Publications

The optimization of traffic flows in highly congested airspace with rapidly varying convective weather is an extremely complex problem. Aviation weather systems such as the Corridor Integrated Weather System (CIWS) provide weather products and forecasts that aid en route traffic managers in making tactical routing decisions in convective weather, but traffic managers need automated decision support systems that integrate flight information, trajectory models and convective weather products to assist in developing and executing convective weather mitigation plans. A key element of an integrated ATM/wx decision support system is the ability to predict automatically when pilots in en route airspace will choose to deviate around convective weather and how far they will deviate from their planned path. The FAA Aeronautical Information Manual suggests that pilots avoid thunderstorms characterized by intense radar echo in en route airspace by at least 20 nautical miles (40 km). However, a recent study (Rhoda, et. al., 2002) of pilot behavior in both terminal and en route airspace near Memphis, TN suggested that pilots fly over high reflectivity cells in en route airspace and penetrate lower cells whose reflectivity is less than VIP level 3. Recent operational experience with CIWS supports the Rhoda findings (Robinson, et. al., 2004). This study presents initial results of research to develop a quantitative model that would predict when a pilot will deviate around convective weather in en route airspace. It also presents statistics that characterize hazard avoidance distances and weather penetrations. The results are based on the analysis of more than 800 flight trajectories through two Air Traffic Control (ATC) en route super-sectors (geographical regions that include several adjacent ATC en route sectors) on five days in the summer of 2003. One supersector from the Indianapolis Air Route Traffic Control Center (ZID ARTCC) encompassed southern Indiana, southwestern Ohio and northern Kentucky (ZID); the other, located in the Cleveland ARTCC (ZOB), included northern Ohio, along the southern shore of Lake Erie (ZOB). The weather encountered along the flight trajectories was characterized by the CIWS high-resolution precipitation (VIL) and radar echo tops mosaic (Klingle-Wilson and Evans, 2005) and NLDN lightning products. Flight trajectories were taken from the Enhanced Traffic Management System (ETMS).

A major concern in contemporary traffic flow management (TFM) is improving decision making when severe convective weather (Wx) impacts en route sectors throughout the National Airspace System (NAS). The FAA is currently seeking to reduce these convective weather delays through the use of multi-hour (e.g. 4 and 6 hour) Wx forecasts coupled with strategic planning by the FAA traffic flow managers and airline personnel to determine how en route traffic should be rerouted so as to avoid sector overloads and minimize the magnitude of the delays that occur [Huberdeau and Gentry (2004)]. One of the major challenges in the strategic planning process is the difficulty in converting the convective weather forecasts into forecasts of en route sector capacity. In this study, we explore the development of a model that can be combined with forecast validation data to translate probabilistic convective weather (Wx) forecasts into forecasts of a surrogate for sector capacity - the fraction of jet routes that would be blocked- within an en route sector.

This paper discusses inter-related studies and development activities that address the significant challenges of implementing Air Traffic Management initiatives in airspace impacted by thunderstorms. We briefly describe current thrusts that will improve the quality and precision of thunderstorm forecasts, work in progress to convert these forecasts into estimates of future airspace capacity, and an initiative to develop a robust ATM optimization model based on future capacity estimates with associated uncertainty bounds. We conclude with a discussion of the thunderstorm ATM problem in the context of future advanced airspace management concepts.

Weather continues to be a significant source of delay for aircraft destined to and departing from the New York metropolitan area, with weather delays through the first half of 2004 reaching levels not seen since 2000. In Allan et al. (2001), it was shown that total arrival delays on days with low ceiling and visibility at Newark Airport (EWR) averaged 210 hours, increasing to an average of 280 hours on days with thunderstorms impacting EWR operations. An analysis of Ground Delay Programs (GDPs) due to weather in the National Airspace System was performed for 2002-20031. Low ceilings, thunderstorms, snow, and wind were all shown to be significant sources of delay (Figure 1). These same weather conditions that lead to GDPs often also lead to holding and long departure delays. In 1998, demonstration of a prototype Integrated Terminal Weather System (ITWS) began in the New York area, helping significantly reduce terminal delays from convection, high surface winds, and vertical wind shear (Allan et al., 2001). In 2002, a new demonstration system, the Corridor Integrated Weather System (CIWS), was introduced at New York Center (ZNY) to help mitigate convective weather delays in the enroute airspace. Substantial benefits were realized from this system and are documented in Robinson et al. (2004). While systems such as ITWS and CIWS have helped significantly with convective weather, much has been learned during the field-testing of these systems about areas where existing research and technology could be leveraged to reduce weather delay in areas that have not been addressed previously. This paper will discuss four experimental products that recently have been or will be fielded in the NY area and how they are expected to benefit the aviation system. Enhancements to the Terminal Convective Weather Forecast (TCWF) address delays in convective weather, snowstorms, and steady rain. The newly fielded Route Availability Planning Tool (RAPT) addresses departure delays in convective weather. The Ceiling and Visibility (C&V) Diagnosis and Prediction Product will address delay due to low ceiling and visibility. The Path-Based Shear Detection (PSD) tool is expected to help both to reduce delays on days with high winds and to indicate regions of potential low altitude turbulence.

This paper presents a detailed study of a convective weather event affecting the northeastern United States on 19 April 2002: its impacts on departure throughput, the response of traffic managers and an analysis of the potential effects of decision support on system performance. We compare actual departure throughput to what may have been achieved using the Route Availability Planning Tool (RAPT), a prototype decision support tool. We examine two questions: Can decision support identify opportunities to release departures that were missed during the event? How is route selection guidance affected by the operational model incorporated into the decision support tool? By "operational model", we mean three things: the choice of weather forecast information used to define hazards (precipitation, echo tops, etc.), the model for how airspace is used (route definition and allocation) and the assessment of the likelihood that a given route is passable. We focus our analysis on the operational model only; we eliminate weather forecast uncertainty as a factor in the analysis by running RAPT using the actual observed weather as the forecast ('perfect' forecast). Results show that decision support based on perfect forecasts is sensitive to all three elements of the operational model. The sensitivity to weather metrics became evident when we compared decision support based upon perfect forecasts of level 3 vertically integrated liquid (VIL) to that based upon VIL plus storm echo tops. Traffic managers were at times able to move more aircraft by abandoning nominal routing than if they had used nominal routing with perfect weather information. The assessment of route availability will, at times, be ambiguous; different interpretations of that assessment lead to decisions that result in significant differences in departure throughput. These results suggest that for traffic flow management tools, a realistic operational model may be at least as important as the frequently discussed problem of weather forecast uncertainty.

Accurate, short-term (0-2 hour) forecasts of convective initiation provide critical information about weather that has a major impact on aviation safety and system capacity. The Terminal Convective Weather Forecast (TCWF) algorithm is a key component of the FAA's operational Integrated Terminal Weather System (ITWS). Convective forecasts rely, in part, upon detection of convergence zones in the boundary layer. Detection of convergence requires accurate, high-resolution wind estimates, which may be based on measurements from many sources, including Terminal Doppler Weather Radar (TDWR), Next Generation Weather Radar (NEXRAD), Automatic Weather Observation System/Automatic Surface Observation System (AWOS/ASOS), aircraft (via the Meteorological Data Collection and Reporting System, MDCRS) and Low Level Wind Shear Alert System (LLWAS). These data may be directly analyzed, combined with satellite and sounding data or ingested into physical models that estimate winds and produce short term forecasts. We compare two windfield estimation techniques: Terminal Winds (TWINDS) [Cole et. al., 2000], an optimal estimation algorithm developed at Lincoln Laboratory that is deployed operationally in ITWS, and Variational Doppler Radar Analysis System (VDRAS) [Sun and Crook, 2001], a 4DVAR algorithm developed and fielded by the Research Applications Program (RAP) at NCAR. These techniques differ markedly in their use of physical models: TWINDS applies no physical constraints to its analysis, while VDRAS uses a 4DVAR technique to fit the data with a boundary layer model as a strong constraint. The techniques also differ in their computational requirements: TWINDS requires substantially less computational power than VDRAS. We were able to run TWINDS at higher horizontal resolution and update rate (1km grid spacing, 5 minute update) than VDRAS (2km and 12 minutes).

The estimation of air and particle motions in storms from multiple Doppler radar measurement is a long standing problem in radar meteorology. Our research interest in understanding the relationship of electrical change generation processes above the freezing level to thunderstorm life cycle, and in the detailed quantification of the eventual low altitude divergent outflow produced by the storm, demands an accurate retrieval of air and particle motions at essentially all altitudes within the storm. We found that existing approaches had deficiencies for our needs, and have developed an improved "hybrid" approach which attempts to provide high quality estimates throughout the storm volume.