The NOAA Aviation Weather Testbed (AWT) is post-processing the NCEP Short Range Ensemble Forecast (SREF) system to evaluate decision support guidance that will assist meteorologists in understanding potential weather impacts on the National Airspace System (NAS). The post-processed predictors from the individual members of the SREF include parameters relevant to aviation such as ceiling, visibility, precipitation, wind, and thunderstorms. These predictors are interpolated to each of the FAA's CORE-30 airports (with the exception of Honolulu). Historical aircraft position data are then used as a first-order proxy to the weather impact at the airports. The interpolated SREF guidance provides the independent predictor variables to a principal component regression (PCR) that retains the most significant independent variables, which are determined automatically over the training period. The final result is a SREF-based hourly probabilistic forecast of weather impact at the CORE-30 airports. This paper describes the SREF predictors, the PCR methodology, and an example of the output. The technique is under development but available verification will be shown. Most importantly, the applicability of the output to the aviation meteorologist communicating weather information to air traffic or industry planners is demonstrated.