Abstract:
The land surface skin temperature is a central parameter in the energy, radiation, and water budgets at the land surface. Improving the skin temperature states in an atmospheric modelling and assimilation system is expected to directly improve forecasts of the temperature and humidity profiles, while also having the potential to enhance the assimilation of radiance data from surface-sensitive channels. Skin temperature estimates with high temporal frequency and extensive spatial coverage can be obtained in near-real time from geostationary Earth orbiting satellites. A global 0.3125x0.25 degree skin temperature product, with an estimated error of less than 2K over land, is available 3-hourly from the NASA Langley Research Center. These skin temperature estimates are assimilated into the Goddard Earth Observing System, version 5 (GEOS-5) atmospheric modelling and assimilation system, using an offline ensemble Kalman filter-based Land Data Assimilation System (LDAS). The LDAS is coupled to GEOS-5 in that it receives atmospheric forcing and returns land surface analysis updates to the atmospheric model over each assimilation cycle. The impact of assimilating the NASA Langley land surface skin temperature data from June to August 2012 is established by examining the skin temperature and land surface flux forecasts, as well as the subsequent changes in the low-level temperature and humidity forecast skill.