Oceanography and Atmospheric Sciences and Meteorology Commons^™

Hurricane Impacts Compounded By Sea Level Rise: An Illustrative Case Study Of Economic Impacts And Workforce Resilience Analysis, Juita-Elena Yusuf, Yin-Hsuen Chen, Robert M. Mcnab, George M. Mcleod

School of Public Service Faculty Publications

Expected sea level rise will increase the probability of extreme flooding events, such as those associated with hurricane surge and/or heavy rainfall. Projecting the economic impacts of a significant hurricane is necessary for weighing the costs and benefits of potential mitigation actions. Accounting for the compounding effects of sea level rise is critical, given the challenges elevated sea levels pose to coastal communities in the U.S. and worldwide. This chapter asks: How can we comprehensively estimate the economic impacts of a hurricane event that is compounded by sea level rise? To address this, we offer a methodology for conducting an …

Enhancing Shipboard Safety Management Under The Ism Code: An Innovative Risk Assessment Framework With A Stern Tube Case Study, Pi-Yen Lin

Journal of Marine Science and Technology–Taiwan

The shipboard safety management system (SMS) is designed to enhance safe operations, risk management, and emergency response to improve overall ship safety and efficiency. This paper demonstrates the use of an engine room simulator (ERS) for collecting failure modes and applies it to a comprehensive failure analysis of the stern tube lubricating oil system. A new risk closeness coefficient method was developed, integrating expert background knowledge and weighted risk assessments. The analysis, based on multiple expert evaluations, covered five subsystems, eight main components, 23 failure modes, and 112 failure causes. This study presents 26 recommendations for maritime practitioners and onboard …

Port And Vessel Communication Traffic Intrusion Detection: A Variational Autoencoder‑Enhanced Multilayer Perceptron Approach, Chien-Lin Chiang, Hsien-Cheng Chou, Ming-Yuan Peng, Yi-Yuan Chiang, Yu-Shun Liu

Journal of Marine Science and Technology–Taiwan

Port and vessel networks increasingly operate on IP/Ethernet backbones with high‑noise, high‑dimensional traffic. We present a lightweight hybrid intrusion‑detection model that couples a variational autoencoder (VAE) with a multilayer perceptron (MLP) and augments training with a boundary‑oriented latent‑space mixup strategy. The VAE models the distribution of normal traffic and identifies anomalies through reconstruction errors. Subsequently, it generates robust latent vectors, enabling the MLP to perform highly accurate supervised classification. On the UNSW‑NB15 dataset, the proposed pipeline attains ≥97% accuracy and an outstanding recall of 99.56% in binary intrusion detection, and visualization of the latent space (PCA) together with reconstruction‑error analyses …

Sar Ship Detection Based On Shallow Feature Guidance, Chenxu Xia, Peng Chen, Ya Zhang, Ying Li

Journal of Marine Science and Technology–Taiwan

Maritime ship detection is of great significance for both military security and civilian applications. Synthetic Aperture Radar (SAR), with its all-weather and all-day imaging capability, plays a vital role in maritime surveillance. Nevertheless, SAR ship targets typically appear small in scale, embedded in complex backgrounds, blurred at boundaries, and easily confused with near-shore features, which pose substantial challenges for accurate detection. To address these issues, we propose a SAR ship detection network that integrates dual enhancements of small-object representation and edge information. The network introduces two key components: the Small Target Refine Pyramid (STRP) to strengthen shallow feature representation for …

The Hidden Heatwave: Thermal Hazards In The New York City Subway System, Abdou Rachid Bah, Maimuna Muntaha, Lenny L. Metlitsky, Cesar Pascal Vasquez, Tyler Ayala, Isaac Morel Lopez, Shaquan A. Larose, Kingston Ditsch, Kip Nielsen, Shaunak Sharma, Reginald U. Avila-Ortega Blake, Hamidreza I. Norouzi

Publications and Research

Underground transit systems (Subway) are susceptible to frequent heat waves, which pose serious health and safety risks to commuters and transit workers. Yet, the patterns and extent of temperature changes within the subway system remain insufficiently understood. To address this gap, we conducted a study of thermal variability across 112 subway stations in New York City. Temperature and relative humidity were measured at both platform and street levels. Results show that during the summer, 70% of subway stations had platform heat index higher than street level heat index. We also developed a machine learning forecasting model to predict platform-level temperatures. …

Predictive Tropical Cyclogenesis Using Deep Learning: A Novel Approach To Early Warning Systems, Nikolay Todorov

Computational and Data Sciences (PhD) Dissertations

Tropical cyclogenesis (TCG) is among the least predictable stages of the tropical cyclone life cycle, yet the timing and location of genesis are exactly what early warning systems (EWS) depend on. We present a spatio-temporal deep learning framework that forecasts genesis as a normalized probability field and delivers that skill through a real-time warning pipeline. The model couples a two-layer ConvLSTM encoder with learned temporal-attention pooling over nine 6-hourly steps (0–48 h lead) and a convolutional refinement head that outputs per-cell genesis probability. It is trained on 1980–2025 ERA5 fields and Emanuel potential intensity at 0.25° and evaluated by leave-one-year-out …

Resolving Satellite And In Situ Mismatches In Net Primary Production Using High-Frequency In Situ Bio-Optical Observations In The Subpolar Northwest Atlantic, Kitty Warsi Kam, Emmanuel Devred, Stephanie Alam Clay, Mohammad M. Amirian, Andrew J. Irwin, Dariia Atamanchuk, Uwe Send, Douglas W. R. Wallace

Publications and Research

Net primary productivity (NPP) plays a central role in biological carbon pump (BCP) and global carbon cycling, but NPP estimates in high-latitude regions remain highly uncertain despite their disproportional contribution to the global carbon sink. Previous studies identified discrepancies among satellite- and in situ-derived NPP estimates, but the drivers of disagreement remain poorly resolved due to limited high-frequency observations. Here, we present continuous depth-resolved estimates of in situ NPP from the Central Labrador Sea (56°N) in the subpolar Northwest Atlantic, reconstructed from daily bio-optical profiles collected between May and November 2016, and a 40-year dataset of photosynthesis parameters derived from …

Progress, Challenges, And Policy Recommendations For China’S Climate Investment And Financing Pilot Zones In Context Of Carbon Neutrality, Xianchun Tan, Zhaoyang Deng, Chenxu Wang, Zhe Peng

Bulletin of Chinese Academy of Sciences (Chinese Version)

To implement the decisions and arrangements of the Central Committee of the Communist Party of China and the State Council on addressing climate change and to channel more capital toward climate action, China launched its first batch of 23 climate investment and finance pilot areas in 2022. Through the end of 2025, this study tracks and assesses of pilot development, synthesizes innovative models, identifies major challenges, and proposes policy recommendations. The results show that the pilot areas have made solid progress, with more than 260 supporting policy documents issued and over 6 300 projects, representing total planned investment exceeding RMB …

Comparing Knowledge-Driven And Data-Driven Machine Learning Frameworks For Coastal Vulnerability Assessment On The Egyptian North Coast, Ali Elgendy, Hesham Morgan, Hesham El-Askary, László Mucsi

Mathematics, Physics, and Computer Science Faculty Articles and Research

Coastal erosion worsened by climate change and human activities is a major threat to global shorelines. As sea levels rise and storms intensify, this rapid shoreline retreat endangers critical infrastructure and the economic security of coastal populations worldwide. However, traditional knowledge-driven frameworks for assessing these threats often rely on subjective, static rules that fail to capture complex, non-linear environmental interactions. To address this critical gap and demonstrate the value of advanced methods, this study compared the traditional Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model against machine learning algorithms, highlighting the potential for more accurate coastal erosion risk assessment. …

Hidden Thermal Signatures Reveal The Microclimatic Influence Of Scheduled Cave Tourism, Matt Rowberry, John Gunn, Andrew Smith

International Journal of Speleology

Tourist activity is widely recognised as a source of cave microclimate disturbance, yet visitor-induced variability is difficult to distinguish from natural environmental fluctuations. The coronavirus pandemic created a natural experiment at Poole’s Cavern, United Kingdom, in which periods of complete closure could be compared with contrasting visitor access regimes. Two years of high resolution temperature records from six monitoring points were analysed. Harmonic regression and a state space model removed deterministic diurnal cycles and lower frequency temperature variability. The remaining residual variability differed systematically among visitor access regimes and between daytime and nighttime conditions. Spectral analysis of the residuals identified …

Carbamate Toxicosis In Carnaby’S Cockatoos (Zanda Latirostris) In A Drying Climate, A Le Souef, Z M. Kissane, David Forshaw, K J. Riley, K Payne, T Hawkins, J Coggins, J M. Shephard, R Vaughn-Higgins, K S. Warren

Climate Science Research Articles

Pesticide exposure poses a growing threat to the health of wild avian populations worldwide. This report documents the first detections of agricultural chemicals in the tissues of wild Carnaby’s cockatoos (Zanda latirostris) in Western Australia. The events, characterised by morbidity and mortality, occurred in a national park near Perth, following periods of elevated summer temperatures over two seasons. Toxicological analysis of liver and digestive tract contents identified multiple pesticides and an herbicide, including methomyl, a highly toxic carbamate insecticide. Hot weather conditions preceding the events potentially increased the cockatoos’ use of alternative water sources for drinking, such as those in …

Wrf Cold-Pool Sensitivities Relevant To Winter Ozone Modelling In The Uinta Basin, John Lawson, Michael J. Davies, Loknath Dhar, Seth N. Lyman

Bingham Research Center

Cold-pool structure controls the confinement of wintertime ozone and its precursors in Utah’s Uinta Basin. Previous studies have documented difficulty capturing stable cold pools in meteorological models, complicating air quality simulations when pollutants disperse too readily. Herein, we evaluate the meteorology behind one such high-ozone event on 2 February 2013 with Weather Research and Forecasting (WRF) simulations; the chemistry is not simulated. We test the sensitivity to Global Forecast System (GFS) or North American Mesoscale (NAM) forcing, domain feedback, boundary-layer and surface-layer schemes, slope-aware radiation, and terrain datasets (fine versus coarse). Across five hourly samples, GFS-driven runs were warmer at …

2026 October 8 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

2026 October 1 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

A Node-Adaptive Meta Graph Learning Framework For Smart Energy Systems-Digitalizing Wildfire Risk Assessment In Renewable-Integrated Grids, Junde Chen, Wenzhao Li, Rejoice Thomas, Polukh Polukhov, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Wildfires pose escalating threats to the resilience of modern power delivery networks, which are increasingly evolving into complex Cyber-Physical Systems (CPS). In these systems, localized infrastructure damage can precipitate catastrophic large-scale outages and cascading failures. Conventional wildfire risk indices, developed for ecological and community safety, fail to account for the geospatial dependencies and operational context relevant to electricity infrastructure. To bridge this gap, we establish a risk assessment framework that converts meteorological variables into a grid-centric Fire Danger Weather Index (FDWI) and propose the Node-Adaptive Meta Graph Convolutional Recurrent Network (NM-GCRN), a highly efficient AI/ML architecture designed to generate fine-grained, …

Age Differences In Perceived Individual And Community Recovery After Tornadoes: Implications For Community-Centered Recovery Policy In An Aging Society, Sizhuo Chen, Zhen Cong

Health Sciences and Kinesiology Faculty Articles

"This study examines perceived individual recovery and perceived community recovery among tornado survivors across three waves spanning four years. Using three-wave longitudinal survey data from survivors in Dallas, Texas; Nashville, Tennessee; and Birmingham, Alabama collected in 2021, 2022, and 2025, we estimate recovery trajectories using linear mixed-effects growth models. We link respondents to tract-level SVI 2020 component measures to examine whether tract-level social vulnerability contextualizes age differences in recovery perceptions. We ask: (1) How do perceived individual recovery and perceived community recovery change over time? (2) Do these trajectories differ by age group? (3) Do community social vulnerability measures contextualize …

Oco-3 Meets Ecostress: Insights Into Ecosystem Diurnal Water-Use Efficiency From Co-Located Solar-Induced Fluorescence And Thermal Observations, Zoe Amie Pierrat, Thomas P. Kurosu, Abhishek Chatterjee, Joshua B. Fisher, Maggie Johnson, Le Kuai, Kanishka Mallick, Nicholas Parazoo, Benjamin Wiebe, Kerry Cawse-Nicholson

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Terrestrial ecosystem regulation of carbon and water fluxes is critical for constraining climate–biosphere feedbacks but remains poorly quantified across space and time. Here, we evaluate whether co-located observations from NASA's Orbiting Carbon Observatory-3 (OCO-3) and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) can reproduce ecosystem water use efficiency (WUE) dynamics observed at FLUXNET sites across temporal scales, vegetation types, climates, and drought conditions. We created the ECOCO3 data set, which harmonizes OCO-3 and ECOSTRESS observations in space and time. ECOCO3 captures broad seasonal and diurnal carbon and water flux patterns including midday drought responses. Sampling sensitivity analysis …

Evaluating Atmospheric Nox In The Marine Boundary Layer Near Tampa Bay, Ben Lloyd '25, Anson Kirsch, Samuel Irvine, Yasin Elshorbany, James Ivey

Student Research

Nitrogen oxides (NOX), including nitric oxide (NO) and nitrogen dioxide (NO₂), are atmospheric constituents that can contribute to nitrate deposition in seawater. Since nitrate availability can influence marine ecosystems, understanding atmospheric nitrogen inputs is important for characterizing nitrogen cycling in coastal environments. This dataset contains atmospheric NO and NO₂ measurements collected from July 5–6, 2023, in the marine boundary layer near Tampa Bay, Florida, at the University of South Florida St. Petersburg campus using a Teledyne T200UP Analyzer.

The dataset provides observations of atmospheric nitrogen oxide concentrations that can be compared with measurements of nitrate in rainwater and seawater to …

2026 - Tennessee Summer Climate Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Seasonal and Annual Climate Summaries

No abstract provided.

Next-Day Pm10 Prediction Maps For South Korea Using Machine Learning With Meteorological And Transboundary Air Quality Data, Yemin Jeong, Jaejin Kim, Jinsoo Kim, Menas Kafatos, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

PM10 poses significant risks to public health, and reliable short-term prediction is essential for air quality management. In this study, we developed an observation-driven framework for generating nationwide next-day (D + 1) PM10 prediction maps over South Korea using machine learning. The framework integrates ground-based PM10 observations from the AirKorea monitoring network, meteorological variables derived from the Local Data Assimilation and Prediction System (LDAPS), and a regional transport proxy based on PM10 observations from upwind locations in China. Station-based predictors were converted into spatially continuous grids using kriging and subsequently used as inputs for two tree-based ensemble models: Random Forest …