Publications

The planning and execution of the Airport Acceptance Rate (AAR) for major metroplex airports is a complex and critical function of traffic managers in the National Airspace System (NAS). Despite the importance of AAR planning, traffic managers currently have no widely available decision support to provide guidance for runway selection and the determination of a sustainable AAR. The AAR Decision Support Capability (AARDSC), currently under development as part of the Collaborative Air Traffic Management Technology Work Package 4 (CATMT WP4), will provide such guidance. This report provides an initial analysis of the impacts of surface winds and winds aloft on the key factors associated with the AAR (the selection of runway configuration and aircraft ground speed and spacing on final approach) and the capabilities of currently available weather forecasts to accurately predict those impacts. The report was limited in scope by the schedule and available resources, and is intended as a foundation for a comprehensive forecast assessment in follow-on work. Surface wind forecasts from the Terminal Aerodome Forecast (TAF) and numerical prediction models (the High Resolution Rapid Refresh [HRRR], Rapid Refresh [RAP] and Rapid Update Cycle [RUC], collectively described as "MODEL") were compared to observed winds gathered from METAR reports as Newark International Airport (EWR). TAF and METAR were compared for 639 days of operations from 2011-2013. MODEL forecasts and METAR were compared for 21 days of operation, 16 of which had Traffic Management Initiatives (TMI) in place to mitigate adverse weather impacts. Winds aloft were translated into several wind impact metrics. The impacts of winds aloft forecast errors were evaluated by comparing impact metrics calculated from MODEL forecasts with those calculated from analysis fields for the 21 case days. Forecasts were evaluated at horizons of 2, 4, 6, and 8 hours.

Turbulence associated with wake vortices generated by arriving and departing aircraft poses a potential safety risk to other nearby aircraft, and as such this potential risk may apply to aircraft operating on Closely Spaced Parallel Runways (CSPRs). Aircraft separation standards are imposed to mitigate this potential risk. The FAA and NASA are investigating application of wind-dependent procedures for improved departure operations that would safely reduce spacing restrictions to allow increased airport operating capacity. These procedures are referred to collectively as Wake Turbulence Mitigation for Departures (WTMD). An important component of WTMD is a Wind Forecast Algorithm (WFA) developed by MIT Lincoln Laboratory. The algorithm is designed to predict when runway crosswind conditions will remain persistently favorable to preclude transport of aircraft departure wakes into the path of aircraft on parallel runways (Figure 1). The algorithm has two distinct components for predicting the winds at the surface (33 ft) and aloft up to 1000 ft (the altitude by which an alternate form of separation would be applied by Air Traffic Control to aircraft departing the parallel runways, typically 15 degree or greater divergence in aircraft paths). The surface component forecast applies a statistical approach using recent observations of winds from 1-minute ASOS observations. The winds-aloft component relies on the 2 to 4 hour wind forecasts from NCEP's Rapid Update Cycle (RUC) model. The baseline version of the algorithm was developed and tested using data from St. Louis Lambert International Airport (STL). Algorithm performance was evaluated using 1-minute ASOS observations and crosswind component measurements taken from a dedicated Light Detection and Ranging (LIDAR) system. The algorithm was also demonstrated and evaluated at Houston George Bush International Airport (IAH). Use of the WFA is planned for 8 other airports deemed likely to derive significant benefit from WTMD procedures. The operational concept of WTMD for use by Air Traffic Control (ATC) includes additional decision levels beyond the WFA forecast. These include a check for VFR ceiling and visibility conditions, and final enablement by a human controller. More details concerning WTMD can be found in Lang et al. (2005) and Lang et al. (2007). A more complete description of the WFA is given in Robasky and Clark (2008). The early history of WFA development is detailed in Cole and Winkler (2004).

Turbulence associated with wake vortices generated by arriving and departing aircraft pose a potential safety risk to other nearby aircraft, and as such this potential risk may apply to aircraft operating on Closely Spaced Parallel Runways (CSPRs). To take wake vortex behavior into account, current aircraft departing/landing standards require a safe distance behind the wake generating aircraft at which operations can be conducted. The Federal Aviation Administration (FAA) and National Aeronautics and Space Administration (NASA) have initiated an improved wake avoidance solution, referred to as Wake Turbulence Mitigation for Departures (WTMD). The process is designed to safely increase runway capacity via actively monitoring wind conditions that impact wake behavior (Hallock, et al., 1998; Lang et al., 2005). An important component of WTMD is a Wind Forecast Algorithm (WFA) being developed by MIT Lincoln Laboratory (Cole & Winkler, 2004). The WFA predicts runway crosswinds from the surface up to a height of approximately ~300 m (1000 ft) once per minute and thus forecasts when winds favorable for WTMD will persist long enough for safe procedures for a particular runway (Lang et al., 2007). The algorithm uses 1–4 hr wind forecasts from the Rapid Update Cycle (RUC) model operated by the National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction (NOAA/NCEP) for upper atmospheric wind profiles. Detailed description of the RUC model can be found elsewhere (Benjamin et al., 1994; 2004a; 2004b). Briefly, the RUC model inputs are assimilations of high frequency observations from a suite of meteorological sensors, including Automated Surface Observing System (ASOS), rawinsonde profiles, satellite, airborne sensors from commercial aircraft, etc. The vertical layers of the atmosphere are resolved approximately isentropically. The model is run hourly, producing hourly forecasts out to 24 hours. The coverage of the RUC grid includes the continental United States, southern Canada, northern Mexico, and adjacent coastal waters. Here we evaluate the performance of RUC in predicting crosswinds with reliability sufficient to support WTMD. For RUC validation, in situ wind profile data were obtained from a Light Imaging Detection and Ranging (LIDAR) deployed at St. Louis Lambert International Airport (STL). The focus of this study is to provide a general quantitative characterization of the difference between RUC predictions and LIDAR measurements of the runway crosswinds. Particular attention was given to cases with inaccurate RUC crosswind forecasts, and cases when significant horizontal and vertical shears occur during situations of convective weather or proximity to large scale weather features, e.g., air mass fronts. (In practice, WTMD procedures and existing weather sources in the Control Tower will manage, to an acceptable level of risk, the hazard exposure associated with the extreme wind shift examples presented here.) Also included was examination of performance degradation with longer RUC forecast horizons and coarser horizontal resolutions, which may be relevant with regard to actual operational forecast data availability, or future applications of the operational concept to include arrival operations. A detailed report for this study is also available (Huang et al., 2007).

San Francisco International Airport (SFO) experiences frequent low ceiling conditions during the summer season due to marine stratus clouds. Stratus in the approach zone prevents dual approaches to the airport??s closely spaced parallel runways, effectively reducing arrival capacity by half. The stratus typically behaves on a daily cycle, with dissipation occurring during the hours following sunrise. Often the low ceiling conditions persist throughout the morning hours and interfere with the high rate of air traffic scheduled into SFO from mid-morning to early afternoon. Air traffic managers require accurate forecasts of clearing time to efficiently administer Ground Delay Programs (GDPs) to match the rate of arriving aircraft with expected capacity. The San Francisco Marine Stratus Forecast System was developed as a tool for anticipating the time of stratus clearing. The system relies on field-deployed sensors as well as routinely available regional surface observations and satellite data from the Geostationary Operational Environmental Satellite (GOES-West). Data are collected, processed, and input to a suite of forecast models to predict the time that the approach zone will be sufficiently clear to perform dual approaches. Data observations and model forecasts are delivered to users on an interactive display accessible via the Internet. The system prototype was developed under the sponsorship of the FAA Aviation Weather Research Program (AWRP). MIT Lincoln Laboratory served as technical lead for the project, in collaboration with San Jose State University, the University of Quebec at Montreal, and the Center Weather Service Unit (CWSU) at the Oakland Air Route Traffic Control Center (ARTCC). The National Weather Service (NWS), under the direction of the NWS Forecast Office in Monterey, assumed responsibility for operation and maintenance of the system following technical transfer in 2004. This document was compiled as a resource to support continuing system operation and maintenance.

The Federal Aviation Administration (FAA) is sponsoring a Terminal Ceiling and Visibility (C&V) initiative to provide automated C&V guidance to the air traffic managers for both tactical (0-2 hour) and strategic (3-12 hour) decision making. To meet these requirements, particularly in the strategic time frame, it will most likely be necessary for the C&V system to incorporate guidance from an explicit numerical weather prediction (NWP) model. If NWP forecasts are found to be suitable for this application, they will be used as the backbone of the terminal C&V forecast system. More details on the terminal area C&V forecast product development for the FAA can be found in Allan et al. (2004). Before these NWP forecast products can be used, it is necessary to first characterize their accuracy relative to operational air traffic control (ATC) requirements. This makes it possible to exploit observed strengths, avoid weaknesses, and facilitate a better utilization of NWP forecast products. This study provides an assessment tailored specifically to address the terminal C&V application. Consequently, the results represent forecast performance for relatively small geographic locations that for practical purposes can be considered point forecasts. It is our intention to answer four questions with this preliminary analysis: 1. How accurate are the NWP forecasts relative to the observational truth and a human generated forecast? 2. For the terminals of interest to this study (i.e. New York City Airports), are there any advantages to utilizing a non-hydrostatic mesoscale model run at horizontal resolutions of 3 km or less? 3. Do the NWP models exhibit forecast skill for non-traditional forecast metrics such as trends in C&V parameters and timings of threshold crossings associated with the onset and clearing of low ceiling and visibility conditions? 4. Are there obvious situations/conditions during which the NWP forecasts have more/less skill? In addition to a report on the NWP terminal ceiling and visibility forecast accuracy, we provide preliminary recommendations on the direction we feel this line of research should pursue, and where we see opportunities to utilize NWP forecasts in an automated terminal C&V decision guidance system. An ancillary goal of this study is to assemble the analysis software infrastructure required to quantitatively evaluate numerical forecast accuracy. We envision using these tools to develop and test modifications to the translation algorithms and techniques that will be necessary to integrate the NWP forecasts into the C&V guidance system. They will be instrumental in reducing the time required to make engineering turns during the upcoming development and implementation stages of this research.

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.

Wind shear detection algorithms that operate on Doppler radar data are tuned to primarily recognize the velocity and reflectivity signatures associated with microbursts and gust fronts. Microbursts produce a divergent pattern in the velocity field that is associated with a descending column of precipitation. Gust fronts produce a convergent pattern that is often associated with a thin-line reflectivity feature. On April 12, 1996 at Dallas-Fort Worth International Airport (DFW) three pilots reported encounters with wind shear in a five minute period (2329-33 GMT). The third pilot (AA 1352) reported an encounter with "severe wind shear", which we refer to as "the incident" throughout the paper. He used maximum throttle to keep the MD-80 in the air and reported that it was only "by the grace of God" that the aircraft did not crash (Dallas Morning News, 4/19/96). The plane, originally bound for Pittsburgh, was diverted to Tulsa where the passengers were offloaded to another aircraft, the black box was removed, and the engines were checked according to procedures required whenever maximum throttle is utilized.

The Runway Wind Nowcast Product will support the ITWS objective by providing short term (up to 30 minutes) forecasts of the tailwind and crosswind components of the horizontal wind over each runway at an ITWS airport. These forecasts will enable FAA users to better anticipate wind shifts impacting runway usage and trajectories of approaching and departing air traffic. They may also support future ITWS products such ceiling and visibility nowcasts. Our initial development efforts, which are reported here, have been directed toward Orlando International Airport (MCO) as the product request originated there. However, in the near future we plan to expand the scope to include other ITWS airports including Memphis. The Runway Wind Nowcast Product is being developed to help Air Traffic Control (ATC) personnel answer the following question: Do we need to change runways? That would become necessary if tailwinds or crosswinds exceed usage thresholds. At most US airports, with dry runways, tailwinds much be less than five knots and crosswinds must be less than 15 knots. Other, lower thresholds apply if the runways are wet. However, these thresholds are subject to local modifications. For example, the MCO tailwind threshold for dry runways is 7 knots. The decision faced by ATC personnel seems, at first, to be clear cut: if the tailwind or crosswind exceeds nominal thresholds, use of that runway must be discontinued. The problem (at least at MCO) is that most threshold crossings are very brief. So, it may be better to temporarily hold traffic than to switch runways. Reliable (i.e., accurate and precise) short term forecasts will help ATC personnel make better hold-or-switch decisions.