88th Annual Meeting (20-24 January 2008)

Monday, 21 January 2008
Modeling convective weather avoidance in enroute airspace
Exhibit Hall B (Ernest N. Morial Convention Center)
Rich DeLaura, MIT Lincoln Laboratory, Lexington, MA; and M. Robinson, M. Pawlak, and J. E. Evans
Poster PDF (486.2 kB)
It is generally agreed that effective management of convective weather in congested airspace requires decision support tools that translate the weather products and forecasts into forecasts of ATC impacts and then use those ATC impact forecasts to suggest air traffic management strategies. A critical first step in the translation process is a validated model for airspace that pilots will seek to avoid.

At the last Conference on Aviation, Range and Aerospace Meteorology, we reported on an initial Convective Weather Avoidance Model (CWAM1). The CWAM1 outputs are three dimensional deterministic and probabilistic weather avoidance fields (WAFs). CWAM1 used Corridor Integrated Weather System (CIWS) VIL and echo top fields and National Lightning Detection Network (NLDN) data to predict aircraft deviations and penetration. CWAM1 was developed using more than 500 aircraft-convective weather encounters in the Indianapolis en route center (ZID) airspace. CWAM1 gave the greatest weight to the difference between flight altitude and the 18 dbZ radar echo top with precipitation intensity playing a secondary role. WAF validation testing showed that CWAM1 was generally reliable statistically; however, there were a number of meteorological conditions where CWAM1 deterministic fields were in error for a significant number of consecutive aircraft passing through a given area of airspace. Additionally, the probability distribution of deviations vs penetrations varied relatively slowly as a function of predictor parameters (e.g., aircraft altitude – echo tops altitude)

This paper presents a new model (CWAM2), based on the analysis of trajectories from several air traffic control centers (Indianapolis, Cleveland and Washington, DC) and an expanded set of meteorological deviation predictors. Additional weather factors that are considered include upper level reflectivity and the height of the VIL centroid (derived from the NSSL 3D reflectivity mosaic), vertical and horizontal storm growth and the spatial variation in VIL and echo top fields.

This work was sponsored by the National Aeronautics and Space Administration (NASA) under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the U.S. Government.

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