Статья

Parameterization of Vegetation Scattering Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands

Chang‐Hwan ParkNational Institute of Meteorological Sciences, Earth System Research Division, Korea Meteorological Administration (KMA), Jeju 63567, KoreaThomas JagdhuberMicrowaves and Radar Institute, German Aerospace Center (DLR), 82234 Weßling, GermanyAndreas CollianderJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USAJohan LeeNational Institute of Meteorological Sciences, Earth System Research Division, Korea Meteorological Administration (KMA), Jeju 63567, KoreaAaron BergDepartment of Geography, Environment and Geomatics, University of Guelph, Guelph, ON N1G 2W1, CanadaMichael H. CoshHydrology and Remote Sensing Laboratory, Agricultural Research Service (ARS), United States Department of Agriculture (USDA), Beltsville, MD 20705, USASeung-Bum KimJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USAYoonjae KimNational Institute of Meteorological Sciences, Earth System Research Division, Korea Meteorological Administration (KMA), Jeju 63567, KoreaVolker WulfmeyerInstitute of Physics and Meteorology, University of Hohenheim, 70599 Stuttgart, Germany

2020en

ABI

Аннотация

An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for surface and root-zone soil moisture, the latter is retrieved using data assimilation and model support. We found that the RTM based on the tau-omega (τ-ω) model can suffer from significant errors over croplands in the simulation of brightness temperature (Tb) (in average between −9.4K and +12.0K for single channel algorithm (SCA); −8K and +9.7K for dual-channel algorithm (DCA)) if the vegetation scattering albedo (omega) is set constant and temporal variations are not considered. In order to reduce this uncertainty, we propose a time-varying parameterization of omega for the widely established zeroth order radiative transfer τ-ω model. The main assumption is that omega can be expressed by a functional relationship between vegetation optical depth (tau) and the Green Vegetation Fraction (GVF). Assuming allometry in the tau-omega relationship, a power-law function was established and it is supported by correlating measurements of tau and GVF. With this relationship, both tau and omega increase during the development of vegetation. The application of the proposed time-varying vegetation scattering albedo results in a consistent improvement for the unbiased root mean square error of 16% for SCA and 15% for DCA. The reduction for positive and negative biases was 45% and 5% for SCA and 26% and 12% for DCA, respectively. This indicates that vegetation dynamics within croplands are better represented by a time-varying single scattering albedo. Based on these results, we anticipate that the time-varying omega within the tau-omega model will help to mitigate potential estimation errors in the current SMAP soil moisture products (SCA and DCA). Furthermore, the improved tau-omega model might serve as a more accurate observation operator for SMAP data assimilation in weather and climate prediction model.

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Идентификаторы

DOI: 10.3390/rs12182939

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar