Weather In Middle-Earth Or Tolkien: The Weather-Master?, Jonas Mertens

Journal of Tolkien Research

Abstract

This article attempts to shed light on the use of weather in general and meteorological expressions in The Lord of the Rings, as J. R. R. Tolkien is well known to be a writer for whom the environment and natural world is closely intertwined with his storytelling. Both a manual count and a count which a digital text analysis tool were combined to find the frequency of previously selected weather terms. In total, more than 2,000 references were found in the books, with the words ‘sun’, ‘wind’ and ‘cold’ being the most abundant. Meteorological expressions are frequently encountered in …

Hyper-Local Weather Predictions With The Enhanced General Urban Area Microclimate Predictions Tool, Kevin A. Adkins, William Becker, Sricharan Ayyalasomayajula, Steven Lavenstein, Kleoniki Vlachou, David Miller, Marc Compere, Avinash Muthu Krishnan, Nickolas Macchiarella

Publications

This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. For the further development and demonstration of GUMP, the Embry–Riddle Aeronautical University (ERAU) campus was used as a test environment. Local weather sensors provided data to train ML models, and CFD models of urban- and suburban-like areas of ERAU’s campus were created and iterated through with a wide assortment of inlet wind speed and direction combinations. ML weather sensor predictions were combined with best-fit …

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 …

Climatological Analysis Of Tropical Cyclone Occurrence Dates And Landfall Characteristics In The North Atlantic And Eastern North Pacific, Nicholas Sava Grondin

Doctoral Dissertations

Tropical cyclones (TCs) are significant hazards to coastal and inland regions across the globe, especially in North America. North America is affected by TCs from two basins, the North Atlantic (NATL) and eastern North Pacific (ENP), with the former being the predominate focus of past research. In this dissertation, I present three studies that directly compare TCs in the NATL and ENP by using the same methods for each basin in studying occurrence dates and intraseasonal variability, effects of environmental parameters on occurrence dates and seasonal forecasting, and the behavior of TCs during the final 36 hours before landfall in …

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 …

The Influence Of Complex Coastlines On The Sea Breeze And Convection Initiation In Coastal North Carolina, Logan Howard, Adam L. Houston

Honors Theses, University of Nebraska-Lincoln

The sea breeze is a common phenomenon in coastal regions around the world. Their development and propagation can be treated as a density current. It is well known that many factors influence density current propagation, including wind. Depending on the orientation, the wind speed and shear can enhance or inhibit the development of the sea breeze. In places like eastern North Carolina, complex coastal geography can create river and sound breezes that, upon collision, have the potential to initiate thunderstorms. Using Cloud Model 1, simulations were conducted to model the behavior of the sea breezes in eastern North Carolina and …

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 …

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 …

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.

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.

Field Station Weather Reports, E. Adee, M. 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 Field Research Report and further details about the Kansas River Valley locations and the east central Kansas locations.

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.