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'Data' plays a central role in data-driven methods, but is not often the subject of focus in investigations of machine learning algorithms as applied to Earth System Modeling related problems. Here we consider the case of eddy-mean…

Atmospheric and Oceanic Physics · Physics 2023-07-04 F. E. Yan , J. Mak , Y. Wang

The availability of reliable, high-resolution climate and weather data is important to inform long-term decisions on climate adaptation and mitigation and to guide rapid responses to extreme events. Forecasting models are limited by…

Sea Surface Temperature (SST) is crucial for understanding upper-ocean thermal dynamics and ocean-atmosphere interactions, which have profound economic and social impacts. While data-driven models show promise in SST prediction, their…

Machine Learning · Computer Science 2025-11-11 Zheng Jiang , Wei Wang , Gaowei Zhang , Yi Wang

Complex ocean systems such as the Antarctic Circumpolar Current play key roles in the climate, and current models predict shifts in their strength and area under climate change. However, the physical processes underlying these changes are…

Atmospheric and Oceanic Physics · Physics 2023-12-19 William Yik , Maike Sonnewald , Mariana C. A. Clare , Redouane Lguensat

Mesoscale eddies remain poorly represented in most climate models, motivating the use of parameterizations to account for their dynamical effects on the coupled system. In this study, we implement a data-driven eddy parameterization based…

Atmospheric and Oceanic Physics · Physics 2026-03-30 Jia-Rui Shi , Pavel Perezhogin , Laure Zanna , Alistair Adcroft

Sea surface temperature (SST) is an essential climate variable that can be measured via ground truth, remote sensing, or hybrid model methodologies. Here, we celebrate SST surveillance progress via the application of a few relevant…

Atmospheric and Oceanic Physics · Physics 2023-06-19 Albert Larson , Ali Shafqat Akanda

Oysters are a vital keystone species in coastal ecosystems, providing significant economic, environmental, and cultural benefits. As the importance of oysters grows, so does the relevance of autonomous systems for their detection and…

Measurement noise is an integral part while collecting data of a physical process. Thus, noise removal is necessary to draw conclusions from these data, and it often becomes essential to construct dynamical models using these data. We…

Machine Learning · Computer Science 2022-05-20 Pawan Goyal , Peter Benner

Underwater surveys provide long-term data for informing management strategies, monitoring coral reef health, and estimating blue carbon stocks. Advances in broad-scale survey methods, such as robotic underwater vehicles, have increased the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Scarlett Raine , Frederic Maire , Niko Suenderhauf , Tobias Fischer

Accurate ocean forecasting systems are vital for understanding marine dynamics, which play a crucial role in environmental management and climate adaptation strategies. Traditional numerical solvers, while effective, are computationally…

Atmospheric and Oceanic Physics · Physics 2024-11-21 Daniel Holmberg , Emanuela Clementi , Teemu Roos

Tracking fish movements and sizes of fish is crucial to understanding their ecology and behaviour. Knowing where fish migrate, how they interact with their environment, and how their size affects their behaviour can help ecologists develop…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Alzayat Saleh , Marcus Sheaves , Dean Jerry , Mostafa Rahimi Azghadi

A common task in Earth Sciences is to infer climate information at local and regional scales from global climate models. Dynamical downscaling requires running expensive numerical models at high resolution which can be prohibitive due to…

Machine Learning · Computer Science 2022-05-19 Carlos Alberto Gomez Gonzalez

Microclimate models are essential for linking climate to ecological processes, yet most physically based frameworks estimate temperature independently for each spatial unit and rely on simplified representations of lateral heat exchange. As…

Machine Learning · Computer Science 2026-03-17 Idan Sulami , Alon Itzkovitch , Michael R. Kearney , Moni Shahar , Ofir Levy

Sea surface temperature (SST) forecasts help with managing the marine ecosystem and the aquaculture impacted by anthropogenic climate change. Numerical dynamical models are resource intensive for SST forecasts; machine learning (ML) models…

Atmospheric and Oceanic Physics · Physics 2023-05-17 Ding Ning , Varvara Vetrova , Karin R. Bryan

Sea ice at the North Pole is vital to global climate dynamics. However, accurately forecasting sea ice poses a significant challenge due to the intricate interaction among multiple variables. Leveraging the capability to integrate multiple…

Artificial Intelligence · Computer Science 2025-10-21 Jaesung Park , Sungchul Hong , Yoonseo Cho , Jong-June Jeon

Edge computing enables data processing closer to the source, significantly reducing latency, an essential requirement for real-time vision-based analytics such as object detection in surveillance and smart city environments. However, these…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-04 Daghash K. Alqahtani , Maria A. Rodriguez , Muhammad Aamir Cheema , Hamid Rezatofighi , Adel N. Toosi

The reduced sensitivity of mean Southern Ocean zonal transport with respect to surface wind stress magnitude changes, known as eddy saturation, is studied in an idealised analytical model. The model is based on the assumption of a balance…

Atmospheric and Oceanic Physics · Physics 2026-02-09 J. R. Maddison , D. P. Marshall , J. Mak , K. Maurer-Song

Long-term monitoring and exploration of extreme environments, such as underwater storage facilities, is costly, labor-intensive, and hazardous. Automating this process with low-cost, collaborative robots can greatly improve efficiency.…

Robotics · Computer Science 2025-03-05 Shuang Chen , Yifeng He , Barry Lennox , Farshad Arvin , Amir Atapour-Abarghouei

El Ni\~no-Southern Oscillation global (ENSO) imprint on sea surface temperature comes in many guises. To identify its tropical fingerprints and impacts on the rest of the climate system, we propose a global approach based on archetypal…

An estimate of the net direction of climate interactions in different geographical regions is made by constructing a directed climate network from a regular latitude-longitude grid of nodes, using a directionality index (DI) based on…

Chaotic Dynamics · Physics 2015-06-23 J. Ignacio Deza , Cristina Masoller , Marcelo Barreiro