The Gastropod Fast Radiative Transfer Model for Advanced Infrared Sounders and Characterization of Its Errors for Radiance Assimilation

Abstract

Principal aspects of the development of Gastropod, a fixed-pressure-grid fast radiative transfer model for the Atmospheric Infrared Sounder (AIRS), are described. Performance of the forward and gradient operators is characterized, and the impact of radiative transfer model errors on retrieval accuracy is quantified in a minimum-variance linear retrieval framework. The model error characteristics do not compromise the information content of channel subsets appropriate for use in operational data assimilation significantly, and retrieval accuracy is robust in realistic suboptimal retrieval scenarios. The fixed-pressure-grid regression model is, therefore, adequate for current data assimilation requirements. Errors in modeled water vapor line absorption do, however, limit the accuracy of retrievals using the full AIRS channel set, and accurate description of forward-model error correlations is essential for retrieval accuracy. Thus, despite recent advances, fixed-pressure-grid models have yet to demonstrate the required degree of accuracy in modeling water vapor line absorption. More accurate models will be required to exploit advanced sounder data to their full potential.