Identifying Smos and Smap Pixels that Exhibit Distinct Roughness-Vegetation Patterns in Level 2 Optical Thickness Retrievals

摘要

The Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) Level 2 Soil Moisture products both exhibit a dry bias over agricultural regions. In regions such as the U.S. Corn Belt, where vegetation water content is high during the growing season and near zero in the winter' the year can be split into periods where retrieved optical thickness is either representative of vegetation water content or surface roughness. We hypothesize that allowing roughness to vary with retrieved optical thickness outside of the growing season will improve the dry bias in the U.S. Corn Belt. Pixels that have a distinct boundary between rough soil and vegetated conditions need to be identified to determine where this modified retrieval process could be useful. SMOS auxiliary land surface fractions are used as a filter for forest, urban, and open water before visually inspecting timeseries of optical thickness for roughness-vegetation patterns.