Publications

The FAA Aviation Weather Research Program (AWRP) is an initiative of the Weather and Flight Service Systems Integrated Product Team, AUA400. One of the goals of the AWRP is to create accurate and accessible forecasts of hazardous weather tailored to the needs of the aviation community. Pursuant to this goal, the AWRP has sponsored the collaboration of the Research Applications Program (RAP) of the National Center for Atmospheric Research (NCAR), the Aviation and Forecast Research Divisions at the NOAA Forecast Systems Laboratory (FSL), the Weather Sensing Group of the Massachusetts Institute of Technology's Lincoln Laboratory (MIT/LL) and the National Severe Storm Laboratory (NSSL) on a Product Development Team (PDT). This Convective Weather PDT is developing an automated system that combines real-time weather- radar data with the current "state-of-the-art" convective weather prediction algorithms to produce forecasts of convective weather for the heavily traveled air traffic routes in the Great Lakes/Northeast corridor (Chicago to New York). This Regional Convective Weather Forecast (RCWF) will be provided to traffic flow management decision-makers as part of the proof-of-concept Corridor Integrated Weather System (CIWS), which began operations in July 2001 with a l-hr animated Regional Convective Weather Forecast (RCWF).

Over the past decade the United States has seen drastic increases in air traffic delays resulting in enormous economic loses. Analysis shows that more then 50% of air traffic delays are due to convective weather. In response the FAA has assembled scientific and engineering teams from MIT Lincoln Laboratory, NCAR. NSSL, FSL and several universities to develop convective weather forecast systems to aid air traffic managers in delay reduction. A user-needs study conducted by Lincoln Laboratory identified that a major source of air traffic delay was due to line thunderstorms (Forman et al., 1999). Recognizing that the line storm envelope motion was distinct from the local cell motion was the impetus for developing the Growth and Decay Storm Tracker' (Wolfson et al., 1999). The algorithm produces forecasts by extracting large-scale features from two dimensional precipitation images. These images are tracked, using either correlation techniques (Terminal Convective Weather Forecast or TCWF) or centroid techniques (National Convective Weather Forecast or NCWF). In TCWF, the track vector field is used to advect the current precipitation images formed to produce a series of forecasts into minute increments up to 60 minutes. The TCWF forecasts are highly skilled for large scale persistent line storms. However, detailed performance analysis of the algorithm has shown that in cases dominated by airmass storms, the algorithm occasionally performed poorly (Theriault et al., 2001). In this paper we describe the sources of error discovered in the TCWF algorithm during the Memphis 2000 performance evaluation, and describe recent enhancements designed to address these problems.

This report describes a formal Assessment of the Terminal Convective Weather Forecast (TCWF) algorithm, developed under the FAA Aviation Weather Research Program by MIT Lincoln Laboratory as part of the Convective Weather Product Development Team (PDT). TCWF is proposed as a Pre-Planned Product Improvement (P3I) enhancement to the operational ITWS currently scheduled for deployment at major airports in 2002. The TCWF Assessment in Memphis, TN ran from 24 March to 30 September 2000. The performance of TCWF was excellent on the large scale, organized storm systems it was designed to predict, and the software was extremely stable during the Assessment. Small changes to the algorithm parameters were made as a result of the 2000 testing. The TCWF performance can be improved on airmass storms and on forecasting new growth and subsequent decay of large-scale storms. These are active areas of research for future ITWS P3I builds.

Air traffic delay due to convective weather reached historically high levels in 1999, as passengers blamed airlines and airlines blamed the FAA for the massive inconveniences. While coordination between the FAA's System Command Center and the regional centers and terminals can be expected to improve with the FAA's new initiatives, it is clear that air traffic management and planning during convective weather will ultimately require accurate convective weather forecasts. In addition to improving system capacity and reducing delay, convective forecasts can help provide safer flight routes as well. The crash of a commercial airliner at Little Rock, AR in June 1999 after a one-hour flight from Dallas/Ft. Worth illustrates the dangers and potential tactical advantage that could be gained with frequently updated one-hour forecasts of convective storms. The Terminal Convective Weather Forecast (TCWF) product has been developed by MIT Lincoln Laboratory as part of the FAA Aviation Weather' Research Convective Weather Product Development Team (PDT). Lincoln began by consulting with air traffic personnel and commercial airline dispatchers to determine the needs of aviation users (Forman, et. al., 1999). Users indicated that convective weather, particularly line storms, caused the most consistent problems for managing air traffic. The "Growth and Decay Storm Tracker" developed by Wolfson et al. (1999) allows the generation of up to 1-hour forecasts of large scale, organized precipitation features with operationally useful accuracy. This patented technology. represents a breakthrough in short-term forecasting capability, providing quantitative envelope tracking as opposed to the usual cell tracking. This tracking technology is now being utilized in NCAR's AutoNowcaster (Mueller, et al., 2000), the National Convective Weather Forecast running at the Aviation Weather Center (Megenhardt, et al., 2000) and by private sector meteorological data vendors. The TCWF has been tested in Dallas/Ft. Worth (DFW) since 1998, in Orlando (MCO) since 1999, and in New York (NYC) since fiscal year 2000 began. These have been informal demonstrations, with the FAA William J. Hughes Technical Center (WJHTC) assessing utility to the users, and with MIT LL modifying the system based on user feedback and performance analyses. TCWF has undergone major revisions, and the latest build has now been deployed at all sites. The TCWF is now in a formal assessment phase at the Memphis international Airport as a prerequisite to an FAA operational requirement. The FAA Technical Center will make a recommendation on whether TCWF is suitable for inclusion in the FAA's operational integrated Terminal Weather System (ITWS), which has an unmet requirement for 30+ minute forecasts of convective weather. Memphis was selected for the TCWF Assessment since it has not been exposed to the forecast product during prior demonstrations. Operations began on March 24, 2000 and operational feedback is being assessed by the FAA Technical Center (McGettigan, et al., 2000) and MCR Corporation is performing a quantitative benefits assessment (Sunderlin and Paull, 2000). This paper details the refined TCWF algorithm and display concept, gives examples of the operational impact of terminal forecasts, and analyzes the technical performance of the TCWF during the early stages of the Memphis Assessment.

A large percentage of serious air traffic delay at major airports in the warm season is caused by convective weather. The FAA Convective Weather Product Development team (PDT) has developed a Terminal Convective Weather Forecast product (TCWF) that can account for short-term (out to 60 min) systematic growth and decay of thunderstorms. The team began work three years ago by evaluating air traffic user needs and requirements. We found that users were willing to trade off forecast accuracy for longer lead times, especially for air traffic management plans that were easy to implement or that incurred low risk (Forman, et al., 1999). The PDT was able to develop an operationally useful forecast product that has been demonstrated in Dallas, TX since March, 1998 (Hallowell, et al., 1999). Further improvements have been made, and testing is now taking place at both Dallas and Orlando, FL. This paper summarizes the basic algorithm methodology and presents quantitative results on optimization of the scale separation filter, which is an integral aspect of the forecast algorithm.