An Exploratory Study of Modeling Enroute Pilot Convective Storm Flight Deviation Behavior

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Thursday, 2 February 2006
An Exploratory Study of Modeling Enroute Pilot Convective Storm Flight Deviation Behavior
Exhibit Hall A2 (Georgia World Congress Center)
Rich DeLaura, MIT Lincoln Laboratory, Lexington, MA; and J. Evans

Poster PDF (967.7 kB)

Aviation weather systems such as the Corridor Integrated Weather System (CIWS) provide weather products and forecasts that aid en route traffic managers in making tactical routing decisions in convective weather. The optimization of traffic flows in highly congested airspace with rapidly varying convective weather is an extremely complex problem. Traffic managers need automated decision support systems that integrate flight information, trajectory models and convective weather products to assist in developing and executing convective weather mitigation plans.

A key element of an integrated ATM/wx decision support system is the ability to automatically predict when pilots in en route airspace will choose to deviate around convective weather and how far they will deviate from their planned path when they do deviate. The FAA Aeronautical Information Manual suggests that pilots avoid thunderstorms characterized by “intense radar echo” in en route airspace by at least 20 nautical miles (40 km). However, a recent study (Rhoda, et. al., 2002) of pilot behavior in both terminal and en route airspace near Memphis, TN suggested that pilots fly over high reflectivity cells in en route airspace and, penetrate lower cells whose reflectivity is less than VIP level 3. Recent operational experience with CIWS supports the Rhoda findings (Robinson, et. al., 2004).

This study presents initial results of research to develop a quantitative model that would predict when a pilot will deviate around convective weather in en route airspace. It also presents statistics that characterize hazard avoidance distances and weather penetrations. The results are based on the analysis of more than 800 flight trajectories through two Air Traffic Control (ATC) en route super-sectors (geographical regions that include several adjacent ATC en route sectors) on five days in the summer of 2003. One super-sector from the Indianapolis Air Route Traffic Control Center (ZID ARTCC) encompassed southern Indiana, southwestern Ohio and northern Kentucky (ZID); the other, located in the Cleveland ARTCC (ZOB), included northern Ohio, along the southern shore of Lake Erie (ZOB). The weather encountered along the flight trajectories was characterized by the CIWS high-resolution precipitation (VIL) and radar echo tops mosaic (Klingle-Wilson and Evans, 2005) and NLDN lightning products

A weather-related deviation was defined as a flight path segment where the planned trajectory encountered hazardous weather and the actual trajectory flown deviated from the planned trajectory by a distance greater than the deviation distance threshold. The deviation distance threshold for each super-sector was determined by analyzing trajectories during a 24-hour period in which no hazardous weather was present. An automated algorithm was developed to detect flight trajectories that encountered significant weather and to determine which of these encounters resulted in convective weather-related deviations. The detection algorithm results were verified by an analyst, and the verified results and associated convective weather data provided input to statistical classification algorithms that were used to generate the deviation model.

The avoidance distance associated with a deviation is defined as the minimum distance between the deviating flight trajectory and the contour of a weather feature which may be considered the boundary of the cell that caused the deviation (for example, the 30,000 foot echo top contour). Avoidance distances were calculated for 24 different weather feature boundaries from more than 200 deviations selected by an analyst.

In the ZID super-sector, where convective cells were generally characterized by high VIL, high echo tops and sharp boundaries, and there was little variation in flight tracks along weather free routes, the model deviation detection and prediction results were encouraging: 1) The automated deviation detection algorithm achieved approximately 90% probability of detection and 10% false alarm rate for both deviations and non-deviations. 2) More than 70% of pilots whose planned flight trajectories encountered convective cells with echo tops more than 5 kft below flight altitude did not deviate. 3) The best predictor of convective weather-related deviation is deltaZ (the difference between flight altitude and radar echo top) along the planned flight trajectory. Deviation prediction models based on deltaZ and VIL or deltaZ and lightning encountered along the planned trajectory had prediction error rates of approximately 22%. 4) Pilots flew within 25 km of cell boundaries (VIP level 3 contour around the convective cell) in approximately 75% of the deviations analyzed.

In the ZOB super-sector, the test case weather was generally characterized by low-topped, weak convection and there were significant flight deviations on weather-free air routes. As a result, weather-related deviations could not be easily identified, and trajectories from ZOB were not included in the deviation prediction model. Analysis of more cases from the ZOB and ZID super-sectors and other regions of the national air system (NAS) is needed to develop a generally applicable automated model for predicting operationally significant deviations in enroute airspace as a function of convective weather characteristics, air route structures and preferred routing strategies.