Atmospheric Sciences Commons^™

An Evaluation Of Current And Future Extreme Precipitation Events In The South American Altiplano Using Convective-Permitting Model Simulations, Karen R. Conron Chamberlain

Electronic Theses & Dissertations (2024 - present)

Extreme precipitation events in the South American Altiplano present significant hazards to communities in the Andean region, yet their future characteristics under anthropogenic climate change remain uncertain because of complex terrain and limitations of course-resolution climate models. This study evaluates the ability of South America Affinity Group Weather Research and Forecasting (SAAG-WRF) model with 4-km grid-spacing to reproduce 2000-2015 temperature, precipitation, and extreme precipitation events over the Altiplano. Examination of projected future changes is completed using the SAAG-WRF pseudo global warming (WRF PGW) simulation representing an approximately 3°C warmer global climate. The historical/control simulation (WRF CTL) was evaluated against DECADE …

Drivers Of Extreme Streamflow During A Snowmelt-Enhanced Heavy Rainfall And Atmospheric River Event In The Catskill Mountains Of New York, Christopher A. Gilberti

Electronic Theses & Dissertations (2024 - present)

This study uses atmospheric reanalysis, precipitation and snow water equivalent (SWE) analyses, mesonet observations, and streamflow records to examine the impact of an atmospheric river storm that produced heavy rainfall and snowpack ablation across the Catskill Mountains of New York on 24–25 December 2020. Earlier in December, an antecedent storm produced SWE values in the Catskills above the 90^th percentile for that point in the season. The atmospheric river event followed with strong southerly warm-air advection ahead of an anomalously deep trough, temperatures and dewpoints that exceeded 10°C, and heavy orographically enhanced rainfall and rapid snowmelt. Sensible heat fluxes …

The Predictability And Verification Of Precipitation From Landfalling Tropical Cyclones Using An Object-Based Framework, Melissa Piper

Electronic Theses & Dissertations (2024 - present)

Precipitation from landfalling tropical cyclones (TCs) poses a significant risk to life and property in both coastal and inland communities. Early warning systems can help mitigate the impacts of TC-induced flooding; however, this requires accurate quantitative precipitation forecasts (QPFs). Forecasting precipitation from landfalling TCs is a challenge, as the intensity, duration, and location of precipitation can be dependent on numerous storm-related and environmental factors. Previous studies have attempted to identify and correct NWP model deficiencies and reduce forecast uncertainty by applying traditional and advanced verification metrics to TC QPF. However, these studies have mostly used gridpoint verification metrics, limited samples …

Weather-Related Road Condition Detection Using Co-Developed Machine Learning Methods, Carly Sutter

Electronic Theses & Dissertations (2024 - present)

Transportation agencies make critical operational decisions during hazardous weather events, including assessment of road conditions and resource allocation. In this study, machine learning models are developed to provide additional support for the New York State Department of Transportation (NYSDOT) by automatically classifying road conditions across the state. Convolutional neural networks and random forests are trained on NYSDOT roadside camera images and weather data to predict road surface conditions. This task draws critically on a labeled dataset of 22,000 camera images containing six road surface conditions (severe snow, snow, wet, dry, poor visibility, and obstructed) generated from an iterative hand-labeling process …

On The City-Scale Energy Balance Under Electrification And Renewable Generation: The New York City Case, Nour Elgalad

Electronic Theses & Dissertations (2024 - present)

Integration of renewable resources to meet the growing energy demand of dense urban regions is becoming a global priority under decarbonization mandates. This study contributes to these ongoing efforts by assessing the feasibility of using locally deployable urban renewable resources, namely offshore wind in the New York Bight region and rooftop photovoltaic (PV) systems over New York City, to meet the electricity demand of the city, and the grid vulnerabilities that emerge, during two contrasting extreme-weather periods: the intense heatwave of June 2025 and a fully electrified winter cold snap in January 2018. A unified, meteorologically driven modelling framework, based …

Analysis Of The Thermodynamic Variables Associated With Hawaiian Extreme Precipitation Using The Fraction Of Attributable Risk (Far), Matthew J. Sinnenberg

Electronic Theses & Dissertations (2024 - present)

The Hawaiian Islands experience extreme maxima in precipitation that vary spatially, by season, and in response to different teleconnection patterns. Due to the islands’ unique geography, they are not well-resolved by global climate models, necessitating a focused assessment to identify  climatological trends. In this study, a probability-based analysis was conducted on regionally averaged thermodynamic variables relevant to the formation of extreme events. The primary objective was to evaluate whether changes in the occurrence of extreme conditions have occurred and to understand how the El Niño-Southern Oscillation (ENSO) influences these occurrence rates.

Hourly data from ERA5 spanning 1980-2019 were resampled to …

Applications Of Machine Learning For Evaluating Downward-Coupled Stratosphere-Troposphere Interactions And Subseasonal Forecasts Of Opportunity, Elena M. Fernandez

Electronic Theses & Dissertations (2024 - present)

Wintertime stratospheric dynamics provide key information for understanding atmospheric teleconnections and improving subseasonal-to-seasonal (S2S) predictions on timescales of two weeks to two months. Periods of enhanced predictability, often referred to as forecasts of opportunity, arise from large-scale teleconnected variability, within which the stratosphere serves as an important precursor for tropospheric states, such as near-surface temperatures. While traditional diagnostics of downward coupled stratosphere-troposphere interactions typically rely on zonal-mean representations of wind and geopotential height, this dissertation presents an alternative vortex-centric framework through metrics that capture the daily geometric and dynamical evolution of the stratospheric polar vortex. The proposed stratospheric …

Real-Time Production Of High-Resolution, Gap-Free, 3-Hourly Aod Over South Korea: A Machine Learning Approach Using Model Forecasts, Satellite Products, And Air Quality Data, Seoyeon Kim, Youjeong Youn, Menas Kafatos, Jaejin Kim, Wonsik Choi, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Aerosol optical depth (AOD) is essential for air quality monitoring and climate research. However, satellite-based retrievals suffer from cloud-related data gaps, and reanalysis products are limited by coarse spatial resolution and substantial production latency. This study develops a real-time, gap-free, high-resolution (1.5 km) AOD retrieval system for South Korea. The system integrates Copernicus Atmosphere Monitoring Service (CAMS) forecasts, high-resolution meteorological fields, and ground-based air quality observations within a machine learning framework. Three models with varying training periods were systematically evaluated using cross-validation and independent validation with 2024 Aerosol Robotic Network (AERONET) data. The optimal model, trained on 2015–2023 data, achieved …

Performance Comparison Of Kriging Models Used For Estimation Of Rainfall Variability In The Northern Coast Of Tanzania, Salma Suleiman, Clement Mromba

Tanzania Journal of Science

Accurate rainfall estimation underpins effective disaster preparedness and sustainable socioeconomic planning. The performance of Ordinary Kriging (OK), Universal Kriging (UK), and Simple Kriging (SK) in estimation of rainfall variability were assessed across eight stations in the northern coast of Tanzania for the period from 1960 to 2020. Using ArcGIS 10.3, each method was evaluated and cross-validated using six performance metrics, namely; Mean Error (ME), Mean Square Error (MSE), Root Mean Square Error (RMSE), Root Mean Standardized Square Error (RMSSE), Average Standardized Error (ASE), and the Coefficient of Determination (R²). Performance comparison results indicate OK to have achieved the lowest bias, …

Multi-Satellite Image Matching And Deep Learning Segmentation For Detection Of Daytime Sea Fog Using Gk2a Ami And Gk2b Goci-Ii, Jonggu Kang, Hiroyuki Miyazaki, Seung Hee Kim, Menas Kafatos, Daesun Kim, Jinsoo Kim, Yangwon Lee

Institute for ECHO Articles and Research

Traditionally, sea fog detection technologies have relied primarily on in situ observations. However, point-based observations suffer from limitations in extensive monitoring in marine environments due to the scarcity of observation stations and the limited nature of measurement data. Satellites effectively address these issues by covering vast areas and operating across multiple spectral channels, enabling precise detection and monitoring of sea fog. Despite the increasing adoption of deep learning in this field, achieving further improvements in accuracy and reliability necessitates the simultaneous use of multiple satellite datasets rather than relying on a single source. Therefore, this study aims to achieve higher …

Understanding Enso Through Mathematical Models, Maria I. Sanchez Muniz

Open Educational Resources

This assignment introduces students to conceptual models of the El Niño–Southern Oscillation (ENSO) and guides them through a structured investigation of their physical and mathematical foundations. Students analyze the recharge–oscillator and delayed–oscillator frameworks, explore how differential equations capture ocean–atmosphere interactions, and evaluate parameter-driven changes in oscillatory behavior. A key component of the work is the guided use of generative AI as a research tool: students employ AI models to locate peer-reviewed literature, interrogate model extensions, and refine their understanding of complex mechanisms, while synthesizing all final explanations in their own words. By blending classical climate modeling with modern AI-supported inquiry, …

Lead Sources Detected In Manila's Air After The Phase-Out Of Leaded Gasoline, Grace Betito, Paola Angela Bañaga, Maria Obiminda L. Cambaliza, Melliza Templonuevo Cruz, James Bernard Simpas, Mengli Chen, Jariya Kayee, Armin Sorooshian, Rachel A. Braun, Alexander B. Macdonald

Ateneo Atmospheric Physics Laboratory

Abstract

The global phase-out of leaded gasoline marked a major milestone in pollution control, yet modern uses of lead (Pb) continue to pose significant health risks, especially in low- and middle-income countries. In the Philippines, significant data gaps still exist despite increasing exposure. This study presents to the best of our knowledge, the first Pb isotopic fingerprinting of atmospheric aerosols in Metro Manila, Philippines, covering fine (0.56–1 μm) and coarse (5.6–10 μm) fractions, collected in 2018–2019. Results show that local sources, mainly industrial activities (45–62 %) and fossil fuel combustion (30–45 %), are now the dominant contributors to airborne Pb, …

Rainfall-Runoff Modelling In An Indonesian Humid Tropical Area Using Satellite-Based Precipitation Products, Noordiah Helda

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation explores three rainfall-runoff models in the humid tropical regions of Indonesia using satellite-based precipitation products (SBPPs) and develops integrated machine-learning modeling frameworks. Several ground-based observations from BMKG (Badan Meteorologi, Klimatologi, dan Geofisika (also known as the Indonesian Agency for Meteorology, Climatology, and Geophysics)) stations across Indonesia (133−165 stations) are compared and evaluated against satellite products, indicating that GPM performs well, with R-squared values ranging from 0.54 to 0.76 and correlation coefficients ranging from 0.45 to 0.69, respectively.

In the Martapura Watershed, South Kalimantan, due to a lack of observational discharge data, streamflow was generated using the FJ Mock …

The Urban Heat Island And Its Role In Shaping Convective Environments: An Observational Study, Benjamin W. Moll

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

The continued spread of urbanization and its well-documented effects on regional weather and climate necessitate further research. Urban environments are often warmer and drier than their rural surroundings. This trade-off between a warmer but drier environment could have a complex impact on deep convection and its initiation. Previous studies have noted significant changes in precipitation patterns around cities as well as changes to ongoing deep convection. Given the well-documented theory and past research, it is hypothesized here that urban areas have a significant impact on the PBL thermodynamics of convective environments. The urban heat island (UHI) component of the Micro …

Modeling Aerosol Transport During High Particulate Matter Episodes In El Paso-Juarez Region And Mitigating Mining-Related Emissions Of Rare Earth Elements (Rees) To The Air, Suzan Aranda Luna

Open Access Theses & Dissertations

This dissertation examines the use of the HYSPLIT model to develop a methodology for the transport and dispersion of air masses affecting particulate matter (PM) concentrations in the El Paso Region, and bioleaching experiments as an alternative to mitigating rare-earth concentrations in the air. Chapter 2 describes the study methodology, 3 and 4 cover the modeling methodology using two-representative high PM2.5 episodes, occurring on February 28, 2024, and June 19, 2024, respectively. These sections encompass the analysis of backward trajectories using four different meteorological datasets to build trajectory frequency maps, the exploratory model analysis of modeled outputs from lower to …

Aluminum As A Tracer Of Dust Deposition To The Ocean: A Case Study From The Bermuda Region, Tara Elizabeth Williams

OES Theses and Dissertations

Aluminum (Al), a major component of mineral aerosol (dust), partially dissolves in seawater and is widely used as a tracer for estimating time‐averaged dust fluxes to the ocean. Such estimates rely on dissolved Al (DAl) inventories in the surface mixed layer (SML), an assumed SML residence time of DAl (_TDAl), the fractional solubility of Al in dust (Al_S), and the mass fraction of Al in dust. In this study, dust flux estimated from seasonal, water-column DAl data from the Bermuda Atlantic Time-series Study (BATS) region are compared with direct dust flux estimated from contemporaneous measurements of …

Lidar And Radar Investigations Of Gravity Wave Activity In The Middle Atmosphere At Pfrr, Chatanika, Alaska, Satyaki Das

Atmospheric Sciences

The middle atmosphere, spanning the stratosphere and mesosphere, plays a critical role in global atmospheric circulation, particularly in the Arctic, where phenomena like Sudden Stratospheric Warmings (SSW) significantly perturb the circulation patterns. This dissertation investigates the dynamics of the polar middle atmosphere using four-year (20218-2022) temperature and wave activity measurements collected by the three-channel Rayleigh Density Temperature Lidar, Sodium Resonance Wind-Temperature Lidar, and Poker Flat Meteor Wind Radar at Poker Flat Research Range, Chatanika, Alaska (650N,1470W). The primary contributions are the development of a new lidar signal retrieval technique to combine the signal from three-channels and improve the lidar signal …

Climate Change Has Increased Global Evaporative Demand Except In South Asia, Saeed Karimzadeh, Arman Ahmadi, Dennis Baldocchi, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate change alters how strongly the atmosphere draws water from the land, yet a consistent global assessment of this evaporative demand has been lacking. Here, we analyze 45 years of climate data and global models to quantify trends in the key drivers—air temperature, humidity, radiation, wind speed, and cloud cover—that determine the atmosphere’s drying power. We find that evaporative demand has increased worldwide, indicating a stronger atmospheric thirst, except in South Asia, where it has declined. There, widespread irrigation has increased soil and air moisture, enhanced cloud formation, and reduced sunlight reaching the surface, counteracting the global signal. These contrasting …

An Objective Method To Locate Shear Lines During The Northeast Monsoon Season In The Philippines, Lyndon Mark P. Olaguera, John A. Manalo, Jun Matsumoto, Faye Abigail T. Cruz, Jose Ramon T. Villarin

SOSE Affiliate: Manila Observatory

The shear line is a narrow zone of maximum horizontal wind shear, typically identified as a confluence zone of low-level wind streams. Previous studies showed that this system can trigger heavy to extreme rainfall events in the Philippines during the northeast monsoon season. However, a research gap remains in objectively identifying and locating this system. Thus, this study develops a detection method that may be used for monitoring and forecasting the location of shear lines. Results show that the gradient of meridional winds in the y-direction (∂V925hPa/∂y), the boundary layer moisture flux convergence, and the 925 hPa relative vorticity may …

Characterizing Meteorological Patterns For Oregon's Winter Elevated Pm2.5 Concentrations From 2000-2023, Arielle Golda Sherbak

Dissertations and Theses

Valleys and basins are uniquely susceptible to the buildup of air pollution during the wintertime due to cool, dense air pooling under favorable meteorological conditions, a common occurrence in the Intermountain West. In Oregon, wintertime anthropogenic air pollution is primarily from woodburning stoves and heaters and although efforts have been made to reduce wintertime pollution, stagnation events continue to result in decreased air quality. This analysis aims to understand the relationship between air pollution in six Oregon counties and the associated meteorology in the cool season (November-March) using a 2000-2023 climatology.

This is completed through a composite analysis using key …