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An Evaluation of Microburst Prediction Indices for the Kennedy Space Center and Cape Canaveral Air Station63,99 €![Using the WSR-88D to Forecast Downburst Winds at Cape Canaveral Air Station and the Kennedy Space Center]( "Using the WSR-88D to Forecast Downburst Winds at Cape Canaveral Air Station and the Kennedy Space Center")
Using the WSR-88D to Forecast Downburst Winds at Cape Canaveral Air Station and the Kennedy Space Center63,99 €![Use of Climatology to Predict Maximum Wintertime Wind Speeds at the Kennedy Space Center and Cape Canaveral Air Station]( "Use of Climatology to Predict Maximum Wintertime Wind Speeds at the Kennedy Space Center and Cape Canaveral Air Station")
Use of Climatology to Predict Maximum Wintertime Wind Speeds at the Kennedy Space Center and Cape Canaveral Air Station63,99 €![The Horizontal Extent of Cloud-to-Ground Lightning over the Kennedy Space Center]( "The Horizontal Extent of Cloud-to-Ground Lightning over the Kennedy Space Center")
The Horizontal Extent of Cloud-to-Ground Lightning over the Kennedy Space Center64,99 €![Predicting Launch Pad Winds at the Kennedy Space Center with a Neural Network Model]( "Predicting Launch Pad Winds at the Kennedy Space Center with a Neural Network Model")
Predicting Launch Pad Winds at the Kennedy Space Center with a Neural Network Model64,99 €![Improving Cape Canaveral's Next-Day Thunderstorm Forecasting Using a Meso-Eta Model-Based Index]( "Improving Cape Canaveral's Next-Day Thunderstorm Forecasting Using a Meso-Eta Model-Based Index")
Improving Cape Canaveral's Next-Day Thunderstorm Forecasting Using a Meso-Eta Model-Based Index64,99 €![Forecasting Fuel Consumption Requirements for the Air Force Flying Hour Program Using Pooled Time Series Analysis]( "Forecasting Fuel Consumption Requirements for the Air Force Flying Hour Program Using Pooled Time Series Analysis")
Forecasting Fuel Consumption Requirements for the Air Force Flying Hour Program Using Pooled Time Series Analysis63,99 €
The focus of this research effort is directed toward identifying new methods of forecasting the cessation of lightning along the Central Atlantic Coast of Florida. Cloud-to-ground lightning flashes place Air Force (AF) personnel and assets at risk almost daily at this location. Providing a more accurate method of forecasting the cessation of lightning would allow for safer and more efficient execution of AF operations. A data set consisting of 40 thunderstorm cases was identified within a 90 nautical miles (nmi) region surrounding the Melbourne, Florida WSR-88D (KMLB) site. Each case falls between the months of May and September and the years of 1995 through 1997. Simple and multiple linear regression models are built using this dataset. Variables included max Vertically Integrated Liquid water (VIL), max reflectivity, max peak current, peak cumulative flash rate, peak negative flash rate, and peak positive flash rate. Results indicate that three of the simple linear regression models to some extent accurately represent the data. Additionally, when the data set is separated by thunderstorm cell type (multi or single) and cell specific regressions are built, results indicate that the regressions based on the single-cell data set produce a substantial increase in forecast skill compared to that of climatology. In fact, some regressions are shown to improve forecast accuracy by 90 % over that of climatology. Moreover, multiple linear regression models are shown to produce similar results and further reinforce the notion that each thunderstorm cell type (multi or single) behaves substantially different from the other with respect to forecasting the cessation of lightning.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.