Combined winds and turbulence prediction system for automated air-traffic management applications

A time-lagged ensemble of energy dissipation rate (EDR)-scale turbulence metrics is evaluated against in situ EDR observations from commercial aircraft over the contiguous United States and applied to air-traffic management (ATM) route planning. This method uses the Graphic Turbulence Guidance forecast methodology with three modifications. First, it uses the convection-permitting-scale (Δx = 3 km) Advanced Research version of the Weather Research and Forecasting Model (ARW) to capture cloud-resolving-scale weather phenomena. Second, turbulence metrics are computed for multiple ARW forecasts that are combined at the same forecast valid time, resulting in a time-lagged ensemble of multiple turbulence metrics. Third, probabilistic turbulence forecasts are provided on the basis of the ensemble results, which are applied to the ATM route planning. Results show that the ARW forecasts match well with observed weather patterns and the overall performance skill of the ensemble turbulence forecast when compared with the observed data is superior to any single turbulence metric. An example wind-optimal route (WOR) is computed using areas experiencing ≥10% probability of encountering severe-or-greater turbulence. Using these turbulence data, lateral turbulence avoidance routes starting from three different waypoints along the WOR from Los Angeles International Airport to John F. Kennedy International Airport are calculated. The examples illustrate the trade-off between flight time/fuel used and turbulence avoidance maneuvers.

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Author Kim, Jung-Hoon
Chan, William
Sridhar, Banavar
Sharman, Robert
Publisher UCAR/NCAR - Library
Publication Date 2015-04-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T19:06:21.562707
Metadata Record Identifier edu.ucar.opensky::articles:16653
Metadata Language eng; USA
Suggested Citation Kim, Jung-Hoon, Chan, William, Sridhar, Banavar, Sharman, Robert. (2015). Combined winds and turbulence prediction system for automated air-traffic management applications. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7tx3gj0. Accessed 19 April 2024.

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