Recently published! Joint bias correction and downscaling of subseasonal forecasts via diffusion models 👉https://cup.org/4yXJu8r ✍️Maria Pyrina, Adel Imamovic, Dominik Bueeler, Christoph Spirig and Daniela I.V. Domeisen #climate #subseasonalprediction

Recently published! Interpretable machine learning for CMIP6 multi-model ensembles 👉https://cup.org/45FZTkm ✍️Siyi Wu and @steve.fediscience.org.ap.brid.gy  Part of the Climate Informatics 2026 special issue.  #CMIP6 #machinelearning #clustering #ensembleweighting #climate

Recently published! A generative likelihood framework for high-resolution climate model evaluation 👉 https://cup.org/4fNN3Gw ✍️Lilli Johanna Freischem, @treichelt.bsky.social, Ronald Clark, @philipstier.bsky.social and @hannah325.bsky.social #climate #climatemodel

New article! SYNOPTICBENCH: evaluating vision-language models on generating weather forecast discussions of the future 👉https://cup.org/4x01Dkh ✍️Timothy Higgins, Antonios Mamalakis and Chirag Agarwal #visionlanguagemodel #multimodality #weatherforecasting

Recently published! Emulating non-differentiable metrics via knowledge-guided learning: Introducing the Minkowski image loss 👉 https://cup.org/3TppDyy ✍️Filippo Quarenghi, Ryan Cotsakis and Tom Beucler #differentiability #machinelearning #radarprecipitation

New article! One stone three birds: Three-dimensional implicit neural network for compression and continuous representation of multi-altitude climate data 👉https://cup.org/4wbBDm3 ✍️Alif Bin Abdul Qayyum, Xihaier Luo, Nathan M. Urban, Xiaoning Qian & Byung-Jun Yoon #climate

Recent article! Explainable machine learning highlights the role of diffuse radiation in ecosystem carbon uptake of boreal forest 👉https://cup.org/4wIPNLh ✍️Topi Markus Laanti, Aino Aarne, Maxime Durand et al.  #machinelearning #borrealforest

New article! Calibrated conformal prediction intervals for microphysical process rates 👉https://cup.org/4w0sooz ✍️Miriam Simm, Corinna Hoose and Tom Beucler #cloud #microphysics #conformalprediction #machinelearning

New article! Precipitation nowcasting of satellite data using physically aligned neural networks 👉https://cup.org/4wfMkDp ✍️Antônio Catão, Leonardo Voltarelli, Melvin Poveda and Paulo Orenstein #precipitation #data #satellitedata #neuralnetworks #nowcasting

New article! Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks 👉 https://cup.org/4ugXdUr ✍️Shivam Singh, Simon Michael Papalexiou, Hebatallah M. Abdelmoaty, @tomhartvigsen.bsky.social & Antonios Mamalakis #data #generativemodels #precipitation

New article! Assessing the risk of future Dunkelflaute events for Germany using generative deep learning 👉https://cup.org/4nEHj4c ✍️ Felix Strnad, @schmidtjonathan.bsky.social, Fabian Mockert, @philipphennig.bsky.social & @nnludwig.bsky.social #CMIP6 #renewableenergy #generativeAI #climate

Recently published! Data-driven discovery of meteotsunami patterns from sparse observations 👉 https://cup.org/4wcgN6l ✍️Ardiansyah Fauzi, Emiliano Renzi, Frederic Dias, Daniel Santiago Pelaez-Zapata & Tatjana Kokina  #data #meteotsunami #coastalhazard @ucddublin.bsky.social

Recent article! Detecting unique wind field features in hurricane Sandy from topological data maps 👉 https://cup.org/3OEfL25 ✍️Justin Hoffmeier (@FLPolyU) Part of the Connecting Data-Driven and Physical Approaches special issue #weather #cyclones #hurricane #wind #dataanalysis

New article! Combined effects of site and model parameterization for soil respiration components in a Canadian wildfire chronosequence 👉https://cup.org/3NxKQEc ✍️John Zobitz,  Xuan Zhou, Heidi Aaltonen, Egle Köster, Frank Berninger , Jukka Pumpanen & Kajar Köster #carbon #microbes #modelling #soil

New article! Which meteorological parameters influence extreme wind speed in a wind farm? A heterogeneous Granger causality approach 👉https://bit.ly/405R00I  ✍️Kateřina Hlaváčková-Schindler, Rainer Wöss, Irene Schicker & Claudia Plant @univie.ac.at @aswogeosphere.bsky.social #windspeed #windenergy

New article! Actively inferring methane sources with drones 👉 https://bit.ly/4tAYwyr ✍️Alouette van Hove, Kristoffer Aalstad & Norbert Pirk (@uio.no) Part of the Connecting Data-Driven and Physical Approaches special issue. #Bayesian #drones #methane

New article! A machine learning approach using autoencoders to perform quality control on meteorological data 👉https://bit.ly/4qJuQNG ✍️Teresa Kristine Spohn, Eoin Walsh, Kevin Horan (@maynoothuniversity.ie), John O’Donoghue (@unioflimerick.bsky.social), Tim Charnecki, Merlin Haslam, Sarah Gallagher

New article! Uncertainty quantification for deep learning 👉 https://bit.ly/49MlJpa ✍️ Peter Jan van Leeuwen, Jui-Yuan Christine Chiu & Chen-Kuang Kevin Yang (@csuatmossci.bsky.social) Proposes a framework to improve consistency for #uncertaintyquantification in #deeplearning #machinelearning

New article! Language models for the analysis of and interaction with climate change documents 👉 https://bit.ly/48RjC1W ✍️ Elena Volkanovska (@tuda.bsky.social) Part of the Tackling Climate Change with Machine Learning special issue #climatechange #MachineLearning

Calling all @britishecologicalsociety.org #BES2025 attendees! Visit @universitypress.cambridge.org at booth L15 in the Lennox Suite, floor -2, to find out more about Environmental Data Science journal & how to publish your research #openaccess! Have a great conference! #ecology #environment #data

New article! Using Gaussian processes for spatial prediction of PM2.5 concentration based on calibrated data from distributed low-cost sensor networks 👉 https://bit.ly/496Ty42 ✍️Lillian Muyama, Richard Sserunjogi, Deo Okure & Engineer Bainomugisha ( @airqo.bsky.social) #airquality #airpollution

New article! Prediction and uncertainty quantification of drought in North Benin 👉https://bit.ly/3Xhrrsc Part of the Tackling #ClimateChange with #MachineLearning special issue. Study underscoreing the importance of uncertainty quantification in #drought #forecasting.

📢 CALL FOR PAPERS! Solution-Based #DataScience for #Environmental #Biology Challenges A special collection with @cu-esiil.bsky.social  to advance data-intensive approaches to better understand today's environmental challenges  🗓️1 March-31 May 2026 ℹ️https://bit.ly/4q0b68m #TippingPoints

New article! From winter storm thermodynamics to wind gust extremes: discovering interpretable equations from data 👉 https://bit.ly/4oPzZSN ✍️ Frederick Iat-Hin Tam, Fabien Augsburger, Tom Beucler (@fgse-unil.bsky.social, @unil.bsky.social ) @climformatics.bsky.social #CI2025 #thermodynamics #wind

📢 CALL FOR PAPERS: FINAL DAY TO SUBMIT! Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation A special collection building upon a workshop at #EGU25. ⏰ 31 October 2025 ℹ️ https://bit.ly/4k09cBu #climate #AI #forecasting

New article! Graph neural networks for hourly precipitation projections at the convection permitting scale with a novel hybrid imperfect framework 👉https://bit.ly/46RPjIF ✍️Valentina Blasone, @erikacoppola.bsky.social, Guido Sanguinetti, Viplove Arora, Serafina Di Gioia & Luca Bortolussi

📢 Solution-Based #DataScience for #Environmental #Biology Challenges Announcing a new Call for Papers with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges: ℹ️https://bit.ly/4q0b68m 📅 31 May 2026 #TippingPoints #Resilience #Adaptation

Recently published! Precipitation prediction over the upper Indus Basin from large-scale circulation patterns using Gaussian processes 👉 https://bit.ly/4nojwoo ✍️ @kenzatazi.bsky.social , Andrew Orr, @scotthosking.bsky.social  & Richard E. Turner @theturing.bsky.social @bas.ac.uk   #precipitation

New article! Toward accurate forecasting of renewable energy: Building datasets and benchmarking machine learning models for solar and wind power in France 👉 https://bit.ly/4mCtrWj ✍️ Eloi Lindas, Yannig Goude & Philippe Ciais (@lsce-ipsl.bsky.social) #climate #MachineLearning #forecasting

New article! Air quality prediction from images in Indonesia: enhancing model explainability through visual explanation with AQI-net and grad-CAM 👉 https://bit.ly/4g434qD ✍️ Muhammad Labib Alauddin, Novanto Yudistira & Muhammad Arif Rahman @climformatics.bsky.social‬ #CI2025 #airquality