A Generic Methodology to Characterize and Display Terminal Wind Forecast Uncertainty

Predictions of wind speed and direction found in terminal aerodrome forecasts (TAFs) contain uncertainty. The amount of uncertainty is not explicitly stated, making it challenging for human decision-makers to properly anticipate and optimally plan surface wind-dependent airport runway configuration changes. Consequently, tactical decision-making approaches are used, sometimes resulting in runway changes that are reactive and suboptimal.

In 2018, the Federal Aviation Administration (FAA) asked The MITRE Corporation (MITRE) to develop a broadly applicable, generic method that could be used to characterize terminal wind forecast uncertainty in an operationally useful way. The approach was required to be extensible to any location and to be able to use any weather forecast type.

This presentation and the accompanying paper contain information about the terminal wind forecast uncertainty characterization method that was developed by MITRE and presented to the FAA in early 2019. It can be directly used for any airport or non-airport location with a robust set (e.g., ASOS five-minute reports) of historical wind information, and for all 36 reference (runway) headings. The characterization method can use spot or gridded forecasts, and those forecasts can be deterministic or probabilistic. It can perform the characterization on a combination of multiple forecasts. Using regression techniques, the method can also produce characterization information for locations that do not have a robust set of historical wind observations.

The approach uses a common relational database to store the required information, and a COTS software program as the means of providing inputs to it and displaying the numerical probability outputs from it.

The primary target of the method's output is a future decision support system that will be used to help manage airport runway configurations. However, one potential visualization solution was also developed in support of project goals to ensure that humans could ingest and use the output of the method directly, without having to rely solely on the cognitive interpretation of raw numerical probabilities. The visualization solution, which uses widely available data management and presentation software, was designed to ensure that the output of the proposed method can provide operational value for the human decision-maker.

NOTICE

This work was produced for the U.S. Government under Contract DTFAWA-10-C-00080 and is subject to Federal Aviation Administration Acquisition Management System Clause 3.5-13, Rights In Data-General, Alt. III and Alt. IV (Oct. 1996).

The contents of this document reflect the views of the authors and The MITRE Corporation and do not necessarily reflect the views of the Federal Aviation Administration (FAA) or the Department of Transportation (DOT). Neither the FAA nor the DOT makes any warranty or guarantee, expressed or implied, concerning the content or accuracy of these views.

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Approved for Public Release; Distribution Unlimited. Case 19-2499.