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Articles 1 - 7 of 7
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 …
Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan
Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan
Faculty Publications
Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined …
E700xd Portable Doppler Radar Energy Systems Analysis, Brandon M. Bailey [*], Torrey J. Wagner, Jada Williams
E700xd Portable Doppler Radar Energy Systems Analysis, Brandon M. Bailey [*], Torrey J. Wagner, Jada Williams
Faculty Publications
Occurring in industrialized nations, inexpensive and abundantly available power is routinely taken for granted. However, energy resilience and to a lesser extent price are key concerns when considering potential solutions for disaster response, disaster relief, or military operations. The Department of Defense (DoD) currently uses a 5 kW generator to power the E700XD portable Doppler radar system when grid power is unavailable [1]. While the radar has an approximate power consumption of 2.5 kW, there is a potential for higher demand due to weather conditions [2]. This paper examines the cost of operating a currently installed generator, compared to the …
Meeting The Dod’S Tactical Weather Needs Using Cubesats, Shayna K. Mckenney
Meeting The Dod’S Tactical Weather Needs Using Cubesats, Shayna K. Mckenney
Theses and Dissertations
This thesis investigates a CubeSat design that uses Commercial-Off-The-Shelf (COTS) components to capture, store, process, and downlink collected terrestrial weather data at resolutions near stat-of-the-art. The weather phenomena to be detected and transmitted in a timely manner are cloud formations, wind profiles, ocean currents, sea state, lightning, temperature profiles, and precipitation. It is hypothesized and shown that the proposed design will provide an improvement on the current U.S. tactical weather collection satellites because of the anticipated increased reliability and lowered cost to build and maintain the proposed CubeSat constellation. The methodology employed a multi-phase approach through the collective research of …
Data Warehouse Techniques To Support Global On-Demand Weather Forecast Metrics, Meriellen C. Joga
Data Warehouse Techniques To Support Global On-Demand Weather Forecast Metrics, Meriellen C. Joga
Theses and Dissertations
Air Force pilots and other operators make crucial mission planning decisions based on weather forecasts; therefore, the ability to forecast the weather accurately is a critical issue to Air Force Weather (AFW) and its customers. The goal of this research is to provide Air Force Weather with a methodology to automate statistical data analysis for the purpose of providing on-demand metrics. A data warehousing methodology is developed and applied to the weather metrics problem in order to present an option that will facilitate on-demand metrics. On-line analytical processing (OLAP) and data mining solutions are also discussed.
An Intelligent User Interface To Support Air Force Weather Product Generation And Automated Metrics, Darryl N. Leon
An Intelligent User Interface To Support Air Force Weather Product Generation And Automated Metrics, Darryl N. Leon
Theses and Dissertations
Air Force pilots require dependable weather reports so they may avoid unsafe flying conditions. In order to better gauge the accuracy of its weather products, Air Force Weather has established the requirement for an Air Force-wide automated weather metrics program. Under the guidelines for this program, forecasts will automatically be compared to observed weather to determine their accuracy. Statistics will be collected in the hopes of determining forecast error trends that can be corrected through education and training. In order for the statistical data produced by such a program to draw reliable conclusions about forecast accuracy, however, the correct format …