Assimilation of Remotely Sensed Near-Surface Soil Moisture into the GEOS-5 Atmospheric Modeling and Assimilation System

Root-zone soil moisture can control the partition of incoming radiation into latent and sensible heat fluxes, and has been shown to affect the evolution of the atmospheric boundary layer. In an atmospheric model, improving modeled root-zone soil moisture states should then in theory lead to improved atmospheric temperature and humidity profiles. It has previously been shown that modeled root-zone soil moisture is significantly improved by assimilating remotely sensed near-surface soil moisture into the NASA Global Modeling and Assimilation Office's offline Land Data Assimilation System (GMAO LDAS). In this study, near-surface soil moisture retrieved from the passive microwave Soil Moisture Ocean Salinity (SMOS) and the active microwave Advanced Scatterometer (ASCAT) are assimilated into GMAO's Goddard Earth Observing System Model, version 5 (GEOS-5) atmospheric modeling and assimilation system over a one year period. The benefit gained from the assimilation is then tested by comparing the modeled land surface fluxes, low-level temperature and humidity, and precipitation forecasts to independent observations. In the routine GEOS-5 system, the land surface does not directly experience assimilation updates, however most other institutes assimilating soil moisture into atmospheric systems are also updating their land surface states by assimilating low-level atmospheric temperature and humidity observations. Hence, this study is expected to provide a clearer view of the impact of assimilating near-surface soil moisture observations in isolation from other variables.