The study evaluates how feature engineering (FE) affects machine learning models for ocean colour data, proposing a seven‑step optimisation framework that includes band selection, scaling, normalisation, index extraction, PCA, and feature scaling. Applied to Sentinel‑3 OLCI observations, the framework improves model accuracy for estimating Chlorophyll‑a and Secchi disk depth, achieving higher R values and lower mean absolute errors compared to standard algorithms. However, the optimal FE varies across targets and models, indicating that FE optimisation must be tailored to each application.
arXiv:2607. 15775v1 Announce Type: cross Abstract: Access to potable water is crucial for health, economic development, and sustainability.
By Muntasir Tabasum, Al Zadid Sultan Bin Habib, Tanpia Tasnim, Md. Ekramul Islam, Md Younus Ahamed, Md Asif Bin Syed
arXiv:2609.13206v1 Announce Type: cross
Abstract: Marine ecosystems are increasingly impacted by climate change, necessitating tools to identify and predict spatial habitat information. To build such...
By Makayla McDevitt, Maike Sonnewald, Stephanie Dutkiewicz
arXiv:2608. 14935v1 Announce Type: cross Abstract: Turbulent fluxes between the surface and the atmosphere are typically parameterized using empirically fit relationships.
By Susan Dettling, Sue Ellen Haupt, Thomas Brummet, Patrick Hawbecker, Branko Kosovi\'c, David John Gagne
arXiv:2609.12744v1 Announce Type: new
Abstract: Timely monitoring of coastal water quality is critical for environmental protection, yet conventional satellite workflows rely on downlink and ground p...
By Pietro Di Stasio, Francesca Razzano, Elisa Liparulo, Gabriele Meoni, Nicolas Long\'ep\'e, Deodato Tapete, Paolo Gamba, Gilda Schirinzi, Silvia Liberata Ullo
arXiv:2605. 24003v2 Announce Type: replace-cross Abstract: Remote sensing techniques have been increasingly utilised in aquatic applications in recent years.
By Shuang Liu, Fiona Johnson, Rohitash Chandra
arXiv:2606. 02886v1 Announce Type: cross Abstract: Deep learning weather models now match numerical weather prediction accuracy while running orders of magnitude faster, but produce deterministic forecasts without uncertainty estimates, a critical gap for high-stakes decisions during extreme weather events.
By Jose Marie Antonio Mi\~noza, Rex Gregor Laylo, Sebastian C. Iba\~nez
arXiv:2608.24594v1 Announce Type: new
Abstract: Submerged kelp forests are vital coastal ecosystems that support marine biodiversity and ecosystem dynamics, yet accurate underwater kelp segmentation...
By Sundarabalan Balasubramanian, C\'esar Borja, Ana C. Murillo, Lexi N. Wilkes, Meredith L. McPherson, Kira A. Krumhansl, Jennifer A. Dijkstra, Jarrett E. K. Byrnes
MorphoGP is a nonparametric Gaussian process framework designed to predict equilibrium beach profiles under tidal influence. It first classifies beach morphologies using a ContourCluster model based on contrastive learning, then trains a specialized Gaussian process expert for each category to learn relationships between environmental descriptors (waves, tides, sediments) and beach shape. A Gating Net probabilistically combines the experts’ outputs, achieving a 59.3% reduction in test RMSE compared to the best baseline, with a final RMSE of 0.297 m on over 180 Chinese coast beach profiles.
By Xi Wu, Yanqing Wei, Hang Yin, Pengze Li, Hongshuai Qi, Xi Chen
arXiv:2609.25505v1 Announce Type: cross
Abstract: Rapid intensification (RI) remains one of the most consequential and difficult aspects of tropical cyclone (TC) forecasting. Although full-physics nu...
By Shijie Xiao, Jonathan Lin, Thomas Ehrmann, Ali Sarhadi
arXiv:2608. 10022v1 Announce Type: cross Abstract: The large-scale oceanic and atmospheric forecasts provided by global climate models typically lack sufficient resolution to accurately capture the response of the coastal ocean to atmospheric forcing and coastal circulation that drive fine-scale SST variability.
By Onkar Jadhav, Tim French, Ivica Janekovic, Nicole L. Jones, Matthew Rayson
arXiv:2606. 23766v1 Announce Type: cross Abstract: The detection and atmospheric characterization of exoplanets have entered a new data-intensive era driven by the James Webb Space Telescope and the upcoming Ariel mission.
By Muallim Yakubu, Vwavware Oruaode Jude