Temperature and moisture profiles can be retrieved from the Atmospheric InfraRed Sounder (AIRS) with accuracy approaching that of radiosonde measurements. They provide key atmospheric conditions for data assimilation to improve numerical weather prediction, especially valuable over areas where conventional data are sparse, such as oceans. This study uses the Weather Research and Forecasting (WRF) model to investigate the effects of assimilating these profiles on the forecast of Hurricane Ike over the Western Atlantic Ocean in 2008. Observational data, including conventional measurements from radiosondes, aircrafts, surface stations, ocean buoys and ships, with or without the AIRS single field-of-view (SFOV) temperature and moisture profiles under clear sky conditions, are incorporated into the WRF initialization using the three-dimensional variation (3DVAR) data assimilation method. Sensitivity experiments show that inclusion of the AIRS retrievals result in a notable increase of forecast skill for both hurricane track and intensity.

Key Words: AIRS, Assimilation, Temperature and moisture profiles, Hurricane forecast, WRF3DVAR