Atmospheric Sciences Commons^™

Results And Implications For Space Weather Forecasting Of Periodic Mesoscale Solar Wind Structures Responsible For Radiation Belt Particle Loss, Grace Gratton

Discovery Day - Daytona Beach

Highly dynamic and structured mesoscale solar wind continually buffets Earth's magnetosphere, the moon, and Mars. These mesoscale structures cause several significant risks to spacecraft and astronauts, including driving radiation belt depletion and amplifying the hazards of CMEs and SIRs through upstream solar wind preconditioning. Characterizing the solar origins and solar wind properties of geoeffective mesoscale structures is essential for eventually forecasting their arrival and space weather impact at various satellites. In this interdisciplinary work, we leverage modeling and data analysis to characterize a series of events observed by the Balloon Array for Radiation-belt Relativistic Electron Losses (BARREL) instrument – in …

Project Minerva, Lena Wang, Gannon English, Ethan Yemm, Gabrielle Guirguis, Jose Murphy

Discovery Day - Daytona Beach

Project Minerva is a multidisciplinary engineering initiative at Embry-Riddle Aeronautical University (ERAU) dedicated to the design, integration, and deployment of high-altitude balloon (HAB) systems for stratospheric research and aerospace hardware validation. The project challenges student researchers to engineer flight-ready payloads capable of maintaining structural and electronic integrity in extreme temperatures and low-pressure environments in the stratosphere. Typically utilizing 600g latex balloons filled with helium, Project Minerva missions aim to achieve altitudes exceeding 22,000 meters to facilitate vertical atmospheric profiling of variables such as CO₂ concentration, humidity, temperature, and pressure. Beyond its technical objectives, the project serves as a professional training …

The Impact Of Environmental Contributing Factors In Spatial Disorientation And Non-Spatial Disorientation Related General Aviation Accidents, Victoria Cornaro, Molly Mersinger

Discovery Day - Daytona Beach

The Impact of Environmental Contributing Factors in Spatial Disorientation and Non-Spatial Disorientation Related General Aviation Accidents   Spatial disorientation (SD) is an inherent risk of flying and with a high risk of resulting in a fatal accident (Gibbs et al, 2011). SD related accidents occur when a pilot’s perception of the aircraft altitude, position, or relative motion conflict with reality (Benson, 1999). SD accidents are significantly more likely to result in a fatality than non-SD cases. The purpose of this study was to investigate the role of different contributing factors on SD and non-SD general aviation accidents. We used the NTSB …

Stability Through Chaos: Atmospheric Impact And Control Strategies For Laser Communication, Om Acharya, Mykailla Harper, Mark Vanberschot, Aldir Moreira

Discovery Day - Daytona Beach

Study of Atmospheric Effects and Mitigation Strategies in Free-Space Optical Communication Systems examines the fundamental limitations imposed by atmospheric disturbances on point-to-point laser communication links and evaluates methods to improve link reliability and performance. Free-space optical communication offers high data rates and reduced spectral congestion compared to radiofrequency systems, but its effectiveness is constrained by atmospheric effects including turbulence-induced scintillation, beam wander, absorption, and scattering. These phenomena introduce fluctuations in signal intensity and pointing errors, leading to degraded link stability and increased bit error rates. The work analyzes these atmospheric effects and investigates mitigation strategies that enhance optical link robustness …

Real-Time Fused Sensor System For Early Onboard Detection Of Weather Phenomena, Sanjana Singh

Discovery Day - Daytona Beach

Weather-related hazards continue to be a major cause of operational interruptions and safety issues in the aviation sector. Atmospheric phenomena, including turbulence, microbursts, convective storms, and rapidly changing boundary-layer conditions, can arise quickly and often occur on spatial scales that are not adequately addressed by regional forecasting systems. These phenomena particularly endanger aircraft flying at low altitudes, such as general aviation planes, unmanned aerial vehicles (UAVs), and those during takeoff and landing Although meteorological forecasting systems and ground-based radar networks offer important regional insights, they may fail to detect localized atmospheric variations encountered along specific flight routes. Consequently, pilots and …

Investigating The Spatial Scales Of Ionospheric Irregularities Using Wavelet Analysis, Nash Mcleod

Discovery Day - Daytona Beach

Investigating the Spatial Scales of Ionospheric Irregularities Using Wavelet Analysis:   Ionospheric radio wave scintillation arises from plasma density irregularities in Earth’s ionosphere. Consequently, rapid fluctuations occur in the phase and amplitude of Global Navigation Satellite System (GNSS) signals and can impact communication and navigation systems. These irregularities span from a wide range of spatial and temporal scales and evolve dynamically under the influence of magnetosphere-ionosphere (MI) processes. We investigate phase and amplitude scintillation events using Continuous Wavelet Transform (CWT) to study the spatial evolution of ionospheric irregularities. These irregularities are thought to be formed via different plasma mechanisms such as …

Bounded Thunderstorm Tracking Of Lightning Events With Muon Detection, Skylar Wardlaw, Ainsley Helgerson, Maria Kaminska, Logan Velvet, Georgii Dubrov, Jackson Stewart, Aaron Jung, Nathaniel O’Hara, Amelia Koth, Nash Mcleod, Emaleth Wyckoff

Discovery Day - Daytona Beach

The muon is a high-energy particle that can be produced by cosmic rays and trigger upper-atmospheric particle cascades and energetic processes. It has been hypothesized that such cascades are at the onset of lightning. As such, muons serve as a valuable probe for investigating the underlying mechanisms of its initiation, whose full governing dynamics remain vastly unknown despite extensive research. Traditional approaches to lightning research involve simulations and observations of the discharge itself, but the role of high-energy particle interactions has yet to be fully constrained. The CosmicWatch Muon Detector design enables the detection of atmospheric muons through scintillation events, …

Stormtrack: A Regime-Aware Classifier-Router Architecture For Multi-Horizon Kp Index Forecasting, John Rendleman

Discovery Day - Daytona Beach

STORMTRACK: A Regime-Aware Classifier-Router Architecture for Multi-Horizon Kp Index Forecasting Current algorithms in operational space weather face extreme difficultly predicting the Kp geomagnetic index beyond 24 hours, a lead time that is critical for protecting high-frequency communications and infrastructure. Most regression models are optimized for quiet conditions, which dominate the data, leading to systematic underpredictions of storm events that cripple space infrastructure. Probabilistic approaches and physics-based numerical models also falter due to the same class imbalance plaguing standard regressors at multi-day lead times. The ICARUS 6 architecture addresses this by splitting the forecasting component into quiet and storm regimes, which …

Effective Visibility In The Infrared Bands, Peter L. Dean-Erlander, Steven T. Fiorino, Ronald G. Driggers

Faculty Publications

Visibility is an atmospheric metric for the comparison of terrestrial imaging conditions and locations. A limitation of visibility is that it is defined for the visible spectrum only, and there is no simple infrared equivalent. This study compares three reflective infrared wavebands: near-IR (NIR), shortwave IR (SWIR), and extended shortwave IR (eSWIR), to the visible band across a global set of cities to develop three rule-of-thumb functions for IR effective visibility. To accomplish this, a radiometric sensor model is combined with the Laser Environmental Effects Definition and Reference (LEEDR) software package to calculate the visibility of a black-and-white contrast target …

Understanding And Predicting Precipitation Characteristics In The United States Through Machine Learning, Numerical Modeling And Measurements, Cody Luther Ratterman

All Graduate Theses and Dissertations, Fall 2023 to Present

Precipitation is one of the most important yet uncertain variables in the climate system. It varies dramatically in terms of timing, accumulation, rate, and phase, depending on location, season, circulation patterns, and atmospheric conditions. Precipitation forecasts, especially snowfall, are essential to supporting drought mitigation and water management in the Intermountain West. Because rainfall and snowfall lead to opposite effects on snowpack, accurately partitioning rain and snow is important to estimate snowpack levels, winter recreation, mountain ecosystems and runoff. The research findings in this dissertation have advanced the understanding and prediction of precipitation and snowpack in the U.S. by addressing the …

Toward The Significance Of Crevasse Orientation In Low And High Crevassed Regions On The Kennicott Glacier, Alaska, Usa, Claire A. Sturm

DePaul Discoveries

Supraglacial landforms serve as potential indicators of underlying bedrock morphology and glacier dynamics. The distribution and morphology of crevasses are closely associated with stress fields and ice-flow regimes, representing processes of stable glaciers, in contrast to their reduced occurrence in stagnant or receding ice masses. The orientation and density of crevasses influence a glacier’s ability to absorb solar energy, as they facilitate movement of meltwater down to subglacial rivers. Beyond the meltwater acting as a lubricant for basal sliding, the slope of the bedrock further impacts the local velocity and ice deformation of a glacier. The study of ice-fracturing mechanics …

Clearing The Air: Tracking Spatial And Temporal Pm2.5 Variability Along A Biking Transect In Chicago, Beau R. Rass

DePaul Discoveries

Fine particulate matter (PM₂.₅) poses significant risks to human health and disproportionately affects marginalized communities in urban environments (World Health Organization [WHO], 2021; Tessum et al., 2021). Using low-cost mobile sensors, this study explored spatiotemporal PM₂.₅ concentration patterns along a north–south transect of Halsted Street in Chicago. A 2B Technologies Portable Aerosol Monitor (PAM) mounted on a bicycle was used to continuously record PM₂.₅ concentrations with associated GPS coordinates at approximately two-second intervals during 16 sampling events between 08-12-2025 and 10-05-2025. PM₂.₅ concentrations did not differ significantly among the South Side, West Loop, and North Side regions, contrary to the …

Synoptic Conditions Favoring Tropical Cyclone-Enhanced Southwest Monsoon High Precipitation Events In The Philippines, Alwin Andriel L. Bathan, Lyndon Mark P. Olaguera, Faye Abigail T. Cruz, Jose Ramon T. Villarin, John A. Manalo, Jun Matsumoto

SOSE Affiliate: Manila Observatory

The interaction of tropical cyclones (TCs) with the southwest monsoon frequently causes heavy precipitation events (HPEs) and widespread flooding across the Philippines. Despite their substantial socio-economic impacts, the synoptic conditions that favor these events remain insufficiently understood, underscoring the need for systematic investigation to help improve forecasting and risk assessment. Lag composite analysis of daily rainfall records and reanalysis data from July to September for the period 1981–2023 shows that HPEs are more likely to occur when: (1) enhanced monsoon westerlies are present over the tropical Indian Ocean for at least nine days before the HPE, (2) a TC passes …

The Impact Of Madden-Julian Oscillation On Rainfall Variability In South Sulawesi And Its Implications For Science Education, Misbahuddin Mansur, Pariabti Palloan, Agus Susanto

Jurnal Pendidikan Sains

This study examined the relationship between the Madden–Julian Oscillation (MJO) and rainfall variability in South Sulawesi Province, Indonesia, using daily rainfall observations from 24 stations during 1990–2020. A quantitative observational design based on long-term climatological time-series analysis was employed. MJO activity was identified using the Real-time Multivariate MJO (RMM) index, while rainfall variability was analyzed through rainfall anomalies, rainfall frequency, and spatial patterns across Seasonal Zones (ZOM). The results indicate that active MJO phases were generally associated with wetter conditions and higher rainfall frequency, whereas suppressed phases corresponded to drier conditions. Rainfall responses varied considerably among regions, with coastal areas …

A Statistical Analysis Of Current And Future Hurricane Activity In The North Indian Ocean, Basil Lund

2026 Symposium

A hurricane is defined as a tropical storm with winds sustained at 74 mph or greater. I examined major (category 3 and above) hurricane activity over the North Indian Ocean from the years 1972-2019 as reported by Colorado State University Hurricane Forecast Archive. Using RStudio, I conducted a binomial analysis of the CSU dataset to calculate probabilities of zero to ten years with one or more major North Indian Ocean hurricanes in the next decade. I conducted a geometric analysis to determine probabilities associated with waiting periods for the next year with a major hurricane, as well as a Poisson …

Evapotranspiration Everywhere, All The Time: Towards A Unified View From Earth Observation, Joshua B. Fisher, Martha C. Anderson, Diego G. Miralles, Kanishka Mallick, Paul C. Stoy, Youngryel Ryu, Wim G. M. Bastiaanssen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Scientists want to know everything, everywhere, and all the time. This is particularly true in Earth science, where we seek to understand processes that span from the molecular to the planetary scale in how the world works, how it affects us, and how we impact it—especially the water cycle. Evapotranspiration (ET) was the last component to be measured in closing the water cycle: for decades, closing the water budget meant adding up all the measurable components, then inferring ET as the residual. Early measurements relied on water loss from pans and weighing lysimeters, followed by sensors inserted into plants to …

Examining Extremes: A Comparison Between Machine Learning Based Southwestern Conus Seasonal Drought And High Fire Risk Event Synoptic Climatologies, Ethan M. Greenberg

School of Natural Resources: Dissertations, Theses, and Student Research

The Southwestern United States (SW CONUS), comprised of California, Arizona, Nevada, and Utah, is a vast region that tens of millions of people call home. Hosting ecosystems ranging from grasslands and shrublands to temperate forests and climate zones ranging from Mediterranean climates to arid deserts, the region is nearly unanimously prone to intense droughts and devastating wildfires. While fire weather conditions and drought are often studied separately or mentioned as background conditions for the other, there are relatively few studies that compare the typical meteorological conditions between the two. This study aims to more closely understand the meteorological relationship between …

Spatiotemporal Variability Of Differential Reflectivity (Zdr) Columns Due To Environment In Tornadic And Nontornadic Supercells, Adrianne J. Engel

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

Polarimetric signatures have been of interest to researchers and operational forecasters since the completion of the WSR-88D network upgrade in 2013. Differential reflectivity (Z_DR) columns, which are collocated with supercell updrafts, are the focus of this study. Microphysical distributions within these signatures can be used to infer updraft strength and elucidate the processes responsible for updraft intensity and evolution. Z_DR column depth, areal extent, and variability of these metrics through space and time are assessed in a dataset of 114 nontornadic and tornadic supercells. Means of column metrics in nontornadic, non-tornado-producing, and tornado-producing analysis times are evaluated …

Atmospheric Remote Sensing Using X-Band Radar In The Marine Atmospheric Surface Layer, Daniel P. Greenway

Electronic Theses and Dissertations

Atmospheric remote sensors have always offered promising technological advancements for measuring atmospheric properties over large spatial areas at high spatiotemporal resolution – a feat not currently possible with present atmospheric measurement technologies. However, remote sensors do not measure these atmospheric properties directly; they rely on robust calibrations or conversions, complex mathematical inversion methods, and/or machine learning to retrieve these properties. These inverse methods rely on the selection of an objective function, a machine learning technique, and an accurate parameterization for atmospheric property estimation. By leveraging inverse methods to improve the characterization of properties measured by remote sensors, this work enables …

Clear-Air Turbulence Climatology And Trends, Liam Rodgers, Mark Sinclair

Publications

Clear‑air turbulence (CAT) is a major aviation hazard that occurs near airline cruising altitudes in both cloud and cloud‑free environments. Its lack of a distinct visual signature makes detection and avoidance difficult. CAT is associated with wind shear near jet streams, gravity waves, and Kelvin–Helmholtz instability and may be further enhanced by climate change. This study examines the climatology, spatial distribution, seasonal variability, and trends of CAT over the contiguous United States.

Pilot Reports (PIREPs) from 2001–2025 between 100 and 400 hPa are analyzed alongside jet stream, shear, and stability diagnostics derived from NCEP–NCAR Reanalysis data. Proxies such as inverse …

Warming Climate Amplifies Vapor Pressure Deficit Limits On Gross Primary Productivity, Shiqin Xu, Nate G. Mcdowell, Tim R. Mcvicar, Diego G. Miralles, Stephen Sitch, Pablo Sanchez-Martinez, Joshua B. Fisher, Pierre Friedlingstein, Hylke E. Beck, Matthew F. Mccabe

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Ongoing climate warming may profoundly impact terrestrial gross primary productivity (GPP), a key component of the global carbon cycle. However, uncertainty in the relative roles of atmospheric water demand (vapor pressure deficit, VPD) and root-zone soil moisture (SM) limits predictions of drought impacts on GPP. Here, we show that growing-season GPP was more strongly constrained by VPD than SM globally, based on observation-constrained model estimates, satellite retrievals and Dynamic Global Vegetation Model simulations. The importance of VPD increased with higher temperatures and more severe and prolonged droughts. This pattern reflects VPD’s critical role in regulating stomatal conductance and plant hydraulic …

Assessing Hyperlocal And Local Air Quality Through Passive Samplers And Low-Cost Monitors, Yan He

McKelvey School of Engineering Graduate Student Theses & Dissertations

Air pollution is a major environmental health concern and has been associated with respiratory disease, cardiovascular morbidity, metabolic disorders, premature mortality, and additional adverse health outcomes. Air pollution often exhibits substantial variability at fine spatial scales, yet conventional regulatory monitoring networks are too sparse to resolve neighborhood-level exposure gradients that may exist in many urban and rural communities. Hyperlocal differences in pollutant concentrations—driven by local emission sources, land use characteristics, atmospheric chemistry, and meteorological conditions—can lead to systematic differences in long-term exposure among populations living only short distances apart. Improving exposure characterization therefore requires dense monitoring strategies and spatial modeling …

Impact Of In Situ Observations From Three Torus Cases On Model Analyses And Forecasts Of Severe Convection, Robert M. Szot

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

The quality of forecasts of severe deep convection in high-resolution numerical weather prediction is dependent on the representativeness of the model initial conditions. This representativeness may be negatively impacted by limited observation availability and by the presence of mesoscale heterogeneities that were not detected by conventional observations assimilated into convection-allowing models. By assimilating storm-scale observations from the Targeted Observation by Radars and Uncrewed Aircraft Systems (UAS) of Supercells (TORUS) campaign into an ensemble styled after the Warn-on-Forecast System, this study aims to investigate if data from field work platforms can improve the quality of initial conditions in the ensemble, potentially …

Developing A Multi-Band Gnss Remote Sensing Station To Measure Precipitable Water Vapor For Flash Flood Nowcasting, Madison Gleydura

Doctoral Dissertations and Master's Theses

Flash flood nowcasting in Central and Southern Appalachia is particularly challenging due to steep terrain, narrow valleys, highly localized rainfall patterns, and limited measurement coverage. Traditional remote sensing methods, such as Doppler radar and microwave radiometry, suffer from reduced resolution at long range and signal blockage by mountains. GNSS-meteorology offers an established alternative for measuring precipitable water vapor and is currently integrated into several numerical weather models. Recent research demonstrates that commercial-grade GNSS receivers can produce tropospheric products comparable to those from geodetic-grade equipment. The gaps in mountain coverage can be addressed by developing a low-cost, self-contained embedded system that …

Projections Of The Characteristics Of Extreme Precipitation In East Africa Using Bias-Corrected Cmip6 Models, Exavery K. Makula

Tanzania Journal of Science

In the context of ongoing global climate change, the intensification of the hydrological cycle is expected to modify the frequency, magnitude, and spatial distribution of extreme precipitation events. Understanding how precipitation extremes will evolve under climate change is critical for East Africa (EA), a region highly vulnerable to hydroclimatic hazards and strongly dependent on rainfall-driven socioeconomic systems. The region experiences two main rainfall seasons, namely the long rains (March-May, MAM) and the short rains (October-December, OND). This study investigates future projections of the characteristics of extreme precipitation across the EA using an ensemble of biascorrected CMIP6 global climate models. Extreme …

Changes In Land, Ocean, Atmospheric Parameters Associated With The 2025 Myanmar (Mw 7.7) Earthquake, Feng Jing, Akshansa Chauhan, Ashwani Raju, Ramesh P. Singh

Mathematics, Physics, and Computer Science Faculty Articles and Research

Multiple parameters associated with the land, atmosphere, and ocean were analyzed to study short-term and immediate pre-earthquake changes associated with the 28 March 2025 Myanmar earthquake (Mw 7.7). Anomalous clear-sky outgoing longwave radiation (ClrOLR) and trace gases (CH₄, CO, and O₃) were detected within two months prior to the mainshock. Vertical changes at different pressure levels suggest a possible underground source. High-temporal-resolution observations of the infrared brightness temperature and surface air pressure revealed short-lived fluctuations shortly before the earthquake, which may reflect localized stress adjustments and surface latent heat flux release during the final stage of earthquake preparation. In the …

Constraints To Adopting Locally Based Innovation Systems In Adapting To Climate Change Impacts In Serengeti District, Tanzania, Donald Mwiturubani

Journal of Humanities and Social Sciences

Smallholder farmers in rural Tanzania depend mainly on rain-fed agriculture, which makes them vulnerable to the impacts of climate change. This paper is based on a study conducted in Burunga and Musati villages in Serengeti District, Tanzania. The study employed a mixed methods approach; combining qualitative and quantitative methods. It involved 154 participants and employed household surveys, key informant interviews, and focus group discussions as data collection methods. The findings suggest that smallholder farmers in the study area are aware of climate change and do, indeed, develop, adopt, and use locally-based innovation systems that avert or minimise its impacts. Smallholder …

Long-Term Variability Of Air Quality And Greenhouse Gas Emissions From Rice Crop Burning In Punjab During 2012–2020, Harsimranjit Kaur Romana, Dericks Praise Shukla, Ramesh P. Singh

Mathematics, Physics, and Computer Science Faculty Articles and Research

Punjab, India's primary rice and wheat production hub, has witnessed rapid expansion of paddy cultivation over the past two decades, driven by minimum support price incentives, changes in government policies, alignment of sowing with the monsoon season and the adoption of high-yielding varieties. This transition has intensified groundwater extraction and shortened the fallow period between rabi and kharif crop seasons, reducing the window between rice harvesting and wheat sowing, leading to widespread open-field burning of rice residue and recurrent post-monsoon air-quality deterioration across the Indo-Gangetic Plain. Despite numerous short-term or single-pollutant assessments, a spatially resolved, multi-pollutant and multi-decadal evaluation linking …

Characterizing Atmospheric Turbulence With The Lunar Step Response Method, Patrick D. Carattini, Caleb J. Stilp, Katelyn M. Atkinson, Stephen C. Cain

Faculty Publications

Most methods that astronomers use to characterize the strength of atmospheric turbulence in and around their observatories use differential image motion monitors observing a star to provide the necessary data for the measurement. With the Moon becoming a greater national priority, the need to characterize atmospheric paths between observatories on Earth and the Moon is potentially going to grow in the future. To this end, the differential image motion monitor is not an ideal instrument for characterizing turbulence along paths between observatories and the Moon as the bright Moon makes it difficult to detect and locate stars in its vicinity. …

Automated Machine Learning For High-Resolution Daily And Hourly Methane Emission Mapping For Rice Paddies Over South Korea: Integrating Modis, Era5-Land, And Soil Data, Jiah Jang, Seung Hee Kim, Menas Kafatos, Jaeil Cho, Gayoung Yoo, Sujong Jeong, Yangwon Lee

Institute for ECHO Articles and Research

Agriculture is a major global source of methane (CH4), and accurate emission estimates are essential for refining national greenhouse gas inventories and supporting climate-resilient policies. This study develops a high-resolution estimation framework for CH4 emissions from Korean rice paddies by integrating multi-source datasets, including Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis Version 5 (ERA5)-Land meteorological variables, and Harmonized World Soil Database (HWSD) soil properties. Using CH4 flux observations from four global rice ecosystems (Italy, Japan, South Korea, and USA), we constructed parallel daily and hourly machine learning models using an automated machine …