Improved surface soil moisture anomalies from Fengyun-3B over the Jiangxi province of the People's Republic of China

This study develops a data-driven modification scheme for a commonly used soil moisture retrieval algorithm by introducing a vegetation density-related single scattering albedo based on in situ and Fengyun-3B passive microwave observations. The Jiangxi province in China's mainland is one of the most challenging regions for soil moisture retrievals due to its complex topography, open water, and vegetation conditions. However, it has a very dense in situ soil moisture observation network which makes it a suitable test-bed to examine the performance of the modification scheme. The development of this new scheme consists of two steps. In a first step, the model is initialized using the most recently developed algorithm configuration. In the second step, these initial outcomes are used as input to determine the vegetation density related single scattering albedo which is solely based on observational data and used as the final algorithm configuration over our study area. We start by comparing the two most recent algorithm configurations against the in situ soil moisture network and demonstrate an overall improvement in terms of correlations coefficient for the most recent version. Then, the observational data- driven modification scheme was proposed and evaluated against the in situ soil moisture network with further improvements after its implementation. We furthermore applied the vegetation density-based scattering albedo in soil moisture retrievals over all grid cells in Jiangxi, and found that soil moisture data with the newly developed configuration significantly improved (up to 30%) compared to the preceding algorithm configurations. The two existing algorithm configurations were also evaluated over all grid cells and all results indicate consistent improvements between the successive algorithm versions.