Correcting the AMSR-E NASA Soil Moisture for the Effects of Vegetation Transmittance and Emission

Abstract

The Advanced Microwave Scanning Radiometer-Earth Observing System/National Aeronautics and Space Administration (AMSR-E/NASA) daily global soil moisture (SM) product (2002–2011, 25-km resolution) has been widely used but exhibits limited sensitivity to intra-annual and interannual variability in many regions. This limitation is mainly attributed to inaccurate parameter values (A₀ and A₁), which account for vegetation transmittance and emission in the AMSR-E/NASA SM retrieval algorithm. To address this issue, we recalibrated A₀ and A₁ using in situ SM measurements from 13 observation networks (192 sites) and established their empirical relationships with fractional vegetation cover (FVC). Four dominant land cover types (i.e., bare soil, grassland, cropland, and forest) were considered due to their global representativeness and extensive coverage with in situ SM measurements. Based on these relationships, we generated global maps of A₀ and A₁ and produced an improved Global Daily AMSR-E SM dataset (GD_AMSR-E_SM; 2002–2011, 25-km resolution) using the Global Land Surface Satellite (GLASS) FVC dataset and AMSR-E observations. Validation against in situ SM measurements within six independent networks shows that the GD_AMSR-E_SM dataset achieves greater consistency with in situ SM measurements, with mean absolute error (MAE) and root-mean-square error (RMSE) values of 0.026 and 0.032 cm³/cm³, respectively. This represents average reductions of 20% and 26% compared with the AMSR-E/NASA, AMSR-E/Japan Aerospace Exploration Agency (JAXA), and AMSR-E/Land Parameter Retrieval Model (LPRM) SM products. The enhanced algorithm improves the accuracy and reliability of AMSR-E observations for long-term global SM monitoring.