Meteorology Commons^™

Development And Evaluation Of An Mpas-Based Urban Modeling System For The New York City Region, Marco S. Yu, Kristian Rice

Publications and Research

Complex geometry and varying land cover make urban environments difficult to simulate accurately. This research presents a performance evaluation of the newly developed urban modeling system in the Model for Prediction Across Scales (MPAS). Weather over the New York metropolitan area during June 2018 was simulated using supercomputing resources and the new urban modeling system. Modeled 2-m air temperature was compared with historical hourly observations from five NYC Mesonet stations, one located in each of the five boroughs. Comparison showed that the model follows the timing of warming and cooling well, but overestimates the magnitude of temperature swings at peaks …

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 …

2025-2026 - Tennessee Winter Climate Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Seasonal and Annual Climate Summaries

No abstract provided.

2026 April 23 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

2026 March - Tennessee Climate Snapshot, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

2026 March - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

It was a very warm and dry March across Tennessee, with temperatures 10°F+ above average for most parts of the state through the 1st, 2nd, and 4th weeks of March. Based on monthly mean temperatures, it was a top-5 warmest month on record for Memphis, Nashville, Oak Ridge, Knoxville, Chattanooga, and the Tri-Cities, and a top-5 driest month for Nashville. A strong cold front March 16-17 produced the first tornadoes of the year, in Middle Tennessee.   With warm and dry conditions, we've also seen areas classified by the US Drought Monitor as Abnormally Dry (D0) to Extreme Drought …

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 …

2026 February - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All

February 2026 began with a volatile combination of a mid-level low from the Central U.S. and a powerful system moving up the East Coast, trapping Tennessee in a deep freeze. This convergence brought heavy snowfall to East Tennessee while much of the rest of the state was still recovering from a major winter storm just a week prior. On the morning of February 2, record-breaking temperatures hit 15-20°F below normal across the state. In particular, the Bristol/Tri-Cities airport recorded a low of -7°F, breaking its daily record by seven degrees and marking its first sub-zero temperature since 2015. …

2026 February - Tennessee Climate Snapshot, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

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 …

A High-Resolution Daily Precipitation Fusion Framework Integrating Radar, Satellite, And Nwp Data Using Machine Learning Over South Korea, Hyoju Park, Hiroyuki Miyazaki, Menas Kafatos, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Accurate precipitation mapping is essential for effective disaster management; however, individual radar, satellite, and numerical weather prediction products often struggle in the topographically complex terrain of South Korea. This study proposes a high-resolution (~500 m) daily precipitation fusion framework that integrates Korea Meteorological Administration (KMA) radar, Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), and Local Data Assimilation and Prediction System (LDAPS) data. The framework employs a Random Forest model augmented with a monthly Empirical Cumulative Distribution Function (ECDF) correction. Auxiliary predictors are incorporated to enhance physical interpretability and stability, including terrain attributes to represent orographic effects, land-cover …

2026 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

The main weather and climate story of January 2026 was the major winter storm that impacted the state from Saturday, January 24 through Monday, January 26 with rain, freezing rain, sleet, and snow, followed by extremely cold conditions. Winter storm warnings and winter weather advisories were in place across the state on Friday, January 23, as snow and sleet spread into Tennessee from the west in the overnight hours of Friday into Saturday. Most areas of the state saw an initial round of snow and sleet, before a layer of warm air aloft caused most locations to see …

2026 January - Tennessee Climate Snapshot, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Linking Boundary Type, Storm Mode, And Tornado Intensity In Illinois, Jakob Barton

A with Honors Projects

A large dataset of tornadoes across Illinois from 2007-2024 were analyzed for different characteristics of thunderstorms and tornadoes, these characteristics were then compared with each other to find correlation and trends.

Identification And Characterization Of Tornado Seismic Signals In The Central U.S., Seth Thompson

Theses and Dissertations--Earth and Environmental Sciences

Tornadoes cause extensive property damage and endanger lives. While Doppler radar can indicate the potential for tornado development, it cannot confirm that a tornado is in contact with the ground unless a debris signature is present. While on the ground, a significant amount of a tornado’s energy may be transferred into the earth as seismic vibrations. Thus, seismometers have the potential to detect on-the-ground tornadoes. Since 1960, only five papers have published seismic recordings from tornadoes. These studies have mostly reported on seismic waves generated by tornadoes at a relatively large range, from 0.01-2.5 Hz, representing uncertainty in the dominant …

Liutex - A Fluid Vortex, Oscar Alvarez

Mathematics Dissertations

Fluid vortices are found everywhere in our universe. A vortex can take the form of almost anything - from the classical spiral vortex to chaotic plumes. Defining a vortex physically and mathematically is absolutely necessary if we desire to study vortices and their interactions with each other as well as our physical world. Fluid vortices are incredibly important in the study of turbulent flows. From determining wear, optimizing design for better flow, efficiency, etc., to even predicting the weather on Earth or other planets, having the ability to measure vortices in fluid flow is invaluable. In this study, I investigate …

Forecasting Precipitation In Cuba Using Graph Based Deep Learning, Taufiqul Islam

Earth & Environmental Sciences Theses

Daily precipitation forecasting remained a challenging problem in regions characterized by strong spatial heterogeneity, nonlinear atmospheric dynamics, and intermittent rainfall behavior. Cuba represented a particularly complex case due to the combined influence of tropical cyclones, easterly waves, mesoscale convective systems, and orographic effects, which produced highly variable rainfall patterns in both space and time. Conventional statistical and machine-learning models typically treated stations independently and therefore overlooked spatial dependencies that strongly influenced rainfall variability across the island.

This study developed a spatiotemporal deep-learning framework for daily precipitation forecasting across 40 spatial nodes in Cuba using data from 1979 to 2023. The …

Challenges And Best Practices For The Development Of Coastal Hazard Decision Support Tools, Noah Hallisey

Open Access Dissertations

There is growing interest in developing Decision Support Tools (DSTs) supporting emergency managers and other decision-makers during coastal storm events. Yet many tools fail to inform decision-making due to challenges associated with their development and transition into operational tools for real-time decision-making. This dissertation investigates these challenges and offers best practices for their development and implementation for real-world decision-making through a literature review, interviews with subject matter experts in the United States, and a real-world case study.

Manuscript 1 reviews existing published literature to understand whether and how tool developers are incorporating emergency managers in the development of DSTs and …

A Composite Narxnn Approach To Photovoltaic Power Forecasting With Integrated Weather Inputs And Uncertainty Quantification, Denisse Urenda Castañeda, Sharmin Abdullah, Jackson Morgan, Honglun Xu, Michael Pokojovy, Tzu-Liang Tseng

Mathematics & Statistics Faculty Publications

Solar photovoltaics (PV) are a major source of sustainable energy. Yet, their power output is highly sensitive to environmental variability, particularly solar irradiance, cloud cover, wind, and temperature. Accurate forecasting of PV power is essential for efficient grid integration and energy planning, especially in applications requiring reliable longer-term forecasting rather than one-step-ahead predictions. This study presents a PV power forecasting approach using Nonlinear Autoregressive models with Exogenous Inputs (NARX), integrating large-scale numerical weather historical data as exogenous variables. Although NARX models effectively capture temporal dependencies, they can become overly dependent on historical power values, reducing responsiveness to real-time weather changes. …

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 …