Meteorology Commons^™

Theoretical And Observational Analysis Of Ice Particles For Improvement Of Ice Microphysical Models, Vanessa Przybylo

Legacy Theses & Dissertations (2009 - 2024)

Frozen hydrometeors can grow to acquire a multitude of shapes and sizes, which influence the distribution of mass within cloud systems. Aggregates have a variety of formations based on initial ice particle size, shape, falling orientation, and the number of particles that collect. This work employs the theoretical Ice Particle and Aggregate Simulator (IPAS) as a statistical tool to repetitively collect ice crystals to derive bulk aggregate characteristics.

2021 July - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Droughtscape, Summer 2021, National Drought Mitigation Center

DroughtScape: Quarterly Newsletter of the National Drought Mitigation Center (2007–2023)

DroughtScape, Summer 2021

A Glint Contaminated Pixel Correction Algorithm And Potential Application For Estimating Water Visibility, Andrea Taggart

Theses and Dissertations

Glint in satellite reflectance images contaminates pixels making it difficult to ascertain what lies beneath the water surface. An algorithm was created to correct glint contaminated pixels using a nearest neighbor non-glint pixel search algorithm written in Python. The results of the glint corrected pixels were then analyzed using an algorithm to estimate water visibility using light attenuation depths and second derivative estimators based upon glint corrected satellite reflectance using channels from a WorldView-3 (WV-3) image. The above was accomplished for sand, mud, and seagrass bottom types. The results suggest that estimated attenuation depths (a measure of water visibility) is …

Weather And Crime: New York State, Yuna Kim

Student Theses

The present study assesses the degree to which temperature affects the crime rates in all 62 counties in the State of New York. Five different crimes (i.e., robbery, aggravated assault, burglary; larceny, and motor vehicle theft) for the year 2019 were selected from the Division of Criminal Justice Services of New York to be examined. The current study examined whether the rate of these crimes was associated with the changes in weather, with the assumption that higher weathers would lead to higher property and violent crimes, when controlling for the effect of various control variables. The findings suggest that the …

The Development And Evaluation Of The Atlantic Tropical Cyclone Intensification Regression Model (Atcirm), Bruno Platero Huarcaya, Lexi Cruz

Beyond: Undergraduate Research Journal

Operational track forecasts of Tropical Cyclones (TCs) have been improved substantially in recent years and nowadays are sufficiently accurate. However, intensity forecasts have not shown similar improvements, especially for rapidly intensifying storms. The improvement of intensity forecast accuracy can help authorities in risk management and decision making to prevent loss of life and property. The purpose of our project is to develop a statistical linear regression model that provides better predictions for TC intensification over the ocean. Here, different predictor variables are studied, and 2011-2017 Atlantic basin storms are investigated. The final set of predictor variables selected for the model …

2021 June - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Characterizing The Northern Hemisphere Circumpolar Vortex Through Space And Time, Nazla Bushra

LSU Doctoral Dissertations

This hemispheric-scale, steering atmospheric circulation represented by the circumpolar vortices (CPVs) are the middle- and upper-tropospheric wind belts circumnavigating the poles. Variability in the CPV area, shape, and position are important topics in geoenvironmental sciences because of the many links to environmental features. However, a means of characterizing the CPV has remained elusive. The goal of this research is to (i) identify the Northern Hemisphere CPV (NHCPV) and its morphometric characteristics, (ii) understand the daily characteristics of NHCPV area and circularity over time, (iii) identify and analyze spatiotemporal variability in the NHCPV’s centroid, and (iv) analyze how CPV features relate …

Hydrometeorological Responses To Abrupt Land Surface Change Following Hurricane Michael, Shannon Alexis Nelson

LSU Master's Theses

While many of the destructive environmental conditions associated with tropical cyclones are well recognized, tropical cyclone-induced defoliation, a reduction in green leaves and mature vegetation, has been largely overlooked as a source of environmental stress following tropical cyclone passage. The land surface change associated with defoliation reduces evapotranspiration and shade, thus altering boundary layer moisture and energy fluxes that drive the local water cycle, for many months after tropical cyclone passage. Understanding the potential for any hydrometeorological impacts arising from such abrupt land surface change is important for guiding future post-hurricane preparedness and recovery planning in coastal communities.

This thesis …

Downscaling Methodology For Satellite Land Surface Temperatures Over Urban Environments, Naved Khan, Ruben Vecino

Publications and Research

The objective of this study is to develop high spatial and temporal resolution Land Surface Temperature (LST) data using a combination of Landsat 8, infrared satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Geostationary Operational Environmental Satellite-R Series (GOES-16). The Landsat 8 Thermal Infrared Sensor (TIRS) provides higher spatial resolution (30 m) estimates of skin temperature every 16 days. MODIS makes daytime and nighttime observations of the Earth’s thermal emission at a coarser spatial resolution (1000 m), while GOES-16, which has lower spatial resolution (2 km), measures the skin temperature at a much higher temporal resolution …

The Effects Of Late Spring Frost On Forest And Landscape Health And Recovery Of The Black Rock Forest, New York, Caroline Eco, Oliver Imhans, Aaron Davitt, Andrew B. Reinmann

Publications and Research

Projected changes in climate are expected to increase the frequency of late spring frost events in the Northeast US. Such events can be harmful to trees because freezing temperatures that occur after leaf-out can damage or kill young leaves. The resultant defoliation typically forces a second flush of leaves, but delays canopy development, which in turn delays the onset of canopy carbon uptake and alters canopy thermal properties. In this study, we analyzed a recent freeze event that occurred on 8-9 May 2020 (DOY 129-130) at Black Rock Forest (BRF), which is in the Hudson Highlands of southeastern New York …

Applying Human Factors Heuristic Evaluation Tools To Improve Aviation Weather Displays: A Mismatch, John Kleber, Paige Lawton, Beth Blickensderfer

General Aviation Weather Display Interpretation

The evaluation of current Heuristic Evaluation Tools for use in assessing Aviation Weather Displays.

2021 May - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

The Effect Of Initial Conditions On The Weather Research And Forecasting Model, Aaron D. Baker

Electronic Theses and Dissertations

Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to …

Multifidelity Prediction In Wildfire Spread Simulation: Modeling, Uncertainty Quantification And Sensitivity Analysis, Mario Miguel Valero, Lluís Jofre, Ricardo Torres

Faculty Research, Scholarly, and Creative Activity

Wildfire behavior predictions typically suffer from significant uncertainty. However, wildfire modeling uncertainties remain largely unquantified in the literature, mainly due to computing constraints. New multifidelity techniques provide a promising opportunity to overcome these limitations. Therefore, this paper explores the applicability of multifidelity approaches to wildland fire spread prediction problems. Using a canonical simulation scenario, we assessed the performance of control variates Monte-Carlo (MC) and multilevel MC strategies, achieving speedups of up to 100x in comparison to a standard MC method. This improvement was leveraged to quantify aleatoric uncertainties and analyze the sensitivity of the fire rate of spread (RoS) to …

2021 April - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Hazardous Weather Communication En Español: Challenges, Current Resources, And Future Practices, Joseph E. Trujillo-Falcón, Orlando Bermúdez, Krizia Negrón-Hernández, John Lipski, Elizabeth Leitman, Kodi Berry

National Oceanographic and Atmospheric Administration: Technical Reports and Related Materials

According to recent Census data, the Hispanic or Latino population represents nearly 1 in 5 Americans today, where 71.1% of these individuals speak Spanish at home. Despite increased efforts among the weather enterprise, establishing effective risk communication strategies for Spanish-speaking populations has been an uphill battle. No frameworks exist for translating weather information into the Spanish language, nor are there collective solutions that address this problem within the weather world. The objective of this article is threefold. First, the current translation issue in Spanish is highlighted. Through research conducted at the NOAA/NWS Storm Prediction Center, situations are revealed where regional …

Droughtscape, Spring 2021, National Drought Mitigation Center

DroughtScape: Quarterly Newsletter of the National Drought Mitigation Center (2007–2023)

DroughtScape, Spring 2021

Case Studies Of Alberta Clipper Systems And The Impacts On Winter Weather Road Maintenance, Cameron Wunderlin

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Winter weather can cause profound impacts to a variety of economic sectors in the mid-latitudes. In the Great Plains of North America, one sector that is highly impacted by winter weather is road transportation. The burdens to road transportation caused by winter weather have led to the adoption of a Maintenance Decision Support System (MDSS) by the Nebraska Department of Transportation (NDOT). Using both observational and numerical weather model data, NDOT-MDSS generates both winter weather forecasts and winter road maintenance recommendations. Little is known about how well NDOT-MDSS is forecasting conditions for different winter weather events. Using a case study …

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 …