Evaluation of Enroute Convective Weather Avoidance Models Based on Planned and Observed Flight*

The effective management of convective weather in congested airspace requires decision support tools that can translate weather information available to air traffic managers into anticipated impact on air traffic operations. The Convective Weather Avoidance Model (CWAM) has been under development at Lincoln Lab under sponsorship of NASA to develop a correlation between pilot behavior and observable weather parameters (Chan et al, 2007). To date, the observable weather parameters have been derived primarily from the Corridor Integrated Weather System (CIWS) (Klingle-Wilson and Evans, 2005 and Evans and Ducot, 2006) high resolution Vertically Integrated Liquid (VIL) precipitation map and the CIWS Echo Top product. Deviations have been identified using a database of planned and actual en route flight trajectories based on data from the Enhanced Traffic management System (ETMS). CWAM has used a simple model that is based upon finding weather encounters and then comparing the distance between the planned and actual flight trajectories to define pilot deviations. Due to a large number of false deviations from this model, a significant amount of hand editing was required to use the database. This paper will present two areas of work to improve the performance and usefulness of the enroute convective weather avoidance models. First, an improved automated algorithm to detect weather-related deviations that significantly reduces the percentage of false deviation detections will be presented. This new model includes additional information on each deviation, including the location where the decision was