Environmental Data Science (@EnvDataScience) header
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Environmental Data Science is an #OpenAccess @CambridgeUP journal dedicated to the use of data science & AI to enhance our understanding of the environment.

Cambridge, UK
Joined September 2020
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New article! Detecting structural transitions in climate-sensitive environmental signals using spectral entropy and Bayesian change-point inference 👉cup.org/4irhJxM ✍️Tomoo Noguchi #data #environmentalscience
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Recent article! Predicting stream water temperature: A data-driven approach highlighting the impact of riparian vegetation 👉cup.org/4yBniPX ✍️Simon Walther, Benoît Hohl, Pauline Lourenço, Hector Fabio Satizabal Mejia, Jean-François Rubin and Andres Perez-Uribe #data
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Recent article! Data-driven integration kernels for interpretable nonlocal operator learning 👉 cup.org/4yMDn5I ✍️Savannah L. Ferretti, Jerry Lin, Sara Shamekh, @janewbaldwin, Michael S. Pritchard and Tom Beucler #environmentalscience #data
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Explore Position Papers from Environmental Data Science. Free to read and share: bit.ly/4yndnh2 #OAWeek
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Explore special collections from Environmental Data Science. Free to read and share: bit.ly/4ympgUa #OAWeek
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Explore most cited articles from Environmental Data Science. Free to read and share: cup.org/47UTjYp #OAWeek
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Explore most read articles from Environmental Data Science. Free to read and share: cup.org/4yQ9CSl #OAWeek
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Meet the new Editor of Environmental Data Science in this interview with Dr. Qili Dai 👉 bit.ly/4jGYFO0 #environmental #environmentalscience #data
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Recently published! Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression 👉cup.org/4rKqF5m ✍️@sanjitdp, Margaret Johnson, Madeleine Pascolini-Campbell, Glynn Hulley and Mikael Kuusela #data #ECOSTRESS
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New article! Cross-domain offshore wind power forecasting: transfer learning through meteorological clusters 👉cup.org/4iZAhXH ✍️Dominic Weisser, Chloe Hashimoto-Cullen and @bguedj #enviromental #data #wind
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New article! CNN-based forecasting of early winter NAO using sea surface temperature 👉cup.org/4xP9z7W ✍️Elena Provenzano, Guillaume Gastineau, Carlos Mejia, Didier Swingedouw and Sylvie Thiria #CNN #NAO #ENSO
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New article! A machine learning approach to detecting environmental crimes in Brazil 👉cup.org/46MJJ9F By Matthew C. Ingram #machinelearning #Brazil #crime #environment
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New article! Human-centric skills are essential for the responsible and rigorous application of AI in ecology 👉cup.org/4h4fvng ✍️@jmkendallbar, Allison R. Payne, @mfczap, Nathan Fox, Jessica Leivesley, Michaela Alksne, @beverlyjfrench, @AliceMalivert et al #AI #ecology
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New article! Dissipating the correlation smokescreen: causal decomposition of the radiative effects of biomass burning aerosols over the South-East Atlantic 👉cup.org/4c0Oa3D ✍️Emilie Fons, Isabel Louise McCoy, Tom Beucler, David Neubauer & Ulrike Lohmann #smoke #BBAs
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New article! Super-resolving coarse-resolution weather forecasts with flow matching 👉cup.org/4zwkoxO ✍️Aymeric Delefosse, Anastase Charantonis and Dominique Béréziat Part of the Climate Informatics 2026 special issue @Inria #weather #forecasting #deeplearning
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New article! Future wildfire risk in Southern Europe under changing land use, population, and climate: a data-driven approach 👉cup.org/4g5tIj8 ✍️@meuriot_ophelie, Jorge Soto Martin, Francisco Camara Pereira and Martin Drews #climatechange #machinelearning #wildfire
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New article! Generative unsupervised downscaling of climate models via domain alignment: Application to wind fields 👉cup.org/4q0c7Oa ✍️Julie Keisler, Boutheina Oueslati, Anastase Charantonis, @YannigGoude & Claire Monteleoni #downscaling #flowmatching #generative
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Recently published! Joint bias correction and downscaling of subseasonal forecasts via diffusion models 👉cup.org/4yXJu8r ✍️Maria Pyrina, Adel Imamovic, Dominik Bueeler, Christoph Spirig and Daniela I.V. Domeisen #climate #subseasonalprediction
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Recently published! Interpretable machine learning for CMIP6 multi-model ensembles 👉cup.org/45FZTkm ✍️Siyi Wu and Steve M. Easterbrook Part of the Climate Informatics 2026 special issue #CMIP6 #machinelearning #clustering #ensembleweighting
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Recently published! A generative likelihood framework for high-resolution climate model evaluation 👉 cup.org/4fNN3Gw ✍️Lilli Johanna Freischem, Tim Reichelt, Ronald Clark, @PhilipStier and @hannahmchr #climate #climatemodel
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