Meteorology Commons^™

Regional Variability In Tornado Tracks: A Gis-Based Study Of Surface Roughness And Land Cover Differences Between The Lower Midwest And Southeast United States, Joshua Morgan Dison

Theses and Dissertations

Throughout the years, much research has been dedicated to the physical processes leading to tornadogenesis and tornado decay. Much of this research is centered around the inner workings of the supercell itself. Recent studies are now showing that tornadogenesis and decay processes may be generated by interactions with the Earth’s surface. This study examines longtrack tornadoes from 2001-2016 in the southeast and lower Midwest regions of the United States. Utilizing the National Land Cover Database (NLCD) and American Meteorological Society / Environmental Protection Agency / Regulatory Model (AERsurface) surface roughness values, efforts are made to see if statistical significance is …

Understanding How Nws Meteorologists Tailor Hazardous Weather Messaging To Core Partners And Identify Local Vulnerabilities, Allison Camille Harvey

Theses and Dissertations

Over the past few decades, the National Weather Service (NWS) has continued to improve impact-based decision support services (IDSS) efforts to strengthen communication with core partners. This study addressed how a new spatially hazard-specific vulnerability tool called the Brief Vulnerability Overview Tool (BVOT) may impact how NWS meteorologists tailor messaging to their core partners. It was found that relationship building between NWS meteorologists and core partners is key to enhancing trust, especially during blue sky days. This was done by learning core partners’ needs, thresholds, and communication styles when presenting weather information. Core partners also noticed cues from NWS meteorologists …

Exploring The Use Of A Random Forest In Correcting Gfs Tropical Cyclone Landfall Errors, Victoria Grace Maxwell

Theses and Dissertations

While Tropical Cyclone (TC) track forecasting has improved over the years it has been slow. These improvements can be attributed to increased computer capability and better model inputs. Machine learning has been used for forecasting different TC track and intensity. The study here looks to use a Random Forest to predict the TC latitude/longitude “landfall” at 72-hr and quantify improvements to the GFS forecast. Principal Component Analysis was used to reduce the dimensionality of the meteorological variables. Stepwise regression was used to determine the principal components that were important for forecasting landfall. These variables were then tested with a multivariate …

Atmospheric Turbulence Education Effects On Flight Anxiety, Megan A. Hanna

Theses and Dissertations

This study examines the effect of turbulence education on flight anxiety. A pre-post methodology measured students’ anxiety levels before and after a study abroad flight, using an educational video during the pre-flight survey to change their feelings. The Flight Anxiety Situations (FAS) questionnaire assessed anxiety at three survey points: pre-video, post-video, and post-flight. Qualitative analysis using Friedman’s test and the Wilcoxon Signed-rank test, indicated that turbulence education effectively decreased generalized and anticipatory flight anxiety, particularly in non-phobic students. Text analysis of open-ended responses suggested increased scientific knowledge post-video helped students apply technical atmospheric processes to their feelings. Turbulence education was …

Evaluating Rainfall Sensitivity Over Land To Tropical Cyclone Parameters Using Idealized Wrf, Madison C. Yawn

Theses and Dissertations

Tropical cyclones (TCs) are extreme weather events impacting the United States nearly every year. These events often cause severe damage due to the associated responses they produce including storm surge and rainfall, and the accurate estimation of these TC hazards is necessary to support coastal engineering, risk assessment, and emergency management activities. Evaluating TC-driven hazards is often done in combination with numerical models to simulate how environmental interactions alter the physical processes and responses of these storms. The purpose of this study was to simulate synthetic TC events using the Advanced Weather Research and Forecasting (WRF) model to understand how …

Real-Time Enhanced Tornado Warning Product Guidance Based On Tornado Debris Signature Height And Population Density, Alexander Cooke

Theses and Dissertations

This research aims to develop an operational program for enhancing real-time tornado warning capabilities by integrating tornado debris signature (TDS) analysis with population impact assessment. The proposed Python-based tool will ingest Level II radar data to identify and analyze TDS, estimating tornado intensity based on maximum TDS height. For high-intensity tornadoes, the program will project the potential impact area using storm motion vectors and integrate this with population density data. The system will assess whether the situation meets National Weather Service criteria for enhanced warning products, providing forecasters with rapid, objective guidance for critical warning decisions. The program’s performance will …

Influence Of Horizontal Grid Spacing On Numerical Weather Prediction Simulations Of Clear Air Turbulence, Kailah Rose Gordon

Theses and Dissertations

The focus of this research was to analyze the influence of horizontal grid spacing on numerical simulations of kinetic and thermal forced clear air turbulence (CAT) by quantifying uncertainty using a resolution ensemble. Previous studies indicated that microscale (< 1km) spatial resolutions are necessary to resolve turbulent kinetic energy (TKE) with low uncertainty. Six case studies of moderate or greater CAT, from pilot reports, were simulated at six horizontal grid spacings including 1, 2, 4, 8, 16, and 32km using the Weather Research and Forecast (WRF) Model. Results showed that grid spacing does influence the magnitude of uncertainty; however, the relationship between the grid spacings varied with the type of CAT being simulated and the addition of the cumulus parameterization scheme for grid spacings greater than 4km. Overall, higher precision was found between convective resolutions (1-4km), indicating that microscale resolutions are not necessary to precisely simulate TKE for CAT forecasts.

The Role Of Enso Diversity In Modulating Tornadic Activity In The United States, Davis Boyd Newton

Theses and Dissertations

Tornado activity in the United States is influenced by large-scale climate patterns, especially by the El Niño-Southern Oscillation (ENSO). While prior research has explored ENSO’s impact on severe weather, the influence of ENSO flavors, Central Pacific (CP) and Eastern Pacific (EP), on tornadic activity remains understudied. Using tornado records, reanalysis data, and sea surface temperature anomalies, we assess how convective available potential energy (CAPE), wind shear, and jet stream dynamics influence tornado frequency and distribution. Results indicate that CP La Niña years had significant increases in tornado frequency, particularly across the Midwest, Central Plains, and Southeast. EP ENSO years had …

Integrating Case Studies With Meteorologists’ Insight: Assessing Meteorologists’ Perception And Utilization Of Composite Indices, Brianna Marie Salazar

Theses and Dissertations

Meteorologists from sectors, including broadcast, academia, and operations, use derived composite indices such as 0-1km and 0-3km energy helicity index (EHI), effective-layer supercell composite parameter (SCP), fixed-layer and effective layer significant tornado parameter (STP), in addition to other resources, when developing severe local storm forecasts. This study utilizes the Weather Research and Forecasting (WRF) model to create simulations of composite indices for two tornado-producing events: 31 March 2023 and 3 May 1999. With modifications to geographical location, these simulated scenarios are then utilized in the survey to gauge how meteorologists assess where tornado potential is highest. Additionally, a combination of …

An Investigation Into The Inclusivity, Methodology, And Education Of Severe Weather In K-12 Schools, Stephen Holden Wooten

Theses and Dissertations

Schools are a focal point in the lives of everyone in the community, especially teachers, parents, and students. Investigating the connection between these individuals and tornadoes by identifying shortcomings in education, training, and emergency procedures can induce more effective and informed decision-making for future encounters. This study evaluated the inclusivity of tornado protocols for students with disabilities, uncovered where parents prefer their child to shelter in early dismissal situations and clarified how extensively natural hazard education and tornado drills are covered in schools. Two surveys and semi-structured interviews were used to obtain responses from earth science teachers, K-12 guardians, and …

Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick

Theses and Dissertations

The main contributions of this research is to add to the growing library of literature on the use of deep learning algorithms for the spatiotemporal prediction of dangerous atmospheric and hydrologic phenomena. Specifically, we develop novel attention-based and non-attention-based recurrent neural network frameworks to produce short-range sequential forecasts for lightning and tornado occurrences. Additionally, we introduce methods that account for and include error in the model tuning process to generate more reliable models. Furthermore, we have created a lightweight spatiotemporal tornadic prediction dataset that we plan to make publicly available. The first component of this research develops three novel spatiotemporal …

Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case

Theses and Dissertations

United States Air Force (USAF) operations rely on sortie generation, a complex system involving aircraft maintenance, operational planning, munitions, security forces, and aircrew. Failures in any of these areas can jeopardize a mission, and extreme weather events such as lightning, high winds, and snow further complicate operations. This thesis examines the impact of extreme weather on sortie generation, focusing on developing a data-driven discrete-event simulation (DES) to predict generation timelines and identify high-risk areas. The model allows users to adjust key inputs, including the month, number of aircraft, processing times, and personnel/equipment availability. By simulating real-world conditions, the model helps …

Center Fixing Tropical Depressions And Tropical Storms Using Machine Learning-Nighttime Visible Imagery, Nathan K. Stanford

Theses and Dissertations

The first step in most TC-retrieval algorithms is determining the storm’s central position. In mature TCs, the center is highlighted by a distinct eye and curved band pattern; however, in intensifying and decaying storms, the center is often obscured by thick clouds or overlying cirrus. This study assesses the benefits of incorporating machine learning-derived nighttime visual imagery to improve analysis of center fix in intensifying and decaying TD- and TS-strength TCs during periods of darkness and when polar orbiting satellites are unavailable. The study is divided into two parts: the first, an objective analysis using the ARCHER-2 algorithm, and the …

An Analysis Of Moisture Environments Associated With Mature North Atlantic Tropial Cyclones, Katherine Berislavich

Theses and Dissertations

Tropical cyclone (TC) intensity and structure are affected by their environments, including sea surface temperature, vertical wind shear, and atmospheric moisture. Analyses of TC environments often rely on area-averaged quantities, yet the spatial variability of these fields can affect TC behavior, such as moisture distribution impacting where and how much rain falls. This study identifies spatial patterns of environmental moisture surrounding mature North Atlantic TCs during 2000-2021 in shear of less than 20 knots. Empirical orthogonal function analysis of total column water vapor reveals six dominant patterns. These patterns account for nearly 67% of the variance in the dataset and …

Obscuration Analysis Of Camera Imagery For Aviation Applications, Patrick James Roelant

Theses and Dissertations

Image feature detection is a potent tool with many applications, such as fog identification, roadway conditions, etc. As part of the recent surge in machine learning applications, cloud detection has also become an increasingly engaged area of research. Identifying low clouds is especially useful with respect to aviation, particularly in regions of complex topography prone to visibility-related hazards such as haze or fog. To address this issue, a threshold-based semi-automated algorithm was developed and tested to determine whether or not an image is obscured by fog or haze. Images were obtained from a ground-based camera network in Southern California, the …

Using Asos Ceilings And Mesonet Relative Humidity To Improve General Aviation Flight Planning And Decision Making In Complex Terrain, Connor Hayden Welch

Theses and Dissertations

Despite the increasing availability of weather products and access to data, the issue of weather representativeness, especially in relation to terrain, persists in the aviation industry. Data-sparse regions pose a particular challenge, requiring focused research efforts to address this issue and reduce accident and fatality rates within the general aviation (GA) community. This thesis aims to tackle the specific problem of representing visibility conditions, with a focus on obscuration conditions in elevated terrain.

To achieve this goal, data from Automated Surface Observing System (ASOS) ceilometers and nearby mesonet relative humidity (RH) were analyzed to establish a relationship between the lowest …

Protecting The Vulnerable: Tornado Sheltering And Communication Of Public Shelters With A Case Study From The Covid-19 Pandemic, Craig Douglas Croskery

Theses and Dissertations

One of the greatest natural hazards that is faced with in much of the United States are tornadoes. Despite improvements in the warning processes, the risk of significant loss of life remains high. That is particularly true with vulnerable communities which have higher proportions of mobile homes; however, violent tornadoes are very difficult to manage in permanent homes or buildings as well. As a result, tornado shelters have been built in some communities and have become available to the public. However, their presence is intermittent, and there are many tornado-prone areas that lack such shelters.

After a public survey, it …

Quantifying Seasonal And Annual Precipitation Variability On San Salvador Island, Bahamas Using Surface Observations And Satellite Estimates., John Bryson Wells

Theses and Dissertations

San Salvador Island is a small Bahamian island located in the subtropics just north of the Tropic of Cancer. Due to its subtropical location, the island is influenced by both mid-latitude and tropical weather patterns. These weather patterns vary in scale from localized convective uplift to synoptic-scale systems. This study compares satellite-derived estimates of precipitation and rain gauge observations from June 2019 through September 2021 to evaluate the relationship between the two datasets. This study then uses the satellite-derived estimates of precipitation over a 20-year period to quantify annual and seasonal variability in precipitation on San Salvador. Corroborating past research, …

Verification Of The Localized Aviation Mos Program (Lamp) At Major Us Airports For Ifr Conditions, Mackenzie O'Rourke

Theses and Dissertations

The objective of this research is to quantify the LAMP’s performance when forecasting for IFR conditions at specific major airports for forecast hours one, three, six, and twelve, and further determine how the LAMP performs seasonally at those specific airports and forecast hours. Two by two contingency tables were used to calculate the Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), Heidke Skill Score (HSS), and Bias score. The results show that the LAMP performs relatively better in the cool season compared to the warm season consistently at each chosen airport, and that the LAMP performs …

Analysis Of Weather-Related Flight Delays At 13 United States Airports From 2004-2019 Using A Time Series And Support Vector Regression, Caroline E. Sleeper

Theses and Dissertations

This study seeks to investigate weather-related flight delay trends at 13 United States airports. Flight delay data were collected from 2004-2019 and normalized by airport operations data. Using Support Vector Regression (SVR), visual trends were identified. Further analysis was conducted by comparing all four meteorological seasons through computing 95% bootstrap confidence intervals on their means. Finally, precipitation and snowfall data were correlated with normalized delays to investigate how they are related. This study found that the season with the highest normalized delay values is heavily dependent upon location. Most airports saw a decrease in the SVR line at some point …

Tornado Outbreak False Alarm Probabilistic Forecasts With Machine Learning, Kirsten Reed Snodgrass

Theses and Dissertations

Tornadic outbreaks occur annually, causing fatalities and millions of dollars in damage. By improving forecasts, the public can be better equipped to act prior to an event. False alarms (FAs) can hinder the public’s ability (or willingness) to act. As such, a probabilistic FA forecasting scheme would be beneficial to improving public response to outbreaks.

Here, a machine learning approach is employed to predict FA likelihood from Storm Prediction Center (SPC) tornado outbreak forecasts. A database of hit and FA outbreak forecasts spanning 2010 – 2020 was developed using historical SPC convective outlooks and the SPC Storm Reports database. Weather …

Fragility Of The Florida Panhandle's Electrical Transmission Grid To Hurricanes, Zachary D. Schumann

Theses and Dissertations

The increased frequency and intensity of extreme weather events from climate change necessitates understanding impacts on critical infrastructure, particularly electrical transmission grids. One of the foundational concepts of a grid’s resilience is its robustness to extreme weather events, such as hurricanes. Resilience of the electric grid to high wind speeds is predicated upon the location and physical characteristics of the system components. Previous modeling assessments of electric grid failure were done at the systems level with assumptions on location and type of specific components. To facilitate more explicit adaptation metrics, accurate component-level information is needed. In this study, we build …

From The Sky To The Smartphone: Communicating Weather Information In A Digital Age, Cole M. Vaughn

Theses and Dissertations

As new technology has emerged in the digital era, the public can now choose from a variety of new media from which to get weather information. Weather applications (apps) and social media have emerged as some of the popular new media. This study sought to understand the extent to which these new media are used, how weather apps are perceived, how the news media used Twitter during Hurricane Irma, and how the public engaged with the news media’s tweets. A survey and dataset of tweets were used to evaluate the research questions and hypotheses of this research. The study found …

Cloud Image Classification Using Machine Learning, Marcus Peter Cote

Theses and Dissertations

Machine learning is a rapidly expanding technology that has proven to be highly useful for image classification. Ground-based camera networks are an emerging resource for aviation weather information with near real-time imagery available online for public viewing and download. While raw web camera imagery can be analyzed by aviators, high pilot workload motivates the use of machine learning to autonomously interpret cloud type information from images that is relevant to aviation weather hazards. In particular, transfer learning is a machine learning approach by which elements of a pre-trained machine learning model are refitted for new tasks. By employing transfer learning …

An Investigation Of Geostationary Satellite Imagery To Compare Developing And Non-Developing African Easterly Waves, Jenna Bartlett

Theses and Dissertations

African easterly waves (AEWs) are known precursors to tropical cyclone (TC) formation, although it is not always clear which AEWs will develop and which AEWs will not. To investigate AEW evolution, this study examines novel observations from the geostationary Advanced Baseline Imager (ABI) during July-September 2019. Case studies are conducted for two AEWs: one that became Hurricane Dorian, the strongest and most devastating hurricane of the 2019 Atlantic hurricane season, and a long-lived September AEW that did not become a TC. Lower-level moisture and flow, and the strength and spatial distribution of convective activity, differed between these two waves. By …

The Effects Of Incorporating 0-500 M Srh Into The Violent Tornado Parameter, Jay Palmer Roberts

Theses and Dissertations

Between 2011-2021, violent tornadoes accounted for an average of 65% of all tornado-related fatalities. The Violent Tornado Parameter (VTP), created in 2018, attempts to address this forecast problem but has issues with false alarms. Storm Relative Helicity has historically been used in tornado forecasting. Recent studies have shown the 0-500 m effective layer SRH (ESRH) has skill in discerning significantly tornadic events from those that are not.

This study explored the effects of incorporating 0-500 m ESRH into the VTP and issues relating to the parameter’s false alarm rate by examining RUC/RAP forecast soundings for 302 U.S. tornadic events (83 …

Defining Viable Solar Resource Locations In The Southeast United States Using The Satellite-Based Glass Product, Jolie Kavanagh

Theses and Dissertations

This research uses satellite data and the moment statistics to determine if solar farms can be placed in the Southeast US. From 2001-2019, the data are analyzed in reference to the Southwest US, where solar farms are located. The clean energy need is becoming more common; therefore, more locations than arid environments must be observed. The Southeast US is the main location of interest due to the warm, moist environment throughout the year. This research uses the Global Land Surface Satellite (GLASS) photosynthetically active radiation product (PAR) to determine viable locations for solar panels. A probability density function (PDF) along …

An Investigation Of Sea-Breeze Driven Convection Along The Northern Gulf Coast, Caitlin Ford

Theses and Dissertations

Although sea-breezes frequently initiate convection, it is oftentimes challenging to forecast the precise location of storm development. This research examines temporal and spatial characteristics of sea-breeze driven convection and environmental conditions that support convective or non-convective sea-breeze days along the Northern Gulf Coast. Base reflectivity products were used to identify the initial time of convection (values greater than 30 dBZs) along the sea-breeze front. It was found that convective sea-breezes initiated earlier in the day compared to non-convective sea-breezes. Mapping convective cells in ArcGIS revealed favored locations of thunderstorm development including the southeastern cusp of Mobile County, Alabama and convex …

Impact Of Climate Oscillations/Indices On Hydrological Variables In The Mississippi River Valley Alluvial Aquifer., Meena Raju

Theses and Dissertations

The Mississippi River Valley Alluvial Aquifer (MRVAA) is one of the most productive agricultural regions in the United States. The main objectives of this research are to identify long term trends and change points in hydrological variables (streamflow and rainfall), to assess the relationship between hydrological variables, and to evaluate the influence of global climate indices on hydrological variables. Non-parametric tests, MMK and Pettitt’s tests were used to analyze trend and change points. PCC and Streamflow elasticity analysis were used to analyze the relationship between streamflow and rainfall and the sensitivity of streamflow to rainfall changes. PCC and MLR analysis …

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 …