Publications

When operationally significant weather affects the National Airspace System (NAS) a Severe Weather Avoidance Program (SWAP) is initiated. Each SWAP event is a unique mix of demand, weather conditions, traffic flow management (TFM) initiatives and traffic movement. Following a SWAP, the day's events are reviewed and the TFM initiatives used are evaluated to understand their impact on the traffic flows, benefits, and disadvantages. These analyses require an accurate representation of the conditions during SWAP and objective, data-driven metrics to determine the effectiveness of the implemented TFM initiatives, and to identify opportunities for improved decision making in future events. As part of the ongoing development and evaluation of the Route Availability Planning Tool (RAPT), a departure management decision support prototype currently deployed in New York, several detailed metrics were developed to streamline these analyses. This paper focuses on metrics that address the most significant concern regarding departure flows from New York airports: the timely reopening of departure routes that have been closed due to convective weather impacts. These metrics are derived from two datasets: flight tracks from the Enhanced Traffic Management System (ETMS) to monitor the flight traffic, and route blockage from the Route Availability Planning Tool (RAPT) to determine the impact of weather on routes. RAPT automatically identifies Post-Impact-GREENs (PIGs) - the period of time when routes are clear ('GREEN') after being blocked by convective weather. Identifying PIGs early is a key element of the RAPT concept of operations, which enables traffic managers to restart traffic flow sooner along these routes, alleviating backed up ground conditions and reducing delay times for waiting flights. An automated system, that correlates PIGs identified by RAPT with departure traffic flows, calculates both the time from the appearance of each PIG until the first departure along the PIG route, and the departure rate on the route during the PIG period. Short times to first departure and high departure rates during PIGs indicate efficient departure management during SWAP. Arrival aircraft deviating into departure airspace is also managed by closing the departure route until the danger from incurring flights has passed. Arrival incursions are sometimes recorded in the National Traffic Management Log (NTML), but the extent to which the deviations occur is unmeasured. Lack of details regarding deviations limits evaluation of implemented responses and alternative actions. New algorithms comparing clear weather vs. SWAP traffic flows enables the locations and durations of incursions to be identified. Exact figures detailing incursions allows for thorough review as well as recognition of areas of frequent incursions and the potential for developing a targeted response for like situations. Full flight tracks of arriving and departing flights provide significant insight into the status of the NAS. During SWAP when the airspace capacity is decreased and airport operation rates are limited, airborne aircraft by protocol receive priority. Arrival numbers can completely dominate operations at these times both in the air and on the ground, draining the resources available for departures in particular flows or for an entire region. To convey cases where departure infrequency results from these conditions, arrival and departure counts grouped according to direction of travel are calculated on an hourly basis. Results from the automated analysis are made available on the RAPT Evaluation and Post Event Analysis Tool (REPEAT) website by 7AM ET for the FAA Northeast tactical review teleconferences, and are being tracked over the convective season for further analysis of operational performance. This paper will present the techniques used in the automated system and initial results from the analysis of operational data.

Severe weather avoidance programs (SWAP) due to convective weather are common in many of the busiest terminal areas in the US National Airspace System (NAS). In order to make efficient use of available airspace in rapidly evolving convective weather, it is necessary to predict the impacts of the weather on key resources (e.g., departure and arrival routes and fixes), with frequent updates as the weather changes. Currently, this prediction is a mental process that imposes a significant cognitive burden on air traffic managers. As a result, air traffic management in SWAP is often inconsistent and decisions result in less than optimal performance. The Route Availability Planning Tool (RAPT) is a prototype automated decision support tool, intended to help air traffic managers in convective weather SWAP, by predicting the impacts of convective weather on departure routes. Originally deployed in New York in August, 2002, RAPT has recently undergone two field evaluations (2007 and 2008) in order to test and refine its concept of operations, evaluate the accuracy and usefulness of its decision guidance, and estimate observed and potential delay reduction benefits that may be achieved as a result of its use. This paper presents the results of the 2008 performance evaluation, focusing on the concept of operations and the quality of decision support guidance. A second paper [1] presents analyses of delay reduction benefits and the operational decision making environment in which RAPT is deployed.

Airspace capacity constraints caused by adverse weather are a major driver for enhanced Traffic Flow Management (TFM) capabilities. One of the most prominent TFM initiatives introduced in recent years is the Airspace Flow Program (AFP). AFPs are used to plan and manage flights through airspace constrained by severe weather. An AFP is deployed using "strategic" (i.e., 4-6 hour) weather forecasts to determine AFP traffic throughput rates. These rates are set for hourly periods. However, as convective weather continuously evolves, the achievable en route airspace throughput can fluctuate significantly over periods as short as 15-30 minutes. Thus, without tactical AFP adjustments, inefficiencies in available airspace usage can arise, often resulting in increased air traffic delay. An analysis of AFP usage in 2007 was conducted in order to (1) better understand the relationship between AFP parameters and convective weather characteristics, and (2) assess the potential use of an objective model for forecasting tactical AFP throughput. An en route airway blockage-based algorithm, using tactical forecast information from the Corridor Integrated Weather System (CIWS), has been developed in order to objectively forecast achievable flow rates through AFP boundaries during convective weather. A description of the model and preliminary model results are presented.

The Route Availability Planning Tool (RAPT) is an integrated weather/air traffic management decision support tool that has been designed to help traffic managers better anticipate weather impacts on jet routes and thus improve NY departure route usage efficiency. A field study was conducted in 2007 to evaluate RAPT technical performance at forecasting route blockage, to assess RAPT operational use during adverse weather, and to evaluate RAPT benefits. The operational test found that RAPT guidance was operationally sound and timely in many circumstances. RAPT applications included increased departure route throughput, more efficient reroute planning, and more timely decision coordination. Estimated annual NY departure delay savings attributed to RAPT in 2007 totaled 2,300 hours, with a cost savings of $7.5 M. The RAPT field study also sought to develop a better understanding of NY traffic flow decision-making during convective weather impacts since the RAPT benefi ts in 2007 were significantly limited by a number of factors other than direct weather impacts. Observations were made of the multi-facility departure management decision chain, the traffic management concerns and responsibilities at specific FAA facilities, and the procedures and pitfalls of the current process for capturing and disseminating key information such as route/fix availability and restrictions.

The Route Availability Planning Tool (RAPT) is an integrated weather/air traffic management decision support tool that has been designed to help traffic managers better anticipate weather impacts on jet routes and thus improve NY departure route usage efficiency. A field study was conducted in 2007 to evaluate RAPT technical performance at forecasting route blockage, to assess RAPT operational use during adverse weather, and to evaluate RAPT benefits. The operational test found that RAPT guidance was operationally sound and timely in many circumstances. RAPT applications included increased departure route throughput, more efficient reroute planning, and more timely decision coordination. Estimated annual NY departure delay savings attributed to RAPT in 2007 totaled 2,300 hours, with a cost savings of $7.5 M. The RAPT field study also sought to develop a better understanding of NY traffic flow decision-making during convective weather impacts since the RAPT benefits in 2007 were significantly limited by a number of factors other than direct weather impacts. Observations were made of the multi-facility departure management decision chain, the traffic management concerns and responsibilities at specific FAA facilities, and the procedures and pitfalls of the current process for capturing and disseminating key information such as route/fix availability and restrictions.

The Convective Weather Avoidance Model (CWAM), developed in collaboration with NASA, translates convective weather information into a Weather Avoidance Field (WAF), to determine if pilots will route around convective regions. The WAF provides an estimate of the probability of pilot deviation around convective weather in en route airspace as a function of time, horizontal location, and flight altitude [1][2]. The results of the WAF can used to create reroutes around regions of convective weather where pilots are more likely to deviate. If reliable WAF information is provided to the cockpit and ground, pilot decisions may become more predictable, simplifying the task of air traffic control in convective weather. The improvement and validation of CWAM requires inference of pilot intent from flight trajectory data, which is challenging. The process currently involves laborious human review of the results of automated deviation detection algorithms. Both previous CWAM studies and a recent validation study [3] illustrate the difficulties and limitations of attempting to infer pilot intent from flight trajectory data. Furthermore, observed flight tracks may not correctly represent pilot preference. In some instances, pilots may have penetrated airspace that they would rather have avoided or they may have avoided airspace that was easily passable. In order to improve and assess the accuracy of the WAF, it is desirable to compare WAF predictions of pilot intent with direct evidence of the airborne experience during weather encounters in en route airspace, such as normal acceleration. To achieve this, a series of flights using a research aircraft was conducted. In the summer of 2008, four research flights (three on 17 July and one on 14 August) were flown in and around convective activity in the upper Midwestern United States to gather aircraft data that could be correlated to the WAF and other remotely-sensed weather data. The aircraft, a Rockwell Sabreliner Model 50 research aircraft (similar to the Sabreliner Model 40 production model) owned by Rockwell-Collins, flew through and around convective activity while recording on-board accelerations for comparison to the WAF deviation probabilities encountered along the flight trajectory. Aircraft state data, on-board weather radar images, video, photographs and pilot narrative from the cockpit were also collected. This paper briefly describes the CWAM model and WAF. Description of the data collection methodology is then presented. Following that section are descriptions of the flights comparing radar data from the flight deck with ground-based weather radar and the WAF. Visual observations and pilot narrative from the flight deck are also presented. Next, the normal acceleration data from on-board accelerometer data are compared with WAF. Finally, conclusions and suggestions for further study are presented.

In this paper, we develop a novel way to measure the accuracy of weather forecasts based upon the impact on air traffic flows. This method uses new techniques developed as part of the CWAM that consider the complicated interaction between pilots, air traffic controllers and weather. This technique, known as the blockage model (Martin et al., 2006), differentiates between minor deviations performed by pilots around convective weather and their larger deviations due to fully blocked air routes that require air traffic control interaction. This blockage model is being used by the automated Route Availability Planning Tool (RAPT) to predict route blockage for NYC departures. RAPT integrates the Corridor Integrated Weather Systems (CIWS) deterministic 0-2 hour forecasts of precipitation and echo tops into route specific forecasts of impact on air traffic in the congested east coast corridor. Applying the blockage model to the entire CIWS weather domain as a metric for scoring the performance of the forecast algorithms is shown to be an excellent approach for measuring the adequacy of the forecast in predicting the impact of the convective weather on air traffic operations.

It is generally agreed that effective management of convective weather in congested airspace requires decision support tools that translate the weather products and forecasts into forecasts of ATC impacts and then use those ATC impact forecasts to suggest air traffic management strategies. In future trajectory-based operations, it will be necessary to automatically generate flight trajectories through or around convective weather that pilots will find acceptable. A critical first step, needed in both today's air traffic management environment and in the highly automated systems of the future, is a validated model for airspace that pilots will seek to avoid. At the 12th Conference on Aviation, Range and Aerospace Meteorology (Atlanta, 2006), we reported on an initial Convective Weather Avoidance Model (CWAM1) (DeLaura and Evans; 2006). The CWAM1 outputs are three dimensional deterministic and probabilistic weather avoidance fields (WAFs). CWAM1 used Corridor Integrated Weather System (CIWS) VIL and echo top fields and National Lightning Detection Network (NLDN) data to predict aircraft deviations and penetration. CWAM1 was developed using more than 500 aircraft-convective weather encounters in the Indianapolis Air Route Traffic Control Center (ZID ARTCC) airspace. CWAM1 gave the greatest weight to the difference between flight altitude and the 18 dbZ radar echo top with precipitation intensity playing a secondary role. The deviation prediction error rate in CWAM1 was approximately 25%. This paper presents a new model (CWAM2), based on the analysis of trajectories from several ARTCCs [Indianapolis (ZID), Cleveland (ZOB) and meteorological deviation predictors. Additional weather factors that are considered include vertical storm structure (upper level reflectivity and the height of the VIL centroid derived from the NSSL 3D reflectivity mosaic), vertical and horizontal storm growth, the spatial variation in VIL and echo top fields and storm motion.

In this paper, the revised RAPT algorithm and display are described and evaluated. The fidelity of the RAPT operational model is assessed by comparing RAPT departure status with observed departure flows (i.e., trajectories, weather avoidance maneuvers and storm penetrations) on several days when convective weather SWAPs were in effect in New York. Real-time in-situ observations at RAPT facilities (described in a companion paper at this conference; Robinson, 2008), user feedback from RAPT playbacks and the REPEAT web site are used to support this post-event evaluation. For example, real time observations provide the time and operational rationale for a specific departure route closure identified in the traffic flow analysis. This information is necessary to identify closures or flow restrictions that are the result of factors outside of the current RAPT algorithm domain (e.g., traffic restrictions due to volume, downstream congestion, etc.). Real time observations are also used to identify specific times when critical, weather-related operational decisions were made. The RAPT guidance at these critical decision points is analyzed to determine if RAPT provided information that enabled (or could have enabled, had it been used) more timely or effective decisions. The effect of forecast uncertainty on RAPT performance is also examined, particularly in convective weather situations where the location, severity and operational impact were difficult to predict. Strategies that mitigated risks associated with forecast uncertainty are presented. These include the use of additional information provided in the RAPT display, such as echo top heights encountered along the departure route, to confirm or modify RAPT guidance and the consideration of the departure status of two or more adjacent routes to 'average out' variations in the departure status timelines.

This paper describes a method to determine the accuracy of the Convective Weather Avoidance Model which predicts the likelihood that pilots will deviate away from specific areas of convective activity. Visual inspection with a reduced data set helped refine the algorithms used in the verification and offered some preliminary results of the model's accuracy in today's airspace. This model has some explanatory power in predicting regions of airspace where pilots are willing to deviate or fly through. In some instances, pilots appeared not to make an early decision to deviate around convective weather and continued on course as the region appeared more passable when they reached it. In other instances, pilots skirted the edges of regions where the model expected pilots avoid. This behavior suggests edge areas of those model regions were more passable and the convection in that region was not uniform in intensity.