Nearly every day during the summer, convective weather causes substantial delays to aviation operations. While the prediction of convective storms is improving, a great deal of uncertainty (which increases with forecast lead time) remains in terms of predicting the exact location, timing and characteristics of storms. Therefore, daily strategic planning of air routes and traffic flows across the United States requires probabilistic information about the range of possible convective weather outcomes and associated aviation impacts.

During the summer 2011, the Aviation Weather Center (AWC) hosted the Aviation Weather Testbed 2011 Summer Experiment to explore emerging forecast products of convective weather and resulting aviation impacts. Two ensemble-based probabilistic capacity reduction (CR) forecasts were explored as part of a suite of products. One set of CR forecasts was calculated using data from a true multi-physics, multi-initial conditions ensemble supplied by the Air Force Weather Agency, while the other set of CR forecast was calculated using a time-lagged ensemble of the CoSPA forecasts which were developed through a tri-lab effort between MIT/LL, NCAR/RAL and ESRL/GSD. Both ensembles predicted storm intensity (i.e., vertically integrated liquid) and echo tops that were combined and translated into pilot deviation likelihood or Weather Avoidance Field (WAF) using an algorithm developed at MIT/LL. Moreover, the resulting WAFs were analyzed in terms of how much of the potentially available capacity was reduced due to the presence of the convective storm hazards utilizing Metron's MinCut approach. The final product sent to AWC was a CONUS scale forecast of capacity reduction potential for 3 flight levels. During the Aviation Weather Testbed, forecasters and air traffic flow specialists utilized these capacity reduction potential forecasts as first guess in developing their aviation impacts forecasts for the Golden Triangle (vertices at Chicago, New York and Atlanta).

The presentation will discuss the two ensemble-based probabilistic weather impact prediction techniques and provide a quantitative assessment of their performance.

“This research is in response to requirements and funding by the Federal Aviation Administration (FAA). The views expressed are those of the authors and do not necessarily represent the official policy or position of the FAA.”