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Improving Soil Moisture Estimation with a Dual Ensemble Kalman Smoother by Jointly Assimilating AMSR-E Brightness Temperature and MODIS LST
2017
Remote Sensing
Uncertainties in model parameters can easily result in systematic differences between model states and observations, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this research, a soil moisture assimilation scheme is developed to jointly assimilate AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System) brightness temperature (TB) and MODIS (Moderate Resolution Imaging Spectroradiometer) Land Surface Temperature (LST)
doi:10.3390/rs9030273
fatcat:sfw3z2fdunct7eftpw3oygf6j4