Aviation Impact Forecasting based on time-lagged HRRR Ensembles

Storms represent a leading cause of air traffic impact in the national airspace. Forecasting hazardous weather, such as storms, several hours in advance is inherently uncertain, which makes strategic traffic flow planning more difficult. The numerical weather prediction community is leaning toward utilization of ensemble models to capture sensitivity of weather forecasts to initial and boundary conditions, and model physics. A time-lagged ensemble represents a viable approach, if computational resources don't allow for a true multi-model or initiation ensemble to be run.

We are exploring the use of hourly High-Resolution Rapid Refresh (HRRR) model forecasts of vertical integrated liquid (VIL) and echo top (ET) information to create a time-lagged ensemble of aviation impact. In particular, the VIL and ET information is translated into a Weather Avoidance Field (WAF) that can be interpreted in terms of a capacity reduction. The WAF ensemble is used to create a probabilistic aviation impact forecast. Initial results of these probabilistic impact forecasts will be presented.