Publications

The Integrated Terminal Weather System (ITWS) is one of two major development projects sponsored by the FMs Aviation Weather Development Program. Focused on the environment within the airport terminal area, ITWS integrates data from FAA and National Weather Service (NWS) sensors and systems to provide a suite of weather informational products for improving air terminal planning, capacity, and safety. This article provides an overview of the ITWS project, presenting the system concept, some of the design and engineering challenges, and plans for development that will lead to operational systems in the field.

The Federal Aviation Administration (FAA) is sponsoring the development of the Integrated Terminal Weather System (ITWS), which is designed to acquire all of the weather data that is available in the terminal area, both ground-based and aircraft sensed, and to provide short-term (0 to 30-minute) predictions of microbursts, wind shear, gust fronts, runway winds and terminal-area ceiling and visibility. Additionally, the ITWS will be generating the 4-dimensional wind field at many levels in the terminal area, mainly for use by other FAA terminal air traffic control automation systems, but also available as a graphical display. An area of interest and concern to the developers is the interaction between the automated, very-short-term predictions of the ITWS, and the National Weather Service (NWS) aviation meteorologist, who is responsible for issuing terminal forecasts and other aviation advisory and warning products. This paper will describe the ITWS as currently planned and will explore the possible relationships between the ITWS and the NWS forecaster. Consideration will also be given to the NWS's new Advanced Weather Interactive Processing System (AWIPS) and how ITWS information might be used in the terminal forecasting process. This paper is intended to spark discussion of the role of the ITWS in the NWS forecasting process of the future.

Lincoln Laboratory is developing a prototype of the Federal Aviation Administration (FAA) Integrated Terminal Weather System (ITWS) to provide improved aviation weather information in the terminal area by integrating data and products from various FAA and National Weather Service (NWS) sensors and weather information systems. The ITWS Microburst Prediction product is intended to provide and additional margin of safety for pilots in avoiding microburst wind shear hazards (Fig. 1). The product is envisioned for use by traffic managers, supervisors, controllers, and pilots (directly via datalink). Our objective is to accurately predict the onset of microburst wind shear several minutes in advance. The approach we have chosen in developing the ITWS Microburst Prediction algorithm emphasizes fundamental physical principles of thunderstorm evolution and downdraft development, incorporating heuristic and/or statistical methods as needed for refinement. Image processing and data fusion techniques are used to produce an "interest" image (Delanoy etal., 1991, 1992) that reveals developing downdrafts. We use Doppler radar data to identify regions of growing thunderstorms and probable regions of downdraft, and combine these with measures of the ambient temperature structure (height of the freezing level, lapse rate in the lower atmosphere; Wolfson 1990), total lightning flash rate, and storm motion to predict the microburst location, timing, and outflow strength. There is also a simple feedback system based on the results of the Microburst Detection algorithm that desensitizes prediction thresholds if false predictions are being reported. The following slides describe the preliminary ITWS Microburst Prediction algorithm design, and show examples of feature detector, and the algorithm output on one test case. Results from off-line testing on 17 days of data from Orlando are also presented.

In this communication we described how, with nonuniform sampling, the concept of bandlimited extrapolation can be used to obtain unambiguous Doppler velocity estimates in the supra-Nyquist region. The proposed method coherently processes a multi-PRI sample using a generalized form of periodogram analysis. The work is described in the context of meteorologic Doppler processing and includes a discussion of effective suppression for stationary ground clutter when multi-PRI schemes are used.

The Federal Aviation Administration's Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

An important part of the FAA Aviation Weather Development Program is a system, the Integrated Terminal Weather System (ITWS), that will acquire data from the various FAA and National Weather Service (NWS) sensors and combine these with products from other systems (e.g., NWS Weather Forecast Offices and the FAA Aviation Weather Products Generator). This wide variety of input data and products will enable the ITWS to provide a unified set of weather products for safety and planning/capacity improvement for use in the terminal area by pilots, controllers, terminal area traffic managers, airlines, airports, and terminal automation systems (e.g., Terminal Air Traffic Control Automation (TATCA) Center Tracon Advisory System (CTAS) [Andrews and Welch, 1989] and wake vortex advisory systems.

Flight crews need tiimely information about terminal weather conditions when approaching or departing airports. This paper describes a new concept in providing this information from new ground-based terminal weather sensors currently being deployed via new and existing data link systems. Currently, pilots rely on ATIS (Automatic Terminal Information System) for airport weather conditions. However, the Surface Observation (SAO) contained in the ATIS message is nominally only updated once per hour. Special observations are issued more frequently, but are difficult to keep current manually in rapidly changing conditions. The Automated Surface Observing System (ASOS) and Automated Weather Observing Systems (AWOS) are beginning to supplant manual surface observations in many locations. These automated systems offer the advantage of providing continuous , automated surface observations. However, the surface observations issued by these units lack the remarks section provided by manual observers, including such information as the location and motion of storm activity in the airport area. The shortcomings of the current ATIS system were illustrated by an incident at Kansas City International Airport (MCI) in the evening of September 8, 1989. An aircraft approaching from the west received an ATIS message indicating 10 miles visibility at the airport. However, unknown to the crew, an intense storm was approaching the airport from the East. By the time the aircraft reached the airport (about 30 minutes after the initial ATIS message was received), the visibility had dropped to 1/2 nmi, but the flight crew was not notified. The aircraft subsequently struck power lines while on final approach and was forced to make an emergency landing at an alternate airport. This example provides a vivid example of current shortcomings in the generation and dissemination of terminal weather information to the flight deck. Besides improving safety, improved access to terminal weather information would provide economic benefits by allowing more efficient flight planning and utilization of air space.

The Meteorological Data Collection and Reporting System (MDCRS) was designed for the Federal Aviation Administration (FAA) and the National Weather Service (NWS) to collect, decode, store and disseminate aircraft meteorological observations. The system, targeted primarily at improving upper air wind forecasts, was fielded in 1991.

Low level wind shear has been identified as a cause or contributing factor in a significant number of aviation accidents. Research has shown that the most dangerous type of wind shear is the microburst (Fujita, et al., 1977 and 1979). Briefly, a microburst is an intense local downdraft that results in a strong divergent outflow near the surface. The diameter of the outflow region may vary from 3 to 10 Km. Although many of these accidents were nonfatal, six of them resulted in a total of 550 lives lost. During the past 17 years, the mainstay of the effort by the Federal Aviation Administration (FAA) to provide wind shear warnings to pilots has been the Low Level Wind Shear Alert System (LLWAS). The system has been redesigned, based on extensive operational experience and new knowledge about the nature of the aviation wind shear hazard (Goff and Gramzow, 1989). In parallel development, the Terminal Doppler Weather Radar (TDWR) has provided a capable alternative for ground-based microburst detection (Turnbull, et al., 1989). Recent studies on the integration of LLWAS with TDWR have established the value of a combined TDWR/LLWAS wind shear detection system (Cole and Todd, 1993) The LLWAS system is being developed in four phases, I, II, III, and IV, which reflect the chronology of operational deployments. The original LLWAS, now called LLWAS I, was designed for the detection of frontal shears under the assumption that hazardous wind shear is associated with large-scale meteorological features (Goff and Gramzow, 1989). This system was deployed at 110 airports between 1977 and 1987. LLWAS I had no microburst detection capability and had excessive false alerts. LLWAS II was developed to reduce the false alert rate of LLWAS I and to provide a modest microburst detection capability. It is a direct response to recommendations by the National Research Council (NRS-NAS, 1983), following the 1982 microburst crash in New Orleans. This upgrade, deployed by modifying the software in LLWAS I, provided an improvement that would not suffer the delays and costs of the major construction that is required for off-airport LLWAS III sensors. These upgrades to LLWAS I were installed between 1988 and 1991. LLWAS II will be the operational wind shear detection system at many airports until the late '90s. LLWAS III was developed in response to the requirements that LLWAS have a microburst detection capability (NRS-NAS, 1983). This system was designed by a combination of computer simulation studies (Wilson and Flueck, 1986) and a successful field test of a prototype at Stapleton International Airport, Denver in Augist 1987 (Smythe, et al., 1989 and Wilson et al., 1991). LLWAS III combines a dense sensor network and a sophisticated Wind Shear/Microburst (WSMB) detection algoritohm to provide a substantial microburst detection capability. The prototype LLWAS III has continued to operate at Stapleton International Airport, Denver since 1987 and has been credited with the "save" of a commercial airliner on July 8, 1989. Nine LLWAS IIIs are being installed this year. LLWAS IV will be deployed at 83 airports in the late '90s. The LLWAS IV wind shear and microburst detection algorithms will be identical to LLWAS III. This system features a full hardware upgrade. Major imporvements include an ice-free sensor and hardware that is more reliable and maintainable. This report provides an evaluation of the effectiveness of LLWAS II and LLWAS III. The TDWR operational test bed at Orlando International Airport, Orlando (MCO) provides a unique data set for this evaluation. This test-bed features data from a 14-sensor LLWAS, the prototype TDWR, FL-2C, operated by MIT/LL, and the University of North Dakota meteorolgical radar (UND). Data from this test bed in the summers of 1991 and 1992 are used to provide an evaluation of LLWAS II and LLWAS III. Since LLWAS IV uses the same wind shear detection algorithm, it is expected that LLWAS III and LLWAS IV will have comparable wind shear detection capabilities.

We present an overview of the product development strategy and discuss some of the technical considerations. It will be necessary to overcome significant scientific challenges in order to be successful. Our optimism comes from the improved operational meteorological data in the terminal area, from the ability to access and to process these data rapidly, and from ongoing advances in data assimilation for mesoscale models. Our role is to coordinate the fusion of these technical and scientific advances into operational aviation weather products and to evaluate the effectiveness of these products. Major scientific contributions are anticipated from the Forecast Systems Laboratory (FSL), the National Center for Atmospheric Research (NCAR), Pennsylvania State University, and Colorado State University.