An Intercomparison of Noah Model Skills With Benefits of Assimilating SMOPS Blended and Individual Soil Moisture Retrievals

Abstract

Abstract Soil moisture (SM) data from Soil Moisture Operational Product System (SMOPS) have been available and used by users since 2013, and the latest version (3.0) has been operationally released since 2017. The version 3.0 provides a combination of currently all available daily global microwave SM retrievals including observations of ASCATA, ASCATB, SMAP, SMOS, and AMSR2 from 1 April 2015 to present. This study intercompares Noah model skills with benefits of assimilating the SMOPS blended (hereafter, SMOPS) and the five individual satellite SM retrievals. Results show that SMOPS SM product presents a significant advantage in data availability in comparison with the individual SM retrievals. Significant differences in data availability, climatology, and dynamic range of SM values between the bias‐corrected SMOPS and individual SM data lead to remarkable distinctions in Noah model SM simulations. Significant improvements of assimilating individual and blended satellite SM retrievals on model SM simulations versus the open loop in both surface and root zone soil layers are evident with reducing the Soil Climate Analysis Network measurements‐based root mean square errors and raising the correlations with respect to the enhanced vegetation index. Compared to the individual SM assimilations, model SM estimations with benefits of assimilating the SMOPS data provide the more remarkable improvements in surface soil layer.