7.1 A Historical Perspective on the Integration of Weather Information into Air Traffic Management Decision Support Tools (Invited Presentation)

Tuesday, 14 January 2020: 3:00 PM
206A (Boston Convention and Exhibition Center)
James E. Evans, MIT Lincoln Laboratory, Lexington, MA

Handout (1.4 MB)

Improving air traffic management (ATM) decision making for congested airspace and airports in adverse weather has been identified as a key FAA and operator objective for a number of years. An important element of this decision making is understanding the current and expected capacity impacts due to the weather. Historically, this has been accomplished by having experienced ATC personnel subjectively translate the available weather information (e.g., surface observations, weather radar products) and forecasts into assessments of current and expected capacity impacts.

In 2007, the FAA’s Research, Engineering and Development Advisory Committee (REDAC) issued a report on ATM-weather integration that recommended that the FAA initiate a crosscutting research program in ATM/Weather integration with senior FAA leadership and the involvement of NASA [FAA REDAC, 2007].

Since the REDAC report, there has been considerable research on and operational experience with the objective, quantitative translation of meteorological measurements and forecasts into quantitative airspace and airport capacity impact forecasts that can be incorporated into ATM decision support systems. Because pilots have the principal responsibility for the avoidance of weather that will adversely impact their aircraft, a necessary element of the translation involves gaining a quantitative understanding of likely pilot actions in the face of weather phenomena such as thunderstorms and turbulence. Dealing with weather forecast uncertainty has also often been an important aspect of improving decision making.

In this talk we will review experience over the past 20 years in the use of integrated weather-ATM decision support tools with emphasis on capabilities that have been operationally tested. The talk will conclude with a discussion of lessons learned in achieving success in operational use of such tools and, promising areas for achieving improved decision making through ATM-weather integration.

Figure 1 illustrates key elements of a contemporary convective weather-ATM decision tool – the Traffic Flow Impact (TFI) decision tool [Matthews, et. al., 2016] currently being used at the FAA ATC System Command Center (ATCSCC) to improve decision making on reducing flow through en route airspace regions. Forecasts of convective storm precipitation and echo tops are combined with an empirically determined Convective Weather Avoidance Model (CWAM) [Matthews and DeLaura, 2010] to predict the degree that weather will reduce the amount of traffic flow that can be accommodated through groups of routes called Flow Constrained Areas (FCAs). A number of different convective forecasts (e.g. CIWS, HRRR, SREF, LAMP) are used by machine learning algorithms to provide probabilistic 0-12 hour forecasts of flow reduction, including uncertainty in that forecast. These flow forecasts are then used by FAA planners to assign ground delays for flights filed through the FCAs.

In table 1, we show the integrated ATM-weather decision support tools that have been used operationally in the past 20 years.

We will discuss how significant operational success has at times been achieved with a number of the tools (e.g., RAPT [Robinson, et. al., 2009], TBFM, and GPSM [Shisler, et. al., 2013]). However, it has proved harder than expected to achieve ongoing operational success due to factors such as:

  1. Difficulty in achieving adequate user training once systems were operationally deployed (especially when there has been significant loss of experienced operational decision makers due to retirements)
  2. Dealing with weather forecast uncertainty
  3. Coping with differences in air traffic management strategies at different locations
  4. Changes to weather patterns, sensors, site specific ATM factors and Numerical Weather Prediction models that result in a need for ongoing retraining of machine intelligence algorithms

The paper concludes with a discussion of future prospects including a discussion of contemporary proprietary integrated ATM-weather decision approach systems as well as how some of the lessons learned in the first 20 years of operational use of integrated weather-ATM decision support systems might be addressed to inform future tool designs.


FAA REDAC, 2007, “Report of the Weather-ATM Integration Working Group”

Matthews, M. et al, 2016, “Heterogeneous Convective Weather Forecast Translation into Airspace Permeability with Prediction Interval,” Journal Air Transportation.

Matthews, M., DeLaura, R., 2010, “Assessment and Interpretation of En Route Wx Avoidance Fields from the Convective Wx Avoidance Model,”,10th AIAA Aviation Technology, Integration and Operations Conference.

Shisler, L. et. al., 2013, “An operational evaluation of the Ground Delay Program Parameters Selection Mode (GPSM),” Tenth USA/Europe ATM Seminar (ATM2013)

Robinson, M., DeLaura, R., Underhill, N., 2009, “The Route Availability Planning Tool (RAPT),”Eighth USA/Europe ATM Seminar (ATM2009).

DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited.

This material is based upon work supported by the Federal Aviation Administration under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Federal Aviation Administration.

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