Translating Convective Weather Forecasts into Strategic Traffic Management Decision Aids

Weather accounts for over 70% of the delay in the US National Airspace System (NAS) and convective weather accounts for 60% of these weather delays. To try and mitigate these delays, forecasts of convective weather are used by traffic flow managers to attempt to match traffic demand to capacity constraints of specific air traffic resources such as en route flows or departure fixes via a strategic management plan. Traffic demand for impacted resources is managed through the application of traffic management initiatives (TMI) that either remove demand from an impacted airspace or reduce demand by delaying the departure of flights filed through the impacted airspace. Typical strategic TMI programs used by the Air Traffic Managers of today are mandatory playbook reroutes, Ground Delay Programs (GDP) and Airspace Flow Programs (AFP). Since these TMIs require the pre-departure management of demand, the lead time for such decisions may be several hours in advance of the event onset to ensure that the TMI is in place soon enough to capture demand prior to departure. This also allows airline operators to plan for the schedule and fueling consequences of the TMI.

For successful planning of TMIs, decision makers require weather forecasts of the impacted airspace between 2 and 8 hours in advance of the event to set the critical parameters of the TMI such as start time, duration and maximum flow reduction. Weather-only convective forecasts are available to the traffic planner in the strategic time domain such as the Consolidated Storm Prediction for Aviation (CoSPA). However, these forecasts provide little guidance about aviation impact on the air traffic resources and the precise location, severity, scale, and timing of operationally significant storms and the human response to those storms can be notoriously difficult to predict. Therefore, the decision maker is left to make critical TMI decisions based on a subjective assessment of potentially conflicting weather forecast information.

The lack of an explicit translation of weather forecasts into resource constraints is a shortfall in the current weather information available to air traffic managers for strategic traffic flow management. There are several consequences of this shortfall. First, without an explicit translation there is a lack of an operationally relevant methodology to assess weather forecast resource impact and overall forecast performance. Each participant (e.g., Air Traffic Control System Command Center (ATCSCC), Air Routes Traffic Control Center (ARTCC) Traffic Manager Unit (TMU) and Airline Operations Center (AOC)) comes into the collaborative strategic planning process with their own set of operational objectives, favorite forecast information, risk tolerance, etc. This wide and often divergent range of opinions and goals must somehow be melded into a plan of action. Without shared objective forecasts of weather impacts and estimates of decision risk, there is little common ground on which to base discussions about the best plan of action that addresses the different legitimate concerns of stakeholders. Second, the utility of convective weather forecasts is directly related to the quality of decisions and NAS performance outcomes that the forecasts can support. The definition of explicit, validated weather translations provides an objective and operationally relevant measure of truth against which forecasts can be compared. Without translation-based forecast evaluations, it is difficult to determine how much of an operational shortfall in convective weather mitigation is due to poor weather forecasts and how much is the result of poor interpretation and application of forecast information.

This paper will present a method to translate strategic convective weather forecasts into a metric that estimates the impact of convective weather on air traffic flows in the US National Airspace System. The translation method will be validated by measuring the flow rates of aircraft using weather impacted airspace. Case studies will be discussed showing the impact of good and poor strategic and tactical air traffic management on the validation results. Finally, operational experience with an early decision support prototype based on the proposed impact model will be described.