Assimilation of Geostationary Satellite Land Surface Skin Temperature Observations into the GEOS-5 Global Atmospheric Modeling and Assimilation System

The land surface skin temperature is central to the surface energy, water, and radiation balances. In an atmospheric model, improved skin temperature states are expected to yield improved temperature and humidity profiles. In an atmospheric data assimilation system, improved skin temperature states are also expected to enhance the assimilation of atmospheric radiances from surface-sensitive channels. In this work, skin temperature estimates retrieved from geostationary Earth orbiting satellite observations every three hours are assimilated into the Goddard Earth Observing System Model, version 5 (GEOS-5) atmospheric modeling and assimilation system over North America, using an ensemble Kalman filter-based Land Data Assimilation System (LDAS). A dynamic observation bias correction scheme has been implemented within the LDAS to address the biases between the modeled and observed skin temperature estimates. The impact of the assimilation is evaluated by examining the impact on the modeled skin temperature, land surface fluxes, and low-level temperature and humidity.