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Abstract
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.
Highlights
Surface soil moisture, which links the land surface and the atmosphere by influencing the exchange of energy and mass between the two [1], is one of the most important variables in much of the Earth system research, such as hydro-meteorological studies, global scale environmental processes monitoring and climate change studies [2,3].Traditionally, in-situ near surface soil moisture is measured at points, by using conventional can-sampling method and/or using newly developed techniques such as Time Domain Reflectometry (TDR) and neutron probe
The in situ observed meteorological data was used to drive the Land Data Assimilation System (LDAS)-UT, while AMSR-E brightness data were merged into the system to improve the soil moisture estimation
Since there were no vegetation observations for both sites, vegetation information which was needed in SiB2 and radiative transfer model (RTM) were derived from the MODIS (Moderate Resolution Imaging Spectroradiometer)
Summary
In-situ near surface soil moisture is measured at points, by using conventional can-sampling method and/or using newly developed techniques such as Time Domain Reflectometry (TDR) and neutron probe. Through these methods, very accurate soil moisture profiles can be observed. Satellite passive microwave remote sensing makes it possible to measure surface soil moisture at the global scale by direct measurement of brightness temperature which is strongly related to the liquid moisture content [4,5,6,7]. The near surface soil moisture observed by satellite is discontinuous in time
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