assimilation System and Its Validation on Different Land Characteristics. Remote Sens. 2015, 7, 6358-6379.
AMA Style
Lu H, Yang K, Koike T, Zhao L, Qin J. An Improvement of the Radiative Transfer Model Component of a Land Data Assimilation System and Its Validation on Different Land Characteristics. Remote Sensing. 2015; 7(5):6358-6379.
Chicago/Turabian StyleLu, Hui; Yang, Kun; Koike, Toshio; Zhao, Long; Qin, Jun. 2015. "An Improvement of the Radiative Transfer Model Component of a Land Data Assimilation System and Its Validation on Different Land Characteristics" Remote Sens. 7, no. 5: 6358-6379.
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