Environmental Data Science

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

[Environmental Data Science @EnvDataScience]

Explore most cited articles from Environmental Data Science.

Free to read and share: https://t.co/U4knUyJSMW

#OAWeek

[Environmental Data Science @EnvDataScience]

Explore most read articles from Environmental Data Science.

Free to read and share: https://t.co/pDIXhACD2S

#OAWeek

[Environmental Data Science @EnvDataScience]

Meet the new Editor of Environmental Data Science in this interview with Dr. Qili Dai

👉 https://t.co/qCqTom0nri

#environmental #environmentalscience #data

[Environmental Data Science @EnvDataScience]

Recently published!

Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression

👉https://t.co/r6CHmV9DPM
✍️@sanjitdp, Margaret Johnson, Madeleine Pascolini-Campbell, Glynn Hulley and Mikael Kuusela

#data #ECOSTRESS

[Environmental Data Science @EnvDataScience]

New article!

Cross-domain offshore wind power forecasting: transfer learning through meteorological clusters

👉https://t.co/hjeasZmtxO
✍️Dominic Weisser, Chloe Hashimoto-Cullen and @bguedj

#enviromental #data #wind

[Environmental Data Science @EnvDataScience]

New article!

CNN-based forecasting of early winter NAO using sea surface temperature

👉https://t.co/te0bxEb6q2
✍️Elena Provenzano, Guillaume Gastineau, Carlos Mejia, Didier Swingedouw and Sylvie Thiria

#CNN #NAO #ENSO

[Environmental Data Science @EnvDataScience]

New article!

A machine learning approach to detecting environmental crimes in Brazil

👉https://t.co/EvltO8xNSB

By Matthew C. Ingram

#machinelearning #Brazil #crime #environment

[Environmental Data Science @EnvDataScience]

New article!

Human-centric skills are essential for the responsible and rigorous application of AI in ecology
👉https://t.co/8cn6Df6yTt
✍️@jmkendallbar, Allison R. Payne, @mfczap, Nathan Fox, Jessica Leivesley, Michaela Alksne, @beverlyjfrench, @AliceMalivert et al

#AI #ecology

[Environmental Data Science @EnvDataScience]

New article!

Dissipating the correlation smokescreen: causal decomposition of the radiative effects of biomass burning aerosols over the South-East Atlantic

👉https://t.co/3SquLmeBfS
✍️Emilie Fons, Isabel Louise McCoy, Tom Beucler, David Neubauer & Ulrike Lohmann

#smoke #BBAs

[Environmental Data Science @EnvDataScience]

New article!

Super-resolving coarse-resolution weather forecasts with flow matching

👉https://t.co/yv2rVG22s6
✍️Aymeric Delefosse, Anastase Charantonis and
Dominique Béréziat

Part of the Climate Informatics 2026 special issue

@Inria #weather #forecasting #deeplearning

[Environmental Data Science @EnvDataScience]

New article!

Future wildfire risk in Southern Europe under changing land use, population, and climate: a data-driven approach

👉https://t.co/duAYIzGnAI
✍️@meuriot_ophelie, Jorge Soto Martin, Francisco Camara Pereira and Martin Drews

#climatechange #machinelearning #wildfire

[Environmental Data Science @EnvDataScience]

New article!

Generative unsupervised downscaling of climate models via domain alignment: Application to wind fields

👉https://t.co/kAscwYp5vl
✍️Julie Keisler, Boutheina Oueslati, Anastase Charantonis, @YannigGoude & Claire Monteleoni

#downscaling #flowmatching #generative

[Environmental Data Science @EnvDataScience]

Recently published!

Joint bias correction and downscaling of subseasonal forecasts via diffusion models

👉https://t.co/JX05gGq9b7
✍️Maria Pyrina, Adel Imamovic, Dominik Bueeler, Christoph Spirig and Daniela I.V. Domeisen

#climate #subseasonalprediction

[Environmental Data Science @EnvDataScience]

Recently published!

Interpretable machine learning for CMIP6 multi-model ensembles

👉https://t.co/EDbonyiLBi
✍️Siyi Wu and Steve M. Easterbrook

Part of the Climate Informatics 2026 special issue

#CMIP6 #machinelearning #clustering #ensembleweighting

[Environmental Data Science @EnvDataScience]

Recently published!

A generative likelihood framework for high-resolution climate model evaluation

👉 https://t.co/pHDtQzgnbA
✍️Lilli Johanna Freischem, Tim Reichelt, Ronald Clark,
@PhilipStier and @hannahmchr

#climate #climatemodel

[Environmental Data Science @EnvDataScience]

New article!

SYNOPTICBENCH: evaluating vision-language models on generating weather forecast discussions of the future

👉https://t.co/0ueUgpe4qI
✍️Timothy Higgins, @AntoniosMamala2 and @_cagarwal

#visionlanguagemodel #multimodality #weatherforecasting

[Environmental Data Science @EnvDataScience]

Recently published!

Emulating non-differentiable metrics via knowledge-guided learning: Introducing the Minkowski image loss

👉 https://t.co/7I5UP8WpUM
✍️Filippo Quarenghi, Ryan Cotsakis and Tom Beucler

#differentiability #machinelearning #radarprecipitation

[Environmental Data Science @EnvDataScience]

New article!

One stone three birds: Three-dimensional implicit neural network for compression and continuous representation of multi-altitude climate data

👉https://t.co/hxWt2WCMzs
✍️Alif Bin Abdul Qayyum, Xihaier Luo, Nathan M. Urban, Xiaoning Qian & Byung-Jun Yoon

#climate

[Environmental Data Science @EnvDataScience]

Recent article!

Explainable machine learning highlights the role of diffuse radiation in ecosystem carbon uptake of boreal forest

👉https://t.co/IggzUPORAl
✍️Topi Markus Laanti, Aino Aarne, Maxime Durand et al.

@MarkkuKulmala1 @lintunen_anna 

#machinelearning #borrealforest

[Environmental Data Science @EnvDataScience]

New article!

Calibrated conformal prediction intervals for microphysical process rates

👉https://t.co/yU81GV2Z9r
✍️Miriam Simm, Corinna Hoose and Tom Beucler

#cloud #microphysics #conformalprediction #machinelearning