Meteorology Commons^™

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 …

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 …

Atmospheric Impacts From The 2010 Deepwater Horizon Oil Spill, Charles Philip Johnson

LSU Master's Theses

Although the ecological devastations induced by an oil spill are well studied, the hydrometeorological impacts from a long-term slick have gone unnoticed. The ocean-surface alterations stemming from the lasting oil footprint increase solar radiation absorption which in turn alters the surface pressure and moisture gradients and wind speeds thereby influencing precipitation surrounding the oil spill. Revealing the potential impacts from these could better aid in the safety of crews cleaning spills and provide a better understanding of how humans alter the landscape. This thesis examines the changes in local hydrometeorology brought on by the 2010 summer Deepwater Horizon (DWH) oil …

Radar Signatures In Tropical Cyclone Tornadic And Nontornadic Supercells, Michaela Wood

Dissertations & Theses in Earth and Atmospheric Sciences

Tropical cyclones (TCs) contain highly-sheared environments that are conducive for supercell thunderstorms. These TC supercells sometimes produce tornadoes, often with little warning. Given the often-close proximity of tornadic and nontornadic TC supercells, environments may not be well-distinguished, pointing to the potential value of radar observations. In this study, dual-polarimetric radar signatures of a sample of TC supercells are examined in the context of known supercell structure and microphysics. Tornadic and nontornadic TC supercells are compared with their midlatitude counterparts, and the environments and characteristic structure of these storms are shown to be notably different. An attempt is made to distinguish …

The Effect Of Advection On The Three Dimensional Distribution Of Turbulent Kinetic Energy And Its Generation In Idealized Tropical Cyclone Simulations, Joshua B. Wadler, David S. Nolan, Jun A. Zhang, Lynn K. Shay, Joseph B. Olsen, Joseph J. Cione

Publications

The distribution of turbulent kinetic energy (TKE) and its budget terms is estimated in simulated tropical cyclones (TCs) of various intensities. Each simulated TC is subject to storm motion, wind shear, and oceanic coupling. Different storm intensities are achieved through different ocean profiles in the model initialization. For each oceanic profile, the atmospheric simulations are performed with and without TKE advection. In all simulations, the TKE is maximized at low levels (i.e., below 1 km) and ∼0.5 km radially inward of the azimuthal-mean radius of maximum wind speed at 1-km height. As in a previous study, the axisymmetric TKE decreases …

Precipitation Recorded In The Turkana Basin From 2005 To 2022., Acacia Leakey, Greg Henkes, Mae Saslaw, Dino Martins

Geosciences Research Data

This is a dataset of precipitation recorded at three sites in northern Kenya near Lake Turkana using standard rain gauges. The data was recorded at the Koobi Fora Research Station (3.947736, 36.186166) from March 2003 until 2006, at the Turkana Basin Institute’s Ileret facility (4.28510, 36.262158) from 2006 to 2022 and at the Turkana Basin Institute’s Turkwel facility (3.140825, 35.864599) from 2012 to 2022. The data was collected manually by TBI staff observing gradation lines on the collectors following rainfall events and recorded as a single total for each 24 hour period.

Unmanned Aircraft Systems For Precision Meteorology: An Analysis Of Gnss Position Measurement Error And Embedded Sensor Development, Karla S. Ladino

Theses and Dissertations--Biosystems and Agricultural Engineering

The overarching objective of this research was to enhance our comprehension of the three-dimensional precision of meteorological measurements obtained using small unmanned aircraft systems (UAS). Two complimentary experiments were conducted to achieve this objective.

The first experiment entailed the development and implementation of a system to determine the global navigation satellite system (GNSS) position accuracy on a UAS platform. This system was utilized to assess the static and dynamic accuracy of L1 and L1/L2 GNSS receivers in real-time kinematic (RTK) and non-RTK fix modes. Adjusted two-sample t-tests revealed significant differences in horizontal and vertical error between RTK and non-RTK receivers …

Annual Summary Of Weather Data For Parsons - 2022, Matthew Sittel

Kansas Agricultural Experiment Station Research Reports

This report includes the annual summary of precipitation and temperatures from 2022 at the research locations represented in the 2023 Southeast Research and Extension Center Agricultural Research Report.

Spatial And Temporal Characteristics Of Historical Surface Climate Over The Northwest Territories, Canada, Bhaleka D. Persaud

Theses and Dissertations (Comprehensive)

Climate change is putting many of the Northwest Territories (NWT) ecosystems, its people and animal populations at risk due to accelerated warming, permafrost thaw, and changing precipitation regimes. As the NWT continues to warm, at disproportionately higher rates when compared to the rest of Canada, threats to the stability of NWT’s ecosystems are expected to increase. Consequently, understanding how climate warming has changed historically and its implications on natural ecosystems requires point-to-region-specific, long-term climatic data to elucidate important drivers of observed changes relevant to decision makers at community, Indigenous, Territorial and Federal government levels. However, in situ climate data are …

Climate Long-Term Trends Impacting Wheat Production Systems In Kansas, Octavia M.M. Tavares, Fábio Marin, Romulo Lollato, Bruno C. Pedreira

Kansas Agricultural Experiment Station Research Reports

Winter wheat production is of major importance in Kansas. The purpose of the study was to verify the evidence of climate change in a long-term weather data series from Wellington and Parsons, KS, to understand whether climate change has been affecting yield production.

Relative Importance Of Radar Variables For Nowcasting Heavy Rainfall: A Machine Learning Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

Highly short-term forecasting, or nowcasting, of heavy rainfall due to rapidly evolving mesoscale convective systems (MCSs) is particularly challenging for traditional numerical weather prediction models. To overcome such a challenge, a growing number of studies have shown significant advantages of using machine learning (ML) modeling techniques with remote sensing data, especially weather radar data, for high-resolution rainfall nowcasting. To improve ML model performance, it is essential first and foremost to quantify the importance of radar variables and identify pertinent predictors of rainfall that can also be associated with domain knowledge. In this study, a set of MCS types consisting of …

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 …

The Contribution Of Non-Tropical Cyclone Vortices To The Rainfall Of The Philippines, Lyndon Mark P. Olaguera, Jun Matsumoto, John A. Manalo

Physics Faculty Publications

Weaker disturbances than tropical cyclones (TCs) such as tropical depressions and cold surges can significantly induce heavy rainfall and flooding events over the Philippines. However, the analysis of these disturbances including their rainfall contributions are often neglected in previous studies. As the first attempt to address this research gap, this study investigates the rainfall contribution of non-TC vortices over the Philippines from 1979 to 2020. Only those rainfall-producing non-TC vortices that formed and appeared within a 500-km radius from the Philippine coastline were examined in this study. A total of 7,686 non-TC vortex days (50% of the total days during …

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 …

Assessing Changes In Tornado Vulnerablitiy In North Alabama, Mckenna Danielle Brahler

Honors Capstone Projects and Theses

No abstract provided.

Nexus Between Animal Welfare, Environment, And Sustainable Development: Resource Document, Wellbeing International

Nexus – UNEP – Animal Welfare, Environment, Sustainable Development

This Resource Document has been developed to explore the Nexus (links) between Animal Welfare, the Environment, and Sustainable Development. The document includes relevant citations and reports addressing the topics encompassed by the Nexus. It will be maintained as a “living document” (subject to revision) in the WellBeing International Studies Repository. The original document and subsequent revisions will be kept in the Repository to provide a record of the changes.

Estimation Of Economic Risk From Coastal Natural Hazards In Louisiana, Rubayet Bin Mostafiz

LSU Doctoral Dissertations

Louisiana, U.S.A., is among the most vulnerable areas globally to coastal natural hazards, with risk vulnerability likely increasing. The risks associated with non-tropical-cyclone hazards in Louisiana’s coastal zone have been understudied. This research enhances present and future (i.e., 2050) Louisiana risk assessment using locally-weighted, model-based hazard frequency/intensity and population projections.

Results suggest that property risks associated with extreme cold temperature and tornado are and will remain costlier than those for hail and lightning. Property risks of extreme cold temperature and hail are projected to decrease with the expected warming temperatures, with those of all four of these hazards peaking in …

Polarimetric Radar And Vhf Lightning Observations In A Significantly Tornadic Supercell, Jacob Bruss

The Journal of Purdue Undergraduate Research

No abstract provided.

Airflow Dynamics In Wind Cave And Jewel Cave: How Do Barometric Caves Breathe?, Annika K. Gomell, Andreas Pflitsch

International Journal of Speleology

Recent research on air pressure propagation through barometric caves has revealed various speleoclimatological processes, which cause a more complex relationship between surface air pressure changes and resulting pressure gradients between cave and surface air than previously assumed. So far, however, studies on barometric cave airflow have only been based on surface air pressure measurements. Thus, this study investigates and compares airflow at the openings of Wind Cave and Jewel Cave – two major barometric cave systems in South Dakota, USA – as a response to surface air pressure changes and air pressure gradients. Based on high-resolution long-term air pressure measurements …

A Demonstration Of A Simple Methodology Of Flood Prediction For A Coastal City Under Threat Of Sea Level Rise: The Case Of Norfolk, Va, Usa, Tal Ezer

CCPO Publications

Many coastal cities around the world are at risk of increased flooding due to sea level rise (SLR), so here a simple flood prediction method is demonstrated for one city at risk, Norfolk, VA, on the U.S. East Coast. The probability of future flooding is estimated by extending observed hourly water level for 1927–2021 into hourly estimates until 2100. Unlike most other flood prediction methods, the approach here does not use any predetermined probability distribution function of extreme events, and instead a random sampling of past data represents tides and storm surges. The probability of flooding for 3 different flood …