Publications

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.

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.