Atmospheric profile retrieval with AIRS data and validation at the ARM CART site

Abstract

The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder (AIRS) radiances is presented. The retrieval algorithm is applied to AIRS clearsky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations (RAOBs) comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement (ARM) Program Cloud And Radiation Testbed (CART) in Oklahoma, U. S. A. Comparisons show that the physicallybased AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error (RMSE) of 1 K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite (GOES) sounder when comparing AIRS sounding retrievals with the operational GOES sounding products.