5.1
Forecast Aids to Lessen the Impact of Marine Stratus on San Francisco International Airport
F. Wesley Wilson, MIT Lincoln Laboratory, Lexington, MA; and D. A. Clark
San Francisco International Airport (SFIA) is unable to use independent parallel approaches to its closely-spaced parallel runways when marine stratus is present in the approach. Delay programs are imposed to regulate the flow of traffic to match the true arrival capacity of the airport. Failure to forecast accurately the times of onset and dissipation of stratus in the approach results in costly airborne holding and diversions, or in wasted capacity, as the traffic management planners fail to match the arrival rate to the actual airport capacity.
Four forecast algorithms have been developed, which predict the time of dissipation of summer Marine Stratus at SFIA. These algorithms are based on both dynamical and statistical analysis. In addition to operational data, these algorithms use information from special sensors that have been installed for this project: SODARs to measure the height of the inversion base, pyranometers to measure the intensity of the solar radiation at the surface, and time series of 10m winds, temperature, and humidity. The COBEL column model bases its forecast on explicit analysis of the evolution of the boundary layer, with special attention to radiation and cloud water. The COBEL initialization relies heavily on the special sensors. The other algorithms are based on statistical analysis. Each utilizes different data features. The Local Statistical Forecast Model (LSFM) relies primarily on trends in the project sensor data. The Regional Statistical Forecast Model (RSFM) relies on the standard regional surface hourly observations. The Satellite Statistical Forecast Model (SSFM) relies on trends in the regional GOES visible data. A consensus forecast algorithm is under development, which will integrate the forecasts from the individual algorithms.
These automated forecasts are intended for use as guidance by operational forecasters. Performance statistics indicate that each algorithm rivals the skill of the operational forecasts. An operational assessment is planned, in which the forecasters will evaluate these models and their value in the preparation of the operational forecasts.
Session 5, Forecasting and Evaluation/Verification (Parallel with Sessions 6 & 7)
Thursday, 14 September 2000, 8:00 AM-5:49 PM
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