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

‪ 🌳 Do you want to contribute to research on how humans perceive forests? Take this quick, anonymous 10-min survey 🌲 👉 www.biodiful.org#/forest This will help us explore how people experience forest biodiversity! Please share on 🦋 & tag @biodiful.bsky.social to reach more participants 🙏💚 🌐🌍🦤🦑🪴🍁🧪

Recent article! Skillful subseasonal Indian Ocean marine heatwave forecasts using a neural network 👉 https://bit.ly/40c6P6k ✍️Lucas Howard, Aneesh C. Subramanian, Jithendra Raju Nadimpalli, Donata Giglio & Ibrahim Hoteit Part of Connecting Data-Driven and Physical Approaches Issue #machinelearning

New article! Utilization of artificial intelligence and thermal cameras in material analysis for hot-summer Mediterranean climates 👉 https://bit.ly/4u1iBxQ  ✍️ Ahmet Benliay &  Türkan Azeri Combining #AI & #thermal #imaging may be beneficial for #ecological and sustainable architectural design

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

Exploring the Impact of 2025 @climformatics.bsky.social in the Global South - by @rblourenco.bsky.social #CI2025 #ClimateInformatics #DataScience www.cambridge.org/core/blog/20...

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

We are Climate.us, a nonprofit successor to Climate(.)gov. Our goal is to build an enduring, independent, and scientifically rigorous platform that the world can rely on for climate communication, education, and engagement. Stay up to date: Climate.us/#updates#updates

📢 CALL FOR PAPERS: Closing soon! 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

We have exciting news! #CI2026 will be hosted by the École Polytechnique Fédérale de Lausanne (EPFL), in the period of April 27-30, 2026. More information in Tom Beucler's post: www.linkedin.com/posts/tom-be...

📢 CALL FOR PAPERS: Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation   Only 1 month left to submit to this special collection building upon a workshop at #EGU25. ℹ️ https://bit.ly/4k09cBu #climate #AI #forecasting

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

Recently published! 🌍 Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations 👉 https://bit.ly/4oVbLre ✍️James Rudd-Jones, Fiona Thendean & María Pérez-Ortiz (@ucl.ac.uk‬) #ClimateChange #ClimatePolicy

New article! 🌍🛰️ Discrete variational autoencoders for synthetic nighttime visible satellite imagery 👉 https://bit.ly/4oVjTb5 ✍️ Mickell D. Als, David Tomarov & @steve.fediscience.org.ap.brid.gy  (@uoftcompsci.bsky.social‬) Part of the @climformatics.bsky.social  #CI2025 collection #DeepLearning

New article!🌍💨💡 Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6 👉 doi.org/10.1017/eds.... ✍️ Nina Effenberger & @nnludwig.bsky.social This uses a global #climate model and shows #wind as a reliable #energy source with turbine location essential for projections.

Recent article! 🌳🌍 Tree semantic segmentation from aerial image time series 👉 doi.org/10.1017/eds.... ✍️ Venkatesh Ramesh @arthurouaknine.bsky.social & @drolnick.bsky.social Research that advances #forest monitoring using #deeplearning on aerial imagery time series.

📢 CALL FOR PAPERS REMINDER! Connecting #Data-Driven and Physical Approaches: Application to #Climate #Modeling and #Earth System Observation Submit your work to this special collection in EDS (‪@universitypress.cambridge.org) 🗓️ 31st Oct 2025 ℹ️ bit.ly/4k09cBu @brajard.bsky.social #AI #ML #Weather

Article! MoTiF: a self-supervised model for multi-source #forecasting with application to #tropical #cyclones 🌀🌍 ✍️Clément Dauvilliers & Claire Monteleoni (INRIA & colorado.edu‬) �� https://doi.org/10.1017/eds.2025.1000014 Presents #deeplearninga#AIng #AI method for foreca#extremeweathereather.

Recent article! Uncertainty bounds for long-term causal effects of perturbations in spatiotemporal systems 👉 https://bit.ly/3Idjb8x By Kevin Debeire, Andreas Gerhardus, Renée Bichler, @jakobrunge.bsky.social‬ and Veronika Eyring #spatiotemporalmodels #uncertaintyestimations

Recently published! Development of a comprehensive bilateral trade-flow dataset of the environmental pressures of global food production 👉 https://bit.ly/3TPYC4q By authors from @nceas-ucsb.bsky.social  #climatechange #agriculture #food  ‪@jagephart.bsky.social‬

Recently published position paper by ‪@mierksch.bsky.social‬ et al.! Opportunities and challenges of quantum computing for climate modeling 👉 https://bit.ly/4591Cyb   #climatemoedling #quantumcomputing

📢 CALL FOR PAPERS: Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation This special collection will build upon a workshop at #EGU25.  🗓️31st Oct 2025 ℹ️https://bit.ly/4k09cBu @brajard.bsky.social  #climate #AI #forecasting

Discover Environmental Data Science, an #OpenAccess journal focused on #data-driven methods for studying #environmental processes like #climatechange & supporting sustainable decision-making. Check out our 2024 metrics and learn more at: https://bit.ly/47aNIht #datascience

Environmental Data Science is excited to partner with AI for Good Fragile Earth workshop at the #KDD2025 conference with a special collection of papers on AI for Climate Risk Mitigation. View our collection of papers from previous worskhops here: https://bit.ly/4lUKSBM #AI #Climate

Position paper published! Opportunities and challenges of quantum computing for climate modeling 👉 bit.ly/4591Cyb ‪By @mierksch.bsky.social‬, @pierregentine.bsky.socia and colleagues #climate #climatemodeling #qunatumcomputing

🚀 Launching a refreshed EDS book online resource and notebooks powered by the fresh beta release of Jupyter Book 2.0 (JB2) 🚀 👉 Check it out here: www.edsbook.org 📬 Stay tuned for further community-led notebooks ideas to be published this year!

Primeira vez que o Climate Informatics será sediado em um país do Sul Global. Uma oportunidade única para que está na interface da Ciência de Dados e Clima. Ainda há tempo para se inscrever! emap.fgv.br/noticias/cli...

We are happy to partner with @fgvoficial.bsky.social and #IBMResearch for #CI2025 It's only 3 days for the conference, but there's still time to register for online participation. We hope to see you there 😉 portal.fgv.br/noticias/eve...

The complete program of #CI2025 is now online! Please check it at: 2025.climateinformatics.com.br

This is the weather forecasting for #riodejaneiro in the forthcoming days. It seems that we will have #CI2025 with beautiful, warm, sunny days (temps are in Celsius)☀️🏖️ Have you registered already? #6days

Have you already registered?

🚨🚨🚨 We have included some instructions on registration after participant feedback. Please e-mail us at [email protected] , if you need any assistance on this 💪

🌎 Registrations open for Climate Informatics 2025 ( #CI2025 ), April 28–30, 2025, at @fgvoficial.bsky.social, in Rio,Brazil. Join us (hybrid) for #oceanography, #hydrology, #remotesensing, #climate & #socialimpacts sessions! 🔗 2025.climateinformatics.com.br #ClimateScience #DataScience

📢 New CFP: Special Collection in EDS! Calling for work exploring the convergence between #data-driven methodologies (#AI, #machinelearning) and physical modeling for Earth system science, building upon an upcoming workshop #EGU25 (@egu.eu). ℹ️ How to submit: bit.ly/3Eq4WLV 📅 Deadline: 31 Oct 2025

Prezados colegas, É com grande satisfação que anunciamos a abertura das inscrições para a 14ª Conferência Internacional sobre Climate Informatics (CI2025), que ocorrerá de 28 a 30 de abril de 2025 no Centro Cultural FGV - Fundação Getulio Vargas, no Rio de Janeiro

New article! Space-scale exploration of the poor reliability of deep learning models: the case of the remote sensing of rooftop photovoltaic systems 👉 bit.ly/43Jmc9f