Evaluation of Radiative Transfer Models With Clouds

Data from hyperspectral infrared sounders are routinely ingested worldwide by the National Weather Centers. The cloud-free fraction of this data is used for initializing forecasts which include temperature, water vapor, water cloud, and ice cloud profiles on a global grid. Although the data from these sounders are sensitive to the vertical distribution of ice and liquid water in clouds, this information is not fully utilized. In the future, this information could be used for validating clouds in National Weather Center models and for initializing forecasts. We evaluate how well the calculated radiances from hyperspectral Radiative Transfer Models (RTMs) compare to cloudy radiances observed by AIRS and to one another. Vertical profiles of the clouds, temperature, and water vapor from the European Center for Medium-Range Weather Forecasting were used as input for the RTMs. For nonfrozen ocean day and night data, the histograms derived from the calculations by several RTMs at 900cm(-1) have a better than 0.95 correlation with the histogram derived from the AIRS observations, with a bias relative to AIRS of typically less than 2K. Differences in the cloud physics and cloud overlap assumptions result in little bias between the RTMs, but the standard deviation of the differences ranges from 6 to 12K. Results at 2,616cm(-1) at night are reasonably consistent with results at 900cm(-1). Except for RTMs which use full scattering calculations, the bias and histogram correlations at 2,616cm(-1) are inferior to those at 900cm(-1) for daytime calculations.