In recent years, proxy top of atmosphere radiance datasets derived from numerical weather prediction model output have been extensively used to demonstrate the advanced measurement capabilities of the Advanced Baseline Imager (ABI) to be launched onboard the GOES-R satellite in 2015. These datasets are an attractive alternative to those derived from existing air- and ground-based instruments since they can easily be configured to represent the spatial, temporal, and spectral resolutions of the ABI sensor. As part of this effort, researchers at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) have used output from high-resolution Weather Research and Forecasting model simulations to generate physically realistic synthetic ABI radiance datasets covering large geographic areas. Validation results along with an overview of the proxy datasets and their use by various GOES-R projects will be shown.

In the second half of the presentation, results from a regional-scale Observation System Simulation Experiment that was used to examine how changes in the horizontal covariance localization radius employed during the assimilation of infrared brightness temperature observations impacts the accuracy of atmospheric analyses and short-range model forecasts will be shown. Overall, the results indicate that although assimilation of infrared observations consistently improves the cloud analysis regardless of the length of the localization radius, it may be necessary to use a smaller radius to also improve the accuracy of the moisture and thermodynamic fields.