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Full-Text Articles in Meteorology
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Theses and Dissertations
Clustering weather data is a valuable endeavor in multiple respects. The results can be used in various ways within a larger weather prediction framework or could simply serve as an analytical tool for characterizing climatic differences of a particular region of interest. This research proposes a methodology for clustering geographic locations based on the similarity in shape of their temperature time series over a long time horizon of approximately 11 months. To this end an emerging and powerful class of clustering techniques that leverages deep learning, called deep representation clustering (DRC), are utilized. Moreover, a time series specific DRC algorithm …
Ccsfs/Ksc Total Lightning Warning Radii Optimization For Merlin Using Preexisting Lightning Areas, Kimberly G. Holland
Ccsfs/Ksc Total Lightning Warning Radii Optimization For Merlin Using Preexisting Lightning Areas, Kimberly G. Holland
Theses and Dissertations
The purpose of this research is to optimize lightning warning radii specifications for the 45th Space Wing (45 SW), thus reducing the number of unnecessary warnings that delay ground processing needed for space launch execution at Kennedy Space Center and Cape Canaveral Space Force Station. This thesis sought to answer two key research questions addressing: 1) What radius reduction effectively balances both safety and operations and do reduction recommendations from previous research align with results from the new detection system? 2) What insights can be gained from comparing measurement results for seasonal lightning events as well as lightning types? This …
Including Maximum Sustained Wind Speed In A Time Series Model To Forecast Hurricane Movement, Timothy B. Mott
Including Maximum Sustained Wind Speed In A Time Series Model To Forecast Hurricane Movement, Timothy B. Mott
Theses and Dissertations
Techniques for applying time series fundamentals to forecasting hurricane movement are thoroughly examined in this research. The objectives are: (1) to modify Dr. Thomas Curry's threshold autoregressive time series model to improve its ability to forecast hurricane movement, (2) to forecast the maximum sustained wind speed for a hurricane, and (3) to identify if wind speed should be included as an explanatory variable to aid in forecasting hurricane movement. Eleven different models to predict the latitude, longitude and maximum sustained wind speed are compared and contrasted with Curry's bivariate time series model. The results showed the modifications allow significant forecasting …