Convective weather and strong storms are responsible for more than 70 percent of delays and cancellations experienced by airlines operating within the National Airspace System (NAS). Accurate forecasting of the location and timing of convective weather is difficult for numerical models to predict. Convective storm initiation can be observed in satellite imagery before it is detected by operational weather radar. Geostationary satellite data can provide a nowcast of the location and timing of future thunderstorm developments.


The FAA AWRP has employed the Convective Autonowcaster decision support system (DSS) at major airports to assist dispatchers and air traffic controllers to mitigate the effects of convective weather. Developed jointly with UW CIMSS and UAH, ASAP convective weather algorithms combine an enhanced convective cloud mask with corresponding atmospheric motion vectors to monitor the changes in cloud properties producing 30 to 45 minute forecasts of convective weather. ASAP algorithms have been incorporated into the Autonowcaster DSS to be evaluated in benchmark studies in Dallas-Fort Worth and Chicago O’Hare airports as well as into Advanced Weather Interactive Processing System (AWIPS) terminals operated by NOAA.

Efforts to incorporate these algorithms into the NextGen Network Enabled Weather System’s (NNEW) Consolidated Storm Prediction Algorithm (CoSPA) are now underway. This work is being lead by Dr. John Mecikalski, who developed the ASAP convective weather applications at the University of Alabama, Huntsville, and the University of Wisconsin CIMSS, and by Dr. Marilyn Wolfson of MIT Lincoln Laboratory, who directs the FAA AWRP’s Convective Product Development Team.