Atmos BS Undergraduate Research

Climatology of U.S. Tornado Size and Intensity 1950-2024 

Using Transient Luminous Events as a Weather Prediction Tool 

Transient luminous events are a type of upper atmospheric lightning that results from atmospheric gases being excited by electrical discharges. Studies have revealed that these events are related to positive lightning strikes from clouds to Earth’s surface. Each TLE falls into one of four categories: Extremely low voltage events (ELVEs), halos, sprites, and jets. Most data that form the basis for current sprite observations on the global scale comes from the Imager for Sprites and Upper Atmospheric Lightning (ISUAL). This instrument was in service on board a satellite from 2004 to 2016 and took more than 300,000 measurements of specific lightning events, some of which included sprites. Since the end of the ISUAL mission, technologies have emerged in the realm of artificial intelligence that allow for deeper exploration of TLEs. With image recognition software, a semi-automated system is created to find these events with similar accuracy to human-generated results in a fraction of the time. Results for the location and timing of events is analyzed globally, including seasonal and interannual variability. Results show a particular hotspot for sprites in equatorial Africa. This region tends to produce positive cloud to ground lightning, reinforcing past findings. The prominence of ELVEs over oceans on the coastlines of Central America and Indonesia also lines up with past research.  

Role of Topography in the Intensity of the North American Monsoon During the Miocene Climatic Optimum 

Climate Change, Hurricane Intensification and Inequitable Disaster Recovery in the U.S. 

This study investigates the interconnected challenges of climate change-driven hurricane intensification and inequitable disaster recovery outcomes in the United States. Rising global air temperatures are contributing to higher sea surface temperatures and changing atmospheric conditions, which enhance the formation, intensity, and destructive capacity of tropical storms. Scientific research shows that warmer oceans provide more thermal energy for hurricanes, enabling them to reach higher wind speeds, intensify more rapidly, and produce greater storm surges and flooding. Even in cases where storm frequency remains relatively stable, the impacts of individual hurricanes are becoming more severe. Case studies such as Hurricane Katrina demonstrate how climate change functions as a “threat multiplier”, with sea level rise and warmer conditions increasing flood elevations and overall damage.

            While the physical intensity of hurricanes is increasing, their social impacts are not experienced equally. Disaster vulnerability is shaped by a combination of environmental exposure and socioeconomic factors, including income, housing quality, access to transportation, and political representation. Marginalized communities, particularly low-income populations and communities of color, are more likely to reside in high-risk areas and face greater challenges in preparing for, responding to, and recovering from disasters. Empirical evidence shows that these populations often experience disproportionate harm, including longer displacement periods, and reduced access to recovery resources.

            This study further examines how federal disaster recovery programs may unintentionally reinforce these disparities. Although programs administered by agencies such as Federal Emergency Management Agency (FEMA) are critical for providing relief, structural barriers – including complex applications procedures, strict documentation requirements, and property-based aid models – tend to advantage homeowners and higher-income individuals. As a result, renters and economically vulnerable populations frequently receive less assistance despite experiencing significant losses.

            Using a combination of climate science research, literature review, and case study analysis, this paper explores how environmental and institutional factors intersect to shape disaster outcomes. The findings suggest that the increasing intensity of hurricanes, coupled with inequities in recovery systems, exacerbates long-term social vulnerability. The study concludes by proposing targeted and feasible policy reforms, including prioritizing climate-resilient infrastructure investments in high-risk communities and improving the accessibility and equity of federal disaster aid. Together, these strategies aim to enhance both physical resilience and social equity in the face of growing climate-related risks.

Enhanced Great Lakes Snow or at least for a bit 

Examining the Chicago Urban Heat Island Effect in Response to Winter Conditions 

The Urban Heat Island (UHI) effect is the tendency of urban areas to experience warmer temperatures in comparison to rural areas, which has been observed as the urbanization of cities influences the surrounding climate. Previous studies primarily focus on the UHI effect during the warm summer months, with only a few focusing on the cold winter months. Because of this, there has been a limited understanding of the potential effects of winter conditions on the UHI effect. This study focuses on the presence of snow accumulation and wind conditions on temperature fluctuations in urban areas at the local scale. This was done by utilizing analytical methods to examine differences in temperature fluctuations in response to snow depth and wind conditions between urban and rural areas, allowing for the identification of potential changes in UHI magnitude. Observing the effect of snow accumulation and wind conditions on the UHI effect can provide further understanding to implement anthropogenic heating mitigation in urban areas. 

Is there a correlation between El Niño Southern Oscillation and lightning intensity in Earth’s lightning hotspots? 

This project was conducted in order to determine if the El Niño Southern Oscillation has any correlation with the world’s most lightning intensive locations (lightning hotspots). In this work, two datasets were used. Data regarding El Niño Southern Oscillation (3.4 Index) and data regarding lightning variability in the tropics (LIS). These datasets were compared in order to identify correlation that ENSO has on lightning hotspots. Three specific locations were specifically analyzed: Lake Maracaibo, eastern Congo, and Carcana, Argentina. Other locations were also considered during this analysis. One hotspot (eastern Congo) did show correlation during DJF with a value of -0.616. However, all other correlation values were not above 0.3 or -0.3, with the threshold being equal to or above 0.458 or equal to or below -0.458. It was determined through analysis that ENSO does not have a significant impact on the three specified lightning hotspots. However, there were other locations that were not the focus of this research that were highlighted due to showing significant correlation, specifically the Gulf of Mexico. 

The Interactions between Global Warming, Air Quality, and Stratospheric Intrusion Events 

A Better Way to Present Hurricanes to People 

High winds, coastal flooding, tornadoes, and storm surges, as we know, are caused by hurricanes and tropical storm systems in the United States as well as extratropical cyclones elsewhere. The primary location of these storms is along the East Coast, along the Atlantic Ocean. Since the beginning of tropical cyclone forecasting and activity recording in the US, only one of the hazards named has been the primary factor in determining the measure of severity of these storms: wind speed. My hypothesis states: while using the maximum windspeed to determine the category of a hurricane may sound intuitive for most people, I believe there are other factors meteorologists and atmospheric scientists should account for when discussing the severity of tropical cyclones to help “extend” the use of the Saffir-Simpson scale. This would extend from a scale using a single hazard to present a tropical cyclone into a scale with more than one hazard presented. 

Nitrous Dioxide Trends in Northern Virginia using Tropomi Satellite Data 

A Study on the Eastward Movement & Frequency of Tornadoes 

Model Performance on Forecasting Tropical Cyclones in the Northern Indian Ocean Basin 

Tropical cyclones are some of the most destructive natural disasters. From October to May, the North Indian Ocean. Historically, cyclones in the Arabian Sea rarely make landfall over the coasts surrounding the Gulf of Aden. In recent years, the occurrence of cyclones formed outside of the October to May season and the chance of landfall in the Greater Horn of Africa region has increased due to a significant rise in global sea-surface temperatures. The lack of adequate modeling and forecasting has led to extensive destruction. Subseasonal-to-seasonal (S2S) forecasts by ECMWF and NCEP CFSv2 models for cyclones Gonu (2007), Chapala (2015) and Sagar (2018) were compared to track and intensity data from the International Best Track Archive for Climate Stewardship (IBTACS). Results show that the ECMWF model outperformed the NCEP model in both track accuracy and how early the storm was picked up for Gonu and Chapala, but it was found that the NCEP model outperformed the ECMWF model in both categories for TC Sagar. 

Are Average Temperature Trends Affecting Tornado Occurrences and Magnitude in the US? 

Extreme Precipitation & Tropical Cyclones in Virginia 

Does Average Temperature Trends Affect Hail Storm and Damaging Wind Occurrences and Magnitudes in the United States? 

Innovative Techniques for Collecting Airborne Dust in Valley Fever-Prone Regions 

Evaluating the Impact of Atmospheric Dust on Late Pliocene Warmth 

Paleoclimate Models: How d18O proxies in the Early and Middle Miocene can help us to obtain accuracy of climate reconstruction 

Cloud Seeding 

The Effects of Climate Change on Convective Rainfall in the Southeast U.S. 

Climate change is an issue that continues to affect the entire world, along with many of its processes. One such process may the convective precipitation trends in different regions of the world, including the Southeast United States. This is what is examined here, with the focus being on four different sectors of the Southeast U.S. that also include parts of the Gulf of Mexico. Convective rainfall is compiled for the months of April, May, and June for every year from 1979-2020, within each of these four sectors. The compiled data is used to find yearly anomalies in the convective rainfall, as well as create linear regression models that display the monthly data for each year and the average trend over all of the years. Also, convective rainfall and sea-surface maps are created for specific years, which are then compared to the quantitative convective rainfall data. Finally, a discussion is given related to the trends, which explores any possible answers that have been found based on the amount of data that is available. 

The Impact of ENSO Season on JFM Tornadoes and Their Initial Atmospheric Conditions in the Southeast of the CONUS 

The southeast Unites States, also known as “Dixie Alley”, has started to become the new watch area for severe (EF2+) tornadic activity. With the El Niño Southern Oscillation (ENSO) also becoming a large topic of discussion, it is important to find a relationship between these two subjects. With data from the National Weather Service (NWS) and Physical Science Lab (PSL), a regression analysis was able to be run to test the relationship between tornadoes, climate variables that cause tornadoes and different ENSO indices during January-March (JFM). It was found that the ENSO ONI index had the strongest relationship with surface temperatures, CAPE and the number of tornadoes that occurred. The results from this research can also support the results of previous work, indicating that ENSO plays a very small role in the development of tornadic activity in the United States. 

Identification of Cloud Types Using Numerical Data 

Cloud type is investigated using data from simulations over the Atmospheric Radiation Measurement (ARM) project’s Southern Great Plains (SGP) site in Oklahoma with a refined methodology from previous research. The main scientific question investigated is how does cloud type relate to other variables in the atmosphere. The SCAM data has been taken from an area in Oklahoma and specifically looked at afternoon cloud formation. Cloud types are defined by their top height and optical thickness. These variables were calculated from cloud liquid water content, total cloud cover, and cloud liquid water path (LWP). This research has found that Oklahoma in 2016 had a large amount of optical thick clouds and deep convective cirrus clouds were most common. This research helps to improve the current understanding in cloud type research and advocates for an often-overlooked variable. 

The Impact of COVID-19 Economic Recession on Air Quality in Washington DC 

Tropical Cyclone activity during pre- and post-monsoon season inNorth Indian Ocean 

Cape Town’s winter rainfall regime & the “Day Zero” Drought 

Poleward Trend in the South Atlantic Subtropical Ocean Front: A Possible Verification of Hadley Expansion

An analysis of how re-forecasts from CFSv2 improved from the real time GFS forecasts for hurricane Isabel in 2003

The purpose of this paper is to analyze how an updated re-forecast improved from original GFS forecasts for hurricane Isabel. The variables that will be discussed in this paper include total rainfall, wind shear, 200mb and 850mb winds, and 500 mb heights. These variables were picked because they are important variables that could be used to indicate a hurricane threat. The variables discussed in this paper are analyzed by using GrADS to review the 00Z forecasts for September 18th 2003 which was when the storm first made landfall. The results indicate that the re-forecasts from the CFS generally did a better job accurately forecasting the observed values for all variables. Both models did a good job picking up the location of these features but had a difficult time narrowing down the exact magnitude.

Wind energy? I’m a big fan

Although many countries across the world have realized the importance and environmental benefits of renewable energy, many regions in the US have yet to take advantage of these resources. Several economic, social, and political factors play a role in renewable energy implementation, but little attention and research has been conducted on the environmental feasibility of such projects. The West North Central region of the United States has one of the greatest potentials for wind energy, but because of its current heavy reliance on coal and oil, there is little research on how much wind energy potential there is. This project attempts to provide a preliminary analysis on wind power viability in this region by modeling wind speed and variability from 1980 to 2017; this data was also made into an interactive web application in the effort to make this type of information more accessible, visually appealing, and interesting to the public.

Antarctic sea-ice variability: Assessing trends and mechanisms

A Climatological Study of Tropical Cyclones in the Atlantic Basin

Using the HURDAT data set, the frequency and intensity of tropical cyclones were examined on a 100-year time scale along with points of origin, probability track distribution, and land and sea impacts. The results indicate that tropical cyclone activities in the Atlantic Basin show quite variability. The possible reasons for this variability is due to Saharan Air Layer activities, intensity and location of jet stream, events such as El Niño, La Niña, and the Atlantic Multi-Decadal Oscillation.

A Measures-Oriented Forecast Verification for Fairfax, Virginia

The objective of this project is to compare two categories of weather forecasts: human and the operational Global Forecasting System (GFS) numerical model. The comparison will be based on the forecast verification of each category; continuous variable testing (temperature) and Dichotomous variable testing (precipitation). The following will explore the significance/ noteworthiness of forecasting and then an in-depth review of pertinent forecast verification techniques. Relevant techniques include; methods of verification of real continuous scalar quantities, and methods of verification of binary (dichotomous) events.

Alexandria Dingman, Summer 2024 

Hana Tucker, Summer 2023 

Amber Verstynen

Jeremy Goldstein ('18)

Marissa Corrado ('18)

Dylan Costlow ('17)

• Jacquelyn Crowel and Riley Freeland work as subseasonal forecasters, producing the weekly forecast maps in support of Dr. Kathy Pegion’s NOAA funded project SubX (link). 
• Crowel is also investigating the prediction of tropical cyclones in SubX data and Freeland is looking at winter storms, both for the SubX-IFLOOD coastal flood forecast system (link) in collaboration with Dr. Natalie Burls (AOES), Dr. Kathy Pegion (AOES) and Dr. Celso Ferriera (Volgeneau School of Engineering) through a grant from the College of Science and Volgeneau School of Engineering.