Improving ASCAT Soil Moisture Retrievals With an Enhanced Spatially Variable Vegetation Parameterization

This study investigates the performance of TU Wien soil moisture retrieval (TUW-SMR) algorithm by adapting strength vegetation correction. The semiempirical change detection method TUW-SMR exploits multiangle backscatter observations from spaceborne fan-beam scatterometer systems in order to derive surface information expressed degree saturation. parameterization is controlled dry and wet crossover angles that are used determine reference. Backscatter Advanced Scatterometer (ASCAT) produce four data sets based on different describing: 1) a static, respectively, no correction; 2) currently seasonal 3) stronger 4) spatially variable correction with over vegetated areas bare land. All ASCAT evaluated against estimates GLDAS-2.1 Noah land model European Space Agency (ESA) climate initiative (CCI) Passive v04.5 product using triple collocation traditional correlation analysis. results show overall improves both more densely areas, e.g., large parts North America Europe, sparsely vegetated, Western Africa. Nonetheless, experiment also provides insight into challenging conditions where fails take all relevant processes account, wetlands soils subsurface scattering.