The Aviation Weather Forecasting Component of the 2010 NOAA Hazardous Weather Testbed Spring Experiment

The Aviation Weather Center (AWC) partnered with the NOAA Hazardous Weather Testbed (HWT) to evaluate emerging aviation weather forecast methodologies during the 2010 Spring Experiment, conducted during May 17 through June 18 at the HWT. The experiment consisted of using several high-resolution ensemble and deterministic models to create innovative, next-generation aviation weather forecasts to test enhanced decision support for air traffic management and the FAA's Next Generation Air Transportation System (NextGen). Model data generated at high resolution (1 to 4 km) by the National Severe Storms Laboratory (NSSL), the Center for Analysis and Prediction of Storms (CAPS), NOAA's Environmental Modeling Center (EMC), and the National Center for Atmospheric Research (NCAR) all contributed to the data analysis used to create forecasts each day of the experiment. Specifically, the 26-member CAPS Storm Scale Ensemble Forecast (SSEF) allowed participants gain experience with a high-resolution, convection-allowing ensemble forecast system that created probabilistic output fields.

This paper will describe the results of the aviation weather forecasting component of the experiment. Each day, several forecasts were created along with subjective evaluations of the previous day's forecasts and model forecast data. The first set of forecasts, issued in the morning, included delineating areas of a slight, moderate, or high probability of radar echo tops exceeding 25,000 ft valid at 23Z and radar reflectivity exceeding 40 dBZ valid at 21Z, 23Z, and 01Z; these forecasts were updated in the afternoon with new model information. Additionally, a forecast valid at 18-00Z the next day for radar reflectivity exceeding 40 dBZ was issued during the afternoon. A number of output fields were examined for each forecast, especially the mean, maximum, minimum, probability exceedance, and probability matched mean of radar echo top and radar reflectivity. The forecasts were subjectively analyzed and collected via a web-based survey system, and example forecasts and survey results, as well as future challenges for aviation weather forecasting, will be discussed.