Abstract
In this paper, we implemented the in-situ observation of surface soil moisture (SSM), vegetation water content (VWC), and microwave brightness temperatures. By analyzing this in-situ observation dataset and the numerical simulation, we investigated the source of the uncertainty of the current algorithms for Advanced Microwave Scanning Radiometer for Earth observation system (AMSR-E) and AMSR2 to retrieve SSM and vegetation dynamics. Our findings are: (1) the microwave radiative transfer at C-band and X-band is not strongly affected by the shape of vegetation and the existing algorithm can be applied to a wide variety of plant types; (2) the diversity of surface soil roughness significantly affects the indices which are used by the current algorithms and addressing the uncertainty of surface soil roughness is necessary to improve the retrieval algorithms; (3) At C-band, SSM of the homogeneous vegetated land surfaces can be detected only when their VWC is less than approximately 0.25 (kg/m2); (4) the state-of-the-art Radiative Transfer Model (RTM) can predict our observed dataset although we have some biases in simulating brightness temperatures at a higher frequency. The new in-situ observation dataset produced by this study can be the guideline for both developers and users of passive microwave land observations to consider the uncertainties of their products.
Highlights
Passive microwave satellite observations have been used extensively to monitor global surface soil moisture (SSM) and vegetation dynamics, and contributed to deepen the understandings of hydrological and biogeochemical cycles
Liu et al [3] developed the long-term global aboveground biomass carbon dataset from vegetation optical depth (VOD), which is correlated to vegetation water content (VWC), from Special Sensor Microwave Imager (SSM/I), AMSR-E, FengYun-3B Microwave Radiometer Imager (MWRI) and Windsat
We provided the new in-situ observation dataset which is useful to evaluate the capability and limitation of the SSM and VWC retrieval algorithms based on microwave radiometry
Summary
Passive microwave satellite observations have been used extensively to monitor global surface soil moisture (SSM) and vegetation dynamics, and contributed to deepen the understandings of hydrological and biogeochemical cycles. Anderson et al [1] developed the drought monitor in East Africa using the soil moisture product from Advanced Microwave. Liu et al [3] developed the long-term global aboveground biomass carbon dataset from vegetation optical depth (VOD), which is correlated to vegetation water content (VWC), from Special Sensor Microwave Imager (SSM/I), AMSR-E, FengYun-3B Microwave Radiometer Imager (MWRI) and Windsat. Datasets of passive microwave satellite observations have been assimilated to land surface models in order to improve their performance of simulating water and energy fluxes (e.g., [5,6,7,8,9,10,11])
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