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Articles 1 - 13 of 13
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Ionospheric F-Layer Dipole Flute Instability Effects On Electromagnetic Scattering In A Magnetohydrodynamic Plasma, Andrew J. Knisely
Ionospheric F-Layer Dipole Flute Instability Effects On Electromagnetic Scattering In A Magnetohydrodynamic Plasma, Andrew J. Knisely
Theses and Dissertations
The ionosphere has significant impact on radio frequency (RF) applications such as satellites, over-the-horizon radar, and commercial communication systems. The dynamic processes effecting the behavior of the ionic content leads to a variety of instabilities that adversely affect the quality of RF signals. In the F-layer ionosphere, flute instability persists, appearing as two radial regions of high and low density perturbations elongated along the earth's geomagnetic field lines. The sizes of flute structures are comparable to the wavelengths in the high frequency spectrum. The objective is to characterize the high frequency scattering of an incident field by developing a 3D …
Relationship Between Solar Energetic Particle He/H Abundance Ratios And Properties Of Flares And Cmes, Christopher R. Davidson
Relationship Between Solar Energetic Particle He/H Abundance Ratios And Properties Of Flares And Cmes, Christopher R. Davidson
Theses and Dissertations
Previous studies have investigated the He/H elemental abundance ratios of Solar Energetic Particle (SEP) Events of energies above 4 MeV. Also, studies have investigated the correlations between SEPs, Coronal Mass Ejections (CME), and Solar Flares. This work finds the correlations between the >4 MeV He/H abundance ratios and the solar parameters from the SEP, CME, and solar flare associated with the abundance increases. 43 SEP events located at solar west longitude are analyzed to find the correlation coefficients. Highly significant correlation was found between the He/H abundance ratios and the following parameters: solar flare flux, solar flare fluence, CME linear …
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 …
Development And Verification Of Extreme Space Weather Phenomena Models, Sophia G. Schwalbe
Development And Verification Of Extreme Space Weather Phenomena Models, Sophia G. Schwalbe
Theses and Dissertations
A range of 14 M-class flares from 1 June 2015 to 27 September 2016 were analyzed to find significant trends in electron frequency profile modeling using the GLobal airglOW (GLOW) model and radar parameters using a ray tracing algorithm developed by the Air Force Research Laboratory. GLOW was run for all the flares using three different solar spectrum schemes and an average of the three: the Hinteregger method, EUV flux model for aeronomic calculations (EUVAC), and a rebinned Flare Irradiance Spectrum Model (FISM) result. Comparing data for the E-layer where GLOW is most accurate, it was determined that GLOW using …
Profiling Atmospheric Turbulence Using A Dynamically Ranged Rayleigh Beacon System, Steven M. Zuraski
Profiling Atmospheric Turbulence Using A Dynamically Ranged Rayleigh Beacon System, Steven M. Zuraski
Theses and Dissertations
The effect of turbulence on a long range imaging system manifest as an image blur effect usually quantified by the phase distortions present in a system. The blurring effect is conceivably understood on the basis of measured strength of atmospheric turbulence profiled within the propagation volume. One method for obtaining a turbulence strength profile is by use of a dynamically ranged Rayleigh beacon system that exploits strategically varied beacon ranges along the propagation path, effectively deducing estimates of specific path segment contributions of the blurring aberrations affecting an optical imaging system. A system utilizing this technique has been designed, and …
Improving Airfield Pavement Degradation Prediction Skill With Local Climate And Traffic, Evan M. Fortney
Improving Airfield Pavement Degradation Prediction Skill With Local Climate And Traffic, Evan M. Fortney
Theses and Dissertations
Airfield pavements are a critical component of the global transportation network that provide a platform for national defense. Preventative and corrective maintenance activities are founded upon accurate expectations of degradation. The leading pavement management software creates degradation predictions from pavement groups using age as the IV and current state conditions as the DV. For this work, a framework is created and implemented that utilizes a PCR model to build upon accepted practices for degradation modeling to enhance and possibly augment future prediction capabilities. The model was applied to pairs of location and pavement family and reveals several findings: the selected …
Synthetic Lightning Generation Employing Autoregressive-Moving-Average (Arma) Models, Seth R. Powers
Synthetic Lightning Generation Employing Autoregressive-Moving-Average (Arma) Models, Seth R. Powers
Theses and Dissertations
This work explores the question as to whether lightning data can be generated synthetically using vector autoregressive-moving-average (VARMA) models. Geostationary Lightning Mapper (GLM) data is used as the basis for the study. Lightning climatology is examined and compared to previous research to gain insight into the targeted areas. Individual lightning ashes are analyzed to inspect how well the process works on a smaller scale. Then, entire regions are evaluated to simulate lightning creation in a larger setting. Results suggest that the VARMA process employed is sufficient in generating synthetic lightning observations, largely dependent on the time and location of lightning …
Comparison Of Spatial Precipitation Forecasts With A Satellite Dataset, Andrew C. Siebels
Comparison Of Spatial Precipitation Forecasts With A Satellite Dataset, Andrew C. Siebels
Theses and Dissertations
The purpose of this research is to analyze and compare global precipitation data from the Climate Forecast System Version 2 (CFSv2) with the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)-Climate Data Record (CDR) to improve long term precipitation forecasting. The CFSv2 has a 0.5-degree resolution which will provide model data for precipitation forecasts. The PERSIANN-CDR is a satellite derived daily 0.25-degree dataset with 37 years of global precipitation coverage 60 N to 60 S. The 0-to-10, 15-to-25, 55-to-65, and 80-to-90 day forecast time frames will then be analyzed for accuracy, and a quantile mapping (QM) technique …
Climate-Informed Prediction And Forecast Modeling Of Installation Total Energy Consumption, Scott C. Weiss
Climate-Informed Prediction And Forecast Modeling Of Installation Total Energy Consumption, Scott C. Weiss
Theses and Dissertations
Climate variability is an external and stochastic factor that causes energy demand uncertainty. Energy managers can use climate-based models to understand future trends of energy demand and to adjust operations, policy, and budgets accordingly. This research focuses on 1) identifying how climate attributes impact energy use, 2) creating a historically informed statistical modeling framework to skillfully predict energy use, and 3) forecasting future changes to energy use and costs, using CMIP5 temperature projections, at the campus level. After synthesizing the existing breadth of research on climate-informed energy modeling, a skillful, unbiased, climate-informed total energy consumption prediction model is developed for …
Behavior Of Lightning In Developing Storms, Erick A. Tello
Behavior Of Lightning In Developing Storms, Erick A. Tello
Theses and Dissertations
Air Force weather squadrons issue a warning when lightning activity is observed within 5 nautical miles (NM) of protected areas. Upon receiving this warning, personnel outdoors are expected to pause work and move inside. Studies sponsored by the 45th Weather Squadron (45 WS) have concluded that the 5 NM warning radius can be safely reduced for well-developed storms. This thesis investigates whether radii for storms in early development can also be reduced. Our research develops algorithms to partition lightning sensor data into storms. Next, storms are filtered to their earliest lightning events, and the study calculates distances between successive early …
Correction Of Back Trajectories Utilizing Machine Learning, Britta F. Gjermo Morrison
Correction Of Back Trajectories Utilizing Machine Learning, Britta F. Gjermo Morrison
Theses and Dissertations
The goal of this work was to analyze 24-hour back trajectory performance from a global, low-resolution weather model compared to a high-resolution limited area weather model in particular meteorological regimes, or flow patterns using K-means clustering, an unsupervised machine learning technique. The duration of this study was from 2015-2019 for the contiguous United States (CONUS). Three different machine learning algorithms were tested to study the utility of these methods improving the performance of the CFS relative to the performance of the RAP. The aforementioned machine learning techniques are linear regression, Bayesian ridge regression, and random forest regression. These results mean …
Identifying Four Year Average Cloud Field Regimes From World Wide Merged Cloud Analysis Dataset By Way Of K-Means Clustering, Stewart G. Almeida
Identifying Four Year Average Cloud Field Regimes From World Wide Merged Cloud Analysis Dataset By Way Of K-Means Clustering, Stewart G. Almeida
Theses and Dissertations
Joint histograms of cloud top height (CTH) and optical depth (OD) are created using the World-Wide Merged Cloud Analysis (WWMCA) dataset over a four year period (2014-2017) to identify average cloud field regimes and assess the application of utilizing the WWMCA dataset with the AFIT Sensor and Scene Emulation Tool (ASSET). Two selected regions encompassing the Florida peninsula and a portion of the Pacific Ocean off the west-central coast of South America are examined over the months of January and July. Cloud field regimes are identified by running generated hourly OD-CTH histograms through k-means clustering, with optimal cluster number ( …
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 …