Atmospheric Remote Sensing Using X-Band Radar In The Marine Atmospheric Surface Layer,
2026
Coastal Carolina University
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 …
Examining Extremes: A Comparison Between Machine Learning Based Southwestern Conus Seasonal Drought And High Fire Risk Event Synoptic Climatologies,
2026
University of Nebraska-Lincoln
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,
2026
University of Nebraska-Lincoln
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 (ZDR) 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. ZDR 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 …
A Climatology Of Sudden Stratospheric Warmings And Their Tropospheric Response,
2026
Embry-Riddle Aeronautical University
A Climatology Of Sudden Stratospheric Warmings And Their Tropospheric Response, Joe Lovelien, Mark Sinclair
Publications
Sudden Stratospheric Warmings (SSWs) are major disruptions of the wintertime polar vortex that can significantly influence surface weather, including cold air outbreaks (CAOs) across the midlatitudes. This study presents a climatology of SSWs from 1948-2024 using NCEP-NCAR reanalysis data and examines their temporal distribution, relationships with large-scale climate variability, and impacts on surface temperatures in the United States. SSWs are identified using previously published definitions based on the reversal of zonal-mean winds at 60°N and 10 hPa. A total of 44 SSW events were identified, with a strong seasonal preference for January through March. Some decadal variability is observed, though …
Warming Climate Amplifies Vapor Pressure Deficit Limits On Gross Primary Productivity,
2026
King Abdullah University of Science and Technology
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,
2026
Washington University – McKelvey School of Engineering
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 …
Dynamics And Energetics Of Fast Waves From The Earth's Surface To The Lower Thermosphere,
2026
Embry-Riddle Aeronautical University
Dynamics And Energetics Of Fast Waves From The Earth's Surface To The Lower Thermosphere, Richard L. Walterscheid, Michael P. Hickey Ph.D.
Publications
We use a Full Wave Model to examine the dynamics and energetics of waves that can be excited in the troposphere by a large explosive event. We find resonant structures in phase speed wavenumber space that can have substructures with distinct properties. The primary waves found are Lamb waves and fast deep waves (denoted 𝐿′) that have a hybrid internal-external wave nature and were recently identified in observations. Lamb waves and thermospherically ducted waves are branches of two continuous forms separated by a gap in which Lamb waves are preempted by Lamb speed waves oscillating with the buoyancy frequency. We …
Developing A Multi-Band Gnss Remote Sensing Station To Measure Precipitable Water Vapor For Flash Flood Nowcasting,
2026
Embry-Riddle Aeronautical University
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 …
Impact Of In Situ Observations From Three Torus Cases On Model Analyses And Forecasts Of Severe Convection,
2026
University of Nebraska-Lincoln
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 …
Projections Of The Characteristics Of Extreme Precipitation In East Africa Using Bias-Corrected Cmip6 Models,
2026
Environmental and Atmospheric Sciences Group, Department of Physics, University of Dar es Salaam, P.O. Box 35063, Dar es Salaam, Tanzania
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,
2026
China Earthquake Administration
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,
2026
University of Dar Es Salaam
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,
2026
Indian Institute of Technology (IIT) Mandi
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,
2026
Air Force Institute of Technology
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,
2026
Pukyong National University
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 …
A Unified Methodological Framework For Generating Digital Twins Of Multi Class Uncrewed Systems (Uxs),
2026
University of South Alabama
A Unified Methodological Framework For Generating Digital Twins Of Multi Class Uncrewed Systems (Uxs), Sai Raghava Pathuri
Shelby Hall Graduate Research Forum Presentations
No abstract provided.
Deep Learning Style Transfer For Enhanced Smoke Plume Visibility: A Standardized False Color Composite (Sfcc) In Gems Satellite Imagery,
2026
Pukyong National University
Deep Learning Style Transfer For Enhanced Smoke Plume Visibility: A Standardized False Color Composite (Sfcc) In Gems Satellite Imagery, Yemin Jeong, Seung Hee Kim, Menas Kafatos, Jeong-Ah Yu, Kyoung-Hee Sung, Seung-Yeon Kim, Goo Kim, Jae-Jin Kim, Yangwon Lee
Institute for ECHO Articles and Research
Wildfire smoke visualization using geostationary satellite imagery is essential for real-time monitoring and atmospheric analysis; however, inconsistencies in color tone across Geostationary Environment Monitoring Spectrometer (GEMS) images hinder reliable interpretation and model training. This study proposes a Standardized False Color Composite (SFCC) framework based on deep learning style transfer to enhance the visual consistency and interpretability of wildfire smoke scenes. Four tone-standardization methods were compared: the statistical Empirical Cumulative Distribution Function (ECDF) correction and three neural approaches—ReHistoGAN, StyTr2, and Style Injection Diffusion Model (SI-DM). Each model was evaluated visually and quantitatively using six metrics (SSIM, LPIPS, FID, histogram similarity, ArtFID, …
A Systematic Literature Review On The Influence Of The El Niño Southern Oscillation On Rainfall Variability In Central Java, Indonesia,
2026
Universitas Negeri Semarang, Indonesia and Meteorology, Climatology and Geophysics Agency, Indonesia
A Systematic Literature Review On The Influence Of The El Niño Southern Oscillation On Rainfall Variability In Central Java, Indonesia, Sri Endah Ardhi Ningrum Abdullah, Trinah Wati, Wahyu Hardyanto
Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi
The El Niño-Southern Oscillation (ENSO) phenomenon greatly influences rainfall variability in tropical regions, including Central Java, Indonesia. This study employs a Systematic Literature Review (SLR) approach in accordance with the PRISMA guidelines. This study examines 50 articles from 2010 to 2025, as well as conducting a bibliometric analysis using VOSviewer, to identify trends and the evolution of themes. The results of the study indicate that El Niño generally reduces rainfall and increases the risk of drought, while La Niña tends to increase rainfall, potentially causing flooding. The impacts of ENSO extend to agriculture, food security, and water management, and are …
Observation-Based Reconstruction Of High-Resolution Daily Temperature Field Using Lapse-Rate-Constrained Kriging In Complex Terrain: A Nationwide Dataset For South Korea,
2026
Pukyong National University
Observation-Based Reconstruction Of High-Resolution Daily Temperature Field Using Lapse-Rate-Constrained Kriging In Complex Terrain: A Nationwide Dataset For South Korea, Youjeong Youn, Menas Kafatos, Seung Hee Kim, Yangwon Lee
Institute for ECHO Articles and Research
High-resolution air-temperature fields are essential for climate, hydrologic, and ecological applications in complex terrain, yet operational products often lack the spatial detail to resolve topographic effects. We develop an observation-driven reconstruction of daily air temperature fields for South Korea (2024) using ordinary kriging with lapse-rate correction (OKLR), integrating a dense network of over 500 stations from the Automatic Mountain Meteorology Observation System (AMOS) and the Automated Surface Observing System (ASOS). The OKLR framework systematically removes elevation-driven trends using a physically based fixed lapse rate (–6.5 °C km−1), performs kriging on detrended residuals, and reapplies Digital Elevation Model (DEM)-based corrections to …
Data And Code For "Stratocumulus Drizzle Readily, Cumulus Drizzle Selectively: Evidence From Four Oceanic Regions",
2026
Brookhaven National Laboratory
Data And Code For "Stratocumulus Drizzle Readily, Cumulus Drizzle Selectively: Evidence From Four Oceanic Regions", Katia Lamer
SoMAS Research Data
Data and Code for "Stratocumulus drizzle readily, cumulus drizzle selectively: evidence from four oceanic regions"
