Publications

One of the largest sources of error in the current automated convective weather forecast systems is due to its inability to accurately account for new convective storm development. In many situations the initiation of new convection is preceded by low altitude convergence in the horizontal winds. These regions of low altitude convergence, often referred to as boundaries, are typically associated with synoptic scale fronts, drylines, and thunderstorm outflows. Gridded wind analyses that utilize Doppler weather radar, surface, and aircraft measurements are one of the best sources of low altitude winds that can be used to identify wind boundaries over large domains. This study summarizes the preliminary results of a study which examined the feasibility of using gridded wind analyses from operational wind analysis systems to make automated detections of wind boundaries. The analysis focused on two operational wind analysis systems both capable of producing high update, and high spatial resolution wind analyses over a domain that covers the eastern half of the Continental United Sates (CONUS), the Space Time Mesoscale Analysis System (STMAS) and the Corridor Boundary layer wind analysis system (CBOUND). Wind analyses from both systems were first processed with a Lagrangian temporal filter and then passed through an automated boundary detection algorithm based on the Terminal Doppler Weather Radar (TDWR) Machine Intelligent Gust Front Algorithm (MIGFA). The results indicate that the temporal filter improves the boundary signal to noise ratio such that it is technically feasible to make fully automated boundary detections with image processing techniques.

Air traffic congestion in the United States (US) National Airspace System (NAS) has increased significantly in the past ten years. This congestion has resulted in a rise of air traffic delays, which can cause massive monetary and human costs. When convective weather impacts jet routes and airport terminals, particularly within the most congested airspace sectors, it causes a reduction in traffic capacity that can lead to significant delays. In an effort to increase airspace capacity and reduce air traffic delays, the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL), in collaboration with the National Center for Atmospheric Research (NCAR) and the National Oceanic and Atmospheric Administration (NOAA) are tasked by the Federal Aviation Administration (FAA) to provide aviation weather decision support tools for the air traffic management (ATM) community. To determine which weather products and data dissemination approaches will provide the greatest benefit in terms of increasing airspace capacity, MIT LL is performing ongoing marketing research analyses. The method consists of three primary steps (Ballentine 1994; Evans and Robinson 2005; Evans et al. 2003): 1) Study the system 2) Identify benefits 3) Prioritize opportunities In practice, the execution of these three steps is an iterative process. It is critical to understand how the air traffic system operates to assess the benefits of a weather product. For this reason many studies have been conducted by MIT LL where ATM users have been interviewed, use of decision support tools has been observed, and flight track data have been analyzed to extract the behavior of the pilot (Evans et al. 2003; Evans and Robinson 2005; Robinson et al. 2004; Rhoda et al. 2002; Allan et al. 2001; Bieringer et al. 1999; Rhoda and Pawlak 1999; Forman et al. 1999). These studies have provided valuable insight into how the NAS operates during weather impacts. Weather impacts on the air traffic system can be classified into three basic types: 1) Terminal impacts (≤ 5 nm) 2) En route impacts 3) Transition impacts (between Air Route Traffic Control Centers (ARTCC) sectors and terminal operations) Terminal impacts are those that occur in and around the airport, and are generally less than 5 nm from the runways. These impacts are small in dimension and occur at low altitude, and have been shown to be relatively insignificant to the overall delay problem (Evans et al. 2005). En route impacts occur within ARTCC's jet routes and sectors. These impacts can result in a route being totally or partially blocked and lead to a reduction in capacity. The en route impacts generally occur at high altitude. Transition impacts are those that occur within the zone between the ARTCC sectors and the terminal approaches. By understanding the system one can then identify elements or areas of opportunities that can be exploited to help solve the airspace capacity problem. Weber et al. (2005) identifies four key elements for maintaining capacity during convective weather events: 1) Forecasts of convective weather 2) Capacity models where weather is an input 3) Strategy tools for ATM with weather as an input 4) Airspace capacity enhancements Forman et al. (1999) studied the terminal impact problem and found that the ATM users required precipitation forecasts that were reliable, updated rapidly (5-6 minutes), had high resolution (1 km), short lead times (1-2 hours), and were issued with fine time steps (10-15 minutes). MIT LL used this information to refine its terminal convective weather forecast (TCWF) and received very positive feedback from ATM personnel (Hallowell et al. 1999). Subsequently, the precipitation forecast was extended out to 2-hourtime horizons and was provided to the traffic managers working in busy Midwest and Northeast ARTCCs as part of the Corridor Integrated Weather System (CIWS) (See Klingle-Wilson and Evans (2005) for a description of the CIWS product). However, it was quickly determined that the precipitation product alone was not sufficient for identifying usable en route airspace, since occasionally significant precipitation (≥ level 3)1 had relatively low storm tops (≤ 30 kft). Due to feedback from ATM users, MIT LL produced a high resolution (1 km) enhanced Echo Tops Mosaic weather product (Evans et al. 2003) that is used as a proxy for the cloud top height. Since the operational inception of the CIWS enhanced Echo Tops Mosaic product in August 2002, FAA and airline traffic managers have become acutely aware of the benefits of high-resolution storm top information for efficient en route air traffic control (ATC) operations. CIWS field use assessment campaigns in 2003 revealed significant benefits attributed to use of the Echo Tops Mosaic product (Robinson et al. 2004). During interviews, traffic managers explained that in the past, if an aircraft deviated around a storm in high-traffic airspace, jet routes were closed by default, since pilot behavior was the only easily assessable information available about three-dimensional storm structure. After the CIWS Echo Tops Mosaic was introduced, traffic managers were able to differentiate between isolated storm top concerns, which are easily handled by keeping routes open and absorbing occasional, local deviations, and significant high-topped storm events, which legitimately require route closures and reroutes. Post-event interviews in 2003 revealed that though FAA and airline users were very pleased with the availability and quality of the CIWS Echo Tops Mosaic product, they also needed to know both the past trend and predicted behavior of storm top heights. The CIWS Echo Tops Forecast (ETF) was introduced in May 2005 to meet some of the traffic management requests. This paper discusses the ETF product currently operational in CIWS. We will discuss the generation of the forecast algorithm and provide an initial assessment of the use of the ETF in the field.

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.

One of the major challenges in the US National Airspace System (NAS) today is improving the decisions made when adverse aviation weather occurs. Major increases in the usage of high altitude en route airspace by regional and corporate jets, coupled with greater use of "secondary" airports by low cost air carriers, have dramatically increased the complexity of operating the NAS during bad weather. One potentially powerful approach to improving decision making is to explicitly combine aviation weather information with aviation system information to create an integrated weather/air traffic management (wx/ATM) system that improves the productivity of the NAS operators. However, it will not be enough to be able to develop the technology that could make system improvements possible; it has now become increasingly important to demonstrate quantitative user benefits for any new initiatives. In this paper, we discuss the implications on the development and testing of wx/ATM systems of the need for a successful operational benefits demonstration of the new capability. The paper proceeds as follows. In the next section, we discuss how an integrated wx/ATM system differs from the "conventional" aviation weather decision process. Section 3 describes current efforts by the FAA and the Office of Management and Budget (OMB) to appropriately consider operational benefits as a factor in investment decision making. Section 4 discusses key elements of an "operational benefits centric" approach to wx/ATM system development and testing. Sections 5 and 6 discuss two contemporary examples of integrated wx/ATM systems in the context of section 4. The paper concludes with a summary and recommendations.

Major Federal Aviation Administration (FAA) planning documents (e.g., the FAA Flight Plan 2005-2008, the FAA Air Traffic Organization Fiscal Year 2005 Business Plan, and the Operational Evolution Plan) stress the importance of: Improving National Airspace System operations efficiency by increasing safety and capacity (e.g., reducing delays) and Providing FAA services more efficiently, such that operations costs can be reduced while improving safety and capacity. Continued improvements in air traffic delay mitigation in the NAS are imperative, given expectations for significant increases in near-term air traffic demand. The latest FAA aerospace growth forecast projects a 30% increase in Air Route Traffic Control Center (ARTCC) operations by 2015 (FAA Office of Aviation Policy and Plans, 2005). Improving Air Traffic Control (ATC) productivity during convective weather impact events is particularly important. Air traffic demand is escalating in an airspace network near capacity even in clear-weather. This will limit the ability to exploit advancements made in mitigating en route convective weather delays, unless fielded decision support systems are able to improve traffic management efficiency. Moreover, it is also essential that ATC productivity (e.g., as measured by the number of employees and overtime) be improved, given the reduction in Aviation Trust funding from the passenger ticket tax and overall federal funding constraints. We have previously described how a contemporary convective weather decision support system - the Corridor Integrated Weather System (CIWS) - can facilitate significantly improved capacity enhancing decisions, such as keeping routes open longer and proactive rerouting (e.g., Evans et al. 2005; Robinson et al. 2004). These CIWS-enabled capacity enhancements were shown to result in significant reductions in air traffic delays, airline operating costs, and delay-incurred passenger costs (Robinson et al. 2004). A study of the CIWS contributions to ATC productivity enhancements began in 2005. As part of this effort, real-time observations of CIWS product usage and the time to accomplish weather impact mitigation planning decisions during multiday thunderstorm events were carried out at 8 U.S. ARTCCs. A description of the design (and methodological challenges) of this experiment are presented in Section 2 of this paper. Improved ATC productivity was found to have two components: (1) Reduced workload and increased operational efficiency, as characterized by the amount of time required to develop and implement convective weather mitigation plans and the ability to enhance staffing decisions (2) Increased frequency of capacity enhancing decisions. Results demonstrating how CIWS helped traffic managers reduce workload and increase operational efficiency through time-savings and improved decision-making are presented in Section 3. Important factors such as the variation in performance from ARTCC to ARTCC are discussed in some detail. We show that a very important factor in this performance is whether the Area Supervisors at an ARTCC have direct access to CIWS products. The paper concludes by discussing future plans for CIWS ATC productivity enhancement investigations.

Within the FAA Aviation Weather Research Program (AWRP), the Terminal Ceiling and Visibility Product Development Team (TC&V PDT) is responsible for development of forecast guidance products to mitigate the loss of terminal operating capacity associated with low ceiling and visibility restrictions. In particular, accurate anticipation of the onset and cessation of Instrument Meteorological Conditions (IMC) allows the opportunity for air traffic managers to effectively regulate traffic to utilize available capacity. The TC&V PDT approach is to develop forecast guidance solutions that are specific to individual high volume terminals that experience substantial loss of capacity. Due to the inter-hub dependencies of traffic flow, efficiency gains at individual key airports translate to a general reduction of total aircraft delay through the entire National Airspace System. The first key airport targeted was San Francisco International Airport (SFO). A system was developed to provide forecast guidance of the clearing time of stratus cloud that frequently restricts approach capacity during the summer months (Clark, 2002). This prototype system was transferred to the National Weather Service in 2004 (Ivaldi et al., 2006) The current focus of the Terminal C&V PDT is on ceiling and visibility restrictions associated with synoptic-scale transient weather systems that regularly impact the Northeast U.S. during the winter months, typically from November through April. The runway configuration and instrumentation at many of the major northeast terminals (Boston, New York Laguardia and Kennedy, Newark, Philadelphia, etc.) are very susceptible to IMC weather, resulting in a dramatic reduction in operating capacity. The multitude of phenomena contributing to IMC (e.g. frontal cloud shields, advection and radiation fog, precipitation of varying intensity and type, etc.) poses a difficult forecasting challenge. The Terminal C&V PDT is pursuing a variety of candidate technologies that will be integrated to provide a comprehensive solution. Trials of these forecast technologies are being developed using the NYC airspace as an experimental domain for both weather and operations. Development is progressing on two fronts: 1) improvement in the delivery of existing C&V information, and 2) development of new forecast technologies. The ultimate objective is integration of forecasts with operational information to provide a complete decision guidance tool. This paper introduces an experimental display tool and distribution mechanism for delivering C&V data and forecasts, focused on the NYC airspace. Initially, this tool relies on routinely available weather observations and forecasts. The intent of providing such a tool early in the product development stage is to engage the operational community (forecasters, dispatchers, and traffic managers) in the assessment and selection of candidate forecast technologies that are most appropriate for supporting operational decision making. During development, these technologies will be inserted into the display framework to evaluate their effectiveness in real time trials. An overview of the technologies under consideration is provided.

Air traffic in the United States is highly congested in its "Northeast Corridor", an area that roughly encompasses the airspace from Washington, DC to Boston. This region is frequently affected by low cloud ceiling and visibility conditions during the cool season, often in association with synoptic-scale low pressure systems. Operating under IFR (Instrument Flight Rules) for extended periods of time substantially reduces airport capacity and can cause significant delay at major airports. Anticipating transitions into and out of IFR ceiling and visibility conditions can mitigate air traffic disruption by allowing for appropriate upstream planning. For instance, an accurate forecast of the lifting of cloud ceiling out of IFR range would allow for the release of more planes upstream to take advantage of the anticipated increase in capacity. The Federal Aviation Administration (FAA), through its Aviation Weather Research Program (AWRP), is currently sponsoring the Northeast Winter Ceiling and Visibility Project (NECV). Its purpose is to provide situational awareness of current ceiling and visibility conditions in the Northeast United States in a way tailored to the needs of air traffic control (ATC), as well as to bring a number of various but complimentary technologies to bear on providing automated 0-12 hour forecasts of upcoming conditions. Methodologies currently under development include numerical weather prediction (NWP) applications, 1-dimensional column modeling, tracking of aviation-impacting cloud, and statistical forecast models (Clark 2006). This presentation describes the development of statistical forecast models for major New York City airports. The statistical forecast models use routine regional meteorological observations as predictors for future values of ceiling and visibility for selected locations. These predictors consist primarily of hourly surface observations, but upper air soundings and buoy data are available for use as well. The methodology for building the models is based on non-linear regression, with the nonlinearity entering in the spirit of Generalized Additive Models (Hastie and Tibshiriani 1990). Several innovations are introduced to aid in predictor selection and to enhance the skill and stability of the final models. Statistical models such as these have been successfully developed and used recently in an operational setting for ATC. The recently completed San Francisco (SFO) Marine Stratus Initiative (also sponsored by AWRP) features a real-time display and forecast system, which contains as one of its components a regional statistical forecast model (Wilson 2004, Clark et al. 2005). The model uses hourly surface observations from the San Francisco Bay area along with the Oakland sounding to produce regular forecasts of stratus dissipation during the warm season. The performance of this model during two years (May – October) of real-time operations is given in Table 1. The context for the marine stratus model differs from that for NECV in several important ways. In SFO, warm season stratus dissipation is a diurnal phenomenon, governed primarily by mesoscale and radiative processes in conjunction with local topography. The NECV problem is more affected by synoptic dynamics, and less by the diurnal component. This paper next provides a high-level summary of the methodology that has been developed to build these statistical forecast models followed by details of the initial NECV problem, including some discussion of the quality of the predictor data. Model accuracy can be improved by development over phenomenological partitions of the available cases; a method of partitioning the cases is described. The paper concludes with a discussion of near-term tasks.

Remote, oceanic regions have few, if any, high resolution weather products that indicate the current or future locations of aviation hazards such as volcanic ash, convection, turbulence, icing or adverse headwinds. Moreover, oceanic regions present unique challenges due to severely limited data availability, the long duration of transoceanic flights and the difficulty of transmitting critical information into the cockpit. In 2001, the Oceanic Weather Program Development Team (OWPDT; Herzegh et al. 2002) was organized within the Federal Aviation Administration (FAA) Aviation Weather Research Program (AWRP) to focus on resourceful methods for overcoming these limitations through the use of a diverse range of satellite observations, global model results and satellite-based communications. Resulting products focus on the needs of pilots, dispatchers, air traffic managers and forecasters within the oceanic aviation community. The team is a leader in the inflight display of weather products and will continue to develop new displays as products become available.

Three algorithms based on geostationary visible and infrared (IR) observations, are used to identify convective cells that do (or may) present a hazard to aviation over the oceans. The algorithms were developed at the Naval Research Laboratory (NRL), National Center for Atmospheric Research (NCAR), and Aviation Weather Center (AWC). The performance of the algorithms in detecting potentially hazardous cells is determined through verification based upon data from National Aeronautical and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) satellite observations of lightning and radar reflectivity, which provide internal information about the convective cells. The probability of detection of hazardous cells using the satellite algorithms can exceed 90% when lightning is used as a criterion for hazard, but the false alarm ratio with all three algorithms is consistently large (~40%), thereby exaggerating the presence of hazardous conditions. This shortcoming results in part from limitations resulting from the algorithms' dependence upon visible and IR observations, and can be traced to the widespread prevalence of deep cumulonimbi with weak updrafts but without lightning, whose origin is attributed to pronounced departures from non-dilute ascent.

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.