Atmospheric Sciences Commons^™

Comparison Of Methane Emission Quantification Methods At Landfills In New York State, Alexandra M. Catena

Electronic Theses & Dissertations (2024 - present)

Greenhouse gas (GHG) emission increases are a consequence of global population rise and economic growth. It is well known that carbon dioxide is the dominant GHG by mass, but methane has received increasing attention recently due to its high warming potential and relatively short lifetime of about a decade. Methane has several different types of both natural and anthropogenic sources including wetlands, waste management, energy, agriculture and farming, and wildfires, which makes tracking and reducing methane emissions a complex problem. The emission rates of each of these sources are highly uncertain due to differing emission estimation methods, which can be …

Buoy-Based Eddy Covariance Drag Coefficient At A Near-Shore And Offshore Site, David P. Marcial

Electronic Theses & Dissertations (2024 - present)

An eddy covariance (EC) flux system was integrated onto a Navy Oceanographic Meteorological Automatic Device (NOMAD) floating lidar buoy fitted for measuring the offshore wind resource. The EC flux system consisted of two sonic anemometers and an inertial measurement unit that together provided high-frequency (10 Hz) motion-corrected wind measurements. To assess possible impacts of flow distortion, EC momentum fluxes (10 min) were calculated in gravity-aligned, natural, and planar fit (PF) coordinate frames. The buoy was anchored near the Martha’s Vineyard Coastal Observatory Air-Sea Interaction Tower (ASIT; near-shore) for validation of the buoy-based EC fluxes against the fixed tower measurements before …

The Response Of Tropopause Phenomena To Stratospheric Variability: Rossby Wave Breaking And Tropopause Polar Vortices, Cameron R. Paquette

Electronic Theses & Dissertations (2024 - present)

Variability in the high-latitude wintertime stratospheric flow, often referred to as the stratospheric polar vortex, can precede anomalous conditions in tropospheric flow on subseasonal-to-seasonal (S2S) timescales and impact surface weather. The range of stratospheric impacts on tropospheric conditions range from shifts in the North Atlantic storm tracks, formation of cold spells, and development of extreme precipitation. Impacts of stratospheric variability are known to persist for up to 60 days, providing ample windows of opportunity in forecasting on S2S timescales. This dissertation focuses on the stratospheric impacts on tropopause-level processes, such as Rossby wave breaking (RWB) events and tropopause polar vortices …

Limitations Of The High-Resolution Rapid Refresh Gust Algorithm, Alex M. Glasser

Electronic Theses & Dissertations (2024 - present)

ABSTRACT:

Accurate wind and gust forecasts are crucial in operational meteorology, yet there is a distinct gap in the literature regarding the verification of operational gust forecasts. In the present work, we assess the performance of the High-Resolution Rapid Refresh's (HRRR) gust potential, verifying it against the Automated Surface Observing System's (ASOS) observed gusts across the Continental United States (CONUS). The HRRR gust's diurnal cycle reveals a significant underprediction of the gust during daylight hours and a slight overprediction of the gust during hours of darkness. The daytime underprediction undermines the assumption that forecasts represent a potential that tends to …

Stratospheric Variability And Its Relationship To Cold Air Outbreaks In The United States, Paul T. Panhans

Electronic Theses & Dissertations (2024 - present)

Only since the early 2000s, has there been a growing body of work linking extreme winter temperature anomalies to the variability of the Northern Hemisphere stratospheric polar vortex (SPV). However, the understanding behind stratosphere-troposphere coupling and cold air outbreaks (CAOs) remain occasionally contradictory in the literature, making it difficult to properly articulate societal risks. Studies often focused on broad stratospheric influences, but this research directly compared stratospheric variability according to their respective tropospheric impacts. This dissertation filled a knowledge gap, as there has yet to be a comprehensive analysis to quantify the differences in stratospheric variability with and without CAOs …

A Dynamically Adapting Forecast Cone Based On Ensemble Spread, Michael N. Barletta

Electronic Theses & Dissertations (2024 - present)

Dynamically based ensemble prediction systems have gained considerable attention because they can provide a greater range of possible forecast outcomes and quantify the uncertainty in forecasts. In turn, forecasters can convey clearer messages to the public on the range of forecast scenarios and display inherent uncertainty in weather forecasts, which can be difficult to do with deterministic forecasts. Although global ensemble prediction systems have demonstrated skill in their probabilistic track predictions, the information contained within them is not always fully utilized beyond the mean forecast and standard deviation (i.e., spread). One way that these ensembles could be better employed is …

Validating Atmospheric Freezing Level Heights Using Purdue University Weather Balloon Data, Danielle Harr

The Journal of Purdue Undergraduate Research

No abstract provided.

A Meteorological Investigation Of A Tornado- Producing, “Hybrid” Supercell-Multicell Storm Near Delphi, Indiana, On May 8, 2023, Evelyn Rose K. Girardi

The Journal of Purdue Undergraduate Research

No abstract provided.

Discrimination The Roles Of Anthropogenic Greenhouse Gases And Aerosols On Tropical Cyclone Frequency From Downscaling Cmip6 Models, George Gyabaah

Theses and Dissertations

Tropical cyclones (TCs) are devastating disasters, yet predicting their future activity remains highly uncertain. To better understand the impacts of different anthropogenic forcings, specifically greenhouse gases (GHG) and aerosols on the TCs, I downscaled the single forcing experiments of 11 CMIP6 models in the Columbia HAZard Model (CHAZ). This analysis focused on changes in the distribution of the North Atlantic (ATL) and Western North Pacific (WNP) basins and explored the shift in environmental variables that drive them. We then used the formulation of the genesis component of CHAZ as a constraint to quantify the relative contribution of each predictor relative …

Advancing S2s Precipitation Outlooks Through The Weather Regime-Gaussian Mixture Model Framework, Wei Zhang

Funded Research Records

No abstract provided.

Modeling Hourly Storm Surges Using Deep Learning Techniques, Md Abu Zafor

Master's Theses

Storm surges cause coastal flooding, one of the most devastating coastal hazards. Accurate modeling of storm surges is essential for predicting and mitigating these impacts. Traditional approaches model surges at individual tide gauges and often focus on daily time scales, leading to data redundancy and limiting their ability to capture sub-daily variability. This study addresses these limitations using deep learning (DL) algorithms to model hourly surges simultaneously at multiple tide gauges along the U.S. East Coast and Gulf of Mexico. Three algorithms, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and a hybrid ConvLSTM are employed to model surges using …

An Integrated Study Of Aerosol Concentrations And Meteorological Conditions In El Paso Airshed Using Modeling And Instrumentation, Joscelyne Guzman-Gonzalez

Open Access Theses & Dissertations

Atmospheric aerosols are solid or liquid particles suspended in the atmosphere. Aerosols can be primary, which are directly emitted into the atmosphere, or secondary, which are formed when emitted gases undergo complex chemical reactions. Atmospheric aerosols can range from a few nanometers to tens of microns in diameter. Atmospheric aerosols play a significant role in climate; they can absorb or reflect heat, influencing temperature and weather patterns. Air quality is also affected by aerosols, which can have detrimental effects on human health, contributing to respiratory issues and other health problems. El Paso Texas is located at the south of the …

Spatial Gap-Filling Of Himawari-8 Hourly Aod Products Using Machine Learning With Model-Based Aod And Meteorological Data: A Focus On The Korean Peninsula, Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. Developed and validated over South Korea from 1 January to 31 December 2019, the model effectively improved data coverage from 6% to 100%. The approach demonstrated high performance in blind tests, …

Climatological Trends And Effects Of Aerosols And Clouds On Large Solar Parks: Application Examples In Benban (Egypt) And Al Dhafrah (Uae), Harshal Dhake, Panagiotis Kosmopoulos, Antonis Mantakas, Yashwant Kashyap, Hesham El-Askary, Omar Elbadawy

Mathematics, Physics, and Computer Science Faculty Articles and Research

Solar energy production is vastly affected by climatological factors. This study examines the impact of two primary climatological factors, aerosols and clouds, on solar energy production at two of the world’s largest solar parks, Benban and Al Dhafrah Solar Parks, by using Earth observation data. Cloud microphysics were obtained from EUMETSAT, and aerosol data were obtained from the CAMS and assimilated with MODIS data for higher accuracy. The impact of both factors was analysed by computing their trends over the past 20 years. These climatological trends indicated the variations in the change in each of the factors and their resulting …

Predicting Cloud-To-Ground Lightning In The Western United States From The Large-Scale Environment Using Explainable Neural Networks, Dmitri A. Kalashnikov, Frances V. Davenport, Zachary M. Labe, Paul C. Loikith, John T. Abatzoglou, Deepti Singh

Geography Faculty Publications and Presentations

Lightning is a major source of wildfire ignition in the western United States (WUS). We build and train convolutional neural networks (CNNs) to predict the occurrence of cloud-to-ground (CG) lightning across the WUS during June-September from the spatial patterns of seven large-scale meteorological variables from reanalysis (1995-2022). Individually trained CNN models at each 1° × 1° grid cell ( = 285 CNNs) show high skill at predicting CG lightning days across the WUS (median AUC = 0.8) and perform best in parts of the interior Southwest where summertime CG lightning is most common. Further, interannual correlation between observed and predicted …

Lengthening Atlantic Hurricane Seasons With Earlier Storm Formation Dates Including Implications From 2020, Barry D. Keim, L. C. Hamilton, V. M. Brown, P. J. Klotzbach, A. B. Lewis, D. T. Thompson

School of Public Health Faculty Publications

This paper analyzes the formation dates of the nth storm in a sequence for all named North Atlantic tropical cyclones (TCs) and assesses whether the intraseasonal length of the Atlantic hurricane season has changed temporally. The record-breaking 2020 season, with 30 named storms, set records for the earliest third TC formation (Cristobal) and from the sixth TC (Fay) onward. Analysis of season length from 1851 to 2022 identifies only one statistically significant breakpoint detected in the early 1970s, roughly coinciding with the introduction of satellite observations. Since 1970, we also find a trend toward longer North Atlantic hurricane seasons. The …

Global Empirical Model Of Sporadic-E Occurrence Rates, Eli V. Parsch, Anthony L. Franz, Eugene V. Dao, Dong L. Wu, Nimalan Swarnalingam, Cornelius C. J. H. Salinas, Daniel J. Emmons

Faculty Publications

Intense ionization enhancements in the Earth’s ionosphere, known as sporadic-E (E_s), can degrade and severely disrupt the propagation of radio signals. Although many previous studies have analyzed the characteristics and morphologies of sporadic-E, few efforts have attempted to model global E_s occurrence rates (ORs) at high time resolutions. This study develops a global empirical model of blanketing sporadic-E occurrence rates using a Karhunen–Loéve Expansion (KLE) of a global OR climatology built with Global Navigation Satellite System radio occultation (GNSS-RO) and ionosonde observations. Using an fbE ≥ threshold of 3 MHz, the model outputs a blanketing sporadic-E …

Typology Of Atmospheric Conditions Leading To Dam Overtopping In The Eastern Us, Hodo I. Orok, Deanna Hence

I-GUIDE Forum

Statistical characterization of reanalysis datasets during over 300 hydrologic dam incidents between 2003 and 2022 will create a detailed typology of weather systems associated with dam overtopping in the eastern United States. Dam overtopping poses significant risks to infrastructure and public safety, necessitating a comprehensive understanding of the multi-scale atmospheric conditions that lead to such events. To better account for the natural flow of water to the affected dams, we will adopt a watershed-focused Principal Component Analysis (PCA) on regional atmospheric data collected from ERA5 alongside USGS streamflow and Stage IV precipitation observations to enhance understanding of high-risk weather conditions. …

Creating Sustainable School And Home Gardens: Using Weather Stations, Jake Sanders, Daniel Findlay, Kathy Cabe Trundle, Rita Hagevik, Kaitlin Campbell

All Current Publications

This fact sheet provides an overview of how weather stations work and the steps to set up your own weather station. To help monitor the water conditions, wind speeds, and temperatures that can impact your plants, we suggest adding a weather station to your garden area or greenhouse.

Climate Prediction Center Analogs As Extended Range Predictors For Severe Convective Storms, Sean Phipps

Honors Capstones

Increasing the predictability of severe convective storms (SCSs) over extended time ranges (i. e. >8 days) is of utmost importance to forecasters, as modern numerical weather prediction (NWP) models exhibit little skill at this lead time. Analogs have been used to predict temperature and rainfall anomalies at this time range for decades, though modern developments in analog forecasting uses techniques such as analog ensembles to increase the skill of analog models. This study employs a simple analog ensemble (AnEn) method using the Climate Prediction Center (CPC) 6-10 Day 500hPa analogs and uses the Storm Prediction Center (SPC)’s report database to …