Translation Products

Effective strategic management of traffic flows during convective weather events requires a system that can translate convective weather information into anticipated air traffic operational impact. Predictions of convective weather impacts enable proactive traffic flow management, leading to an increase in the effective use of available airspace, and a reduction in overall air traffic delay.

Predicting Air Traffic Impact due to Convective Weather

How does one translate convective weather information into operational impact on air traffic? First, convective weather delays occur because thunderstorms reduce the capacity of air traffic resources, like jet routes. Capacity is reduced because it is harder for the air traffic controller, who is controlling the thunderstorm-impacted resource, to keep aircraft safely separated. One of the challenges is that the response of pilots to thunderstorms must be predicted. If a pilot asks to deviate from the planned route to avoid a thunderstorm, the controller must guide the deviation while keeping the aircraft safely separated from all of the other aircraft in the vicinity. Effectively predicting delays means first accurately predicting pilot behaviors in convective weather.

Convective Weather Avoidance Fields

Example of a pilot deviation to avoid weather upon arrival at DFW airport.

To solve this problem, NASA has developed the Convective Weather Avoidance Model (CWAM) — a first-of-its-kind model that estimates the probability that a pilot will change his or her route to avoid convective weather. CWAM provides a probabilistic measure of the response of pilots to convective weather, based on correlating detailed weather observations with trajectories of aircraft that either penetrated or deviated to avoid areas of convective weather.

An example of a pilot deviation due to convective weather is shown in the image. The pink line is the planned trajectory with labelled points along the path to the Dallas/Ft. Worth airport (DFW). The blue line is the actual trajectory flown by the aircraft, represented as a blue diamond. Several blue points ahead of the aircraft indicate future points along the rerouted flight path into DFW. Notice how the planned trajectory intersects heavy weather, as indicated by the orange and red radar returns, and the actual trajectory almost entirely avoids the weather.

Until the advent of NextGen Weather Processor (NWP), there was no source of the sufficiently precise and quantitative weather characteristics needed to model pilot behavior. CWAM requires as input NWP’s high resolution, deterministic, radar-forward predictions of Precipitation and Echo Tops. Broadly defined probabilistic weather forecasts like the CCFP (CDM Convective Forecast Planning Guidance, where CDM stands for Collaborative Decision Making) do not provide the kind of detailed weather characteristics needed to model pilot decisions.

The output of CWAM is the Convective Weather Avoidance Field (CWAF), which requires as input the aircraft flight altitude, and the NWP Precipitation and Echo Tops products. CWAF indicates the probability that a pilot will deviate at a specific position in three-dimensional space, and in time. Predictions of both enroute and terminal airspace constraints due to weather, based on CWAF estimates, yield more reliable planning information for airlines and their passengers.1

Convective Weather Avoidance Polygons

Example of Convective Weather Avoidance Polygons surrounding regions of high values in the Convective Weather Avoidance Field.

To enable predictions of the most likely weather-avoiding trajectories through areas flagged by CWAF, NASA further developed Convective Weather Avoidance Polygons (CWAP).2 Construction of the polygons relies heavily on the echo tops field at flight altitude most commonly associated with cloud boundaries that pilots will avoid. The CWAP essentially identify the "fly/no fly" boundaries of convective storms that impact air traffic operations.

With robust polygons defined, preferred weather-avoiding trajectories can be automatically generated. Knowing these trajectories in advance can help reduce the workload required to plan and coordinate deviations during weather impacts.

An example of of the Convective Weather Avoidance Field (CWAF) and Convective Weather Avoidance Polygons (CWAP) for thunderstorms over New York and Pennsylvania is shown. CWAF probabilities less than 70% are shown in grey, while probabilities greater than 70% are shown in red. Also illustrated are six polygons ranging in size from small to large, shown as thick white contours surrounding CWAF regions. While the largest of these CWAP enclose both high and low probabilities of pilot deviation, the outer polygon delineates the entire region through which pilots are unlikely to fly. Pilot trajectories have been shown to remain outside of the CWAP enclosed regions.2

NWP's predictive products, along with the associated translation products described here, are used in building Confidence Metrics that support the operational decision making required of strategic traffic flow managers.