π‘ New paper!
Find out how recent significant improvements of #ESMValTool allows a more effective evaluation of complex #ESMs and high-resolution models while needing less computational resources.
π Join the discussion: buff.ly/CyycyeP
@ai4pex.bsky.social
We are a consortium of 19 institutions from all over Europe involved in the Horizon Europe funded project: Artificial Intelligence and Machine Learning for Enhanced Representation of Processes and Extremes in Earth System Models. https://ai4pex.org
π‘ New paper!
Find out how recent significant improvements of #ESMValTool allows a more effective evaluation of complex #ESMs and high-resolution models while needing less computational resources.
π Join the discussion: buff.ly/CyycyeP
π First GA for #AI4PEX in Lund!
Last month partners from across Europe met to advance #EarthSystemModels with #AI, #ML & #EarthObservation - tackling β¨ Benchmarking π Syncing milestones π Boosting outreach π€ Hands-on collaboration.
Big thanks to Lund University for hosting!
π www.ai4pex.org
π Excited to share our teamβs contributions at the ESA Living Planet Symposium next week in Vienna! Catch us across multiple sessions on carbon fluxes, EO data consistency, AI for climate science & more.
#LPS25 ππ°οΈ #EarthObservation #EarthSystemModeling #CINEA
Fourth and last day of our #AI4PEX GA is again reserved for workshops. Moderated by Fangfei Lan from UNIL we spend the morning focusing on Neural Operator Learning. In the afternoon, we build our own hybrid model using the SINDBAD modeling framework, led by Nuno Carvalhais from MPG-BGC.
#CINEA
AI4PEX GA Day 3 we are mainly focusing on the technical and methodological aspects: How to improve our benchmarking? And what can explainable AI do to improve our parametrizations? Highlight was the keynote by Dave Lawrence from UCAR on how #ArtificialIntelligence is entering the #ESMs development.
04.06.2025 17:36 β π 2 π 0 π¬ 0 π 0#AI4PEX GA Day 2: starting with in-depth scientific talks and posters on our main achievements so far, before discussing in more detail next steps for the atmosphere, ocean and land teams.
In the evening we went to Kulturen Open Air Museum, immersing in the history of the region.
#CINEA #HorizonEU
Today, we started with a workshop on Doing Interdisciplinarity to set the stage for an effective communication across disciplinary boundaries, moderated by Catrin Finkenauer from @utrechtuniversity.bsky.social.
02.06.2025 21:21 β π 1 π 0 π¬ 0 π 0Today we're kicking off the 1st #AI4PEX General Assembly in Lund, Sweden, hosted by @lund-university.bsky.social. Within the next 4 days we will talk about achievements, discuss methods and plan research of next year, while getting closer, building trust and turning our team into a project family.
02.06.2025 21:21 β π 0 π 0 π¬ 1 π 0π‘ New Paper!
Clouds are crucial for climate modeling, affecting sunshine, heat, and rainfall. Traditional models use coarse grids, but new methods involve high-detail simulations and #MachineLearning to predict cloud cover and cloud content to improve #HybridModels.
π Learn more:
buff.ly/uIN1R3O
#AI4PEX & #EXPECT joining forces
Fantastic momentum at #EGU25! Teams from two #HorizonEU projects came together to explore synergies and plan future collaboration.
Next steps? We're aiming for a joint hackathon and an ECR meeting to build stronger connections.
#CINEA_EU #ESMs
AI4PEX @ #EGU: the past 2 days we heard a lot about Machine Learning applications and Climate Extremes by Ramon Fuentes Franco, Tom Beucler, Helena Reid, Svenja Seeber and Kai Cohrs.
01.05.2025 16:08 β π 2 π 0 π¬ 0 π 0AI4PEX @ #EGU25
We started the week in Vienna with talks on heatwaves, wildfires and extreme evaporation by Dominik Schumacher, Lars Nieradzki & Yannis Markonis. On Day 2 we dived deeper into ocean modeling with Hongmei Li and model evaluation using the ESMValTool by Valeriu Predoi.
#CINEA #ESM
π Climate science needs sharp tools.
Check out ESMValTool, MESMER, benchmark datasets & more at #EGU25.
Predoi, Bauer, & Cohrs presenting powerful open-source tools, statistical methods, and new frameworks that make climate science more reproducible, transparent, and effective.
#OpenScience
π± Whatβs up with carbon sinks, wildfires & ecosystem feedbacks in a changing climate?
Weβve got you at #EGU25. Models, remote sensing & field data combined.
Talks by Ilyina, Behncke, Nieradzik, Gomarasca & co. π
#CarbonScience #ClimateFeedbacks #EGU25
π₯ Heatwaves, flash floods & weird weather?
Weβre digging into climate extremes at #EGU25 and how these events link to climate change.
β‘οΈ Catch talks by Schumacher, Ivanov, Seeber, and more!
#ExtremeClimate #WeatherEvents #EGU25 #ClimateScience
π AI is transforming climate research!
Catch us at #EGU25 presenting cutting-edge work on applying #MachineLearning, hybrid models, and causal discovery in climate research.
β‘οΈ Donβt miss: Camps-Valls, Reid, Ouala, Beucler + more!
#AI4Climate #ML4Science #EGU25 #ClimateAI
π‘ New Preprint!
How to improve plant physiological processes in #ESM? Check out the enhanced capability of our HYBRID-JSBACH4 model using feed-forward neural networks (FNN) pre-trained on observations capturing variability in stomatal conductance while reducing transpiration bias
π buff.ly/XdEyHd2
π‘ New Paper!
#MachineLearning improves #EarthSystemModels, but explaining its added value is tough. Inspired by climate model hierarchies, we propose using Pareto-optimal models to distill ML's added value in representing cloud cover, radiative transfer and tropical precipitation.
π buff.ly/iirtWkk
What are the climate models we are working on? Land model number 4:
JSBACH4 is the land component of the ICON #ESM where we are focusing on phenology, stomatal conductance, and tree mortality.
π Learn more: buff.ly/xEiRG8c
π’The first 2 years of our project, we brought researchers & local decision-makers together in 2 World CafΓ© workshops to discuss climate science & policymaking. Now, weβre revisiting those conversations with a short summary β a chance to reflect on what was shared.
π£οΈ Read it here: bit.ly/ESM2025WCS
What are the climate models we are working on? Land model number 3:
ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems), the land surface model of the IPSL #EarthSystemModels, where our focus is especially on the hydrological processes.
π Learn more: buff.ly/83X23ho
#ClimateResearch
What are the climate models we are working on? Land model number 2:
JULES (Joint UK Land Environment Simulator): a community land surface model coupled to the Met Office Unified Model where we will build high-dimensional emulators to calibrate land surface behavior.
πLearn more: buff.ly/XkWSYOM
What are the climate models we are working on? Letβs start with the land models:
LPJ-GUESS from Lund University, is a process-based dynamic vegetation-terrestrial ecosystem model where we focus on forest dynamics.
π Learn more: buff.ly/kJQxy5H
#EarthSystemModels #ClimateResearch
ππͺοΈ How is climate change fueling extreme weather?
Our concept paper dives into Extreme Event Attribution (EEA) β the key to linking weather events to climate change. While new methods are making it easier to track the impact of climate change, important challenges still remain.
Paper linked π½
π‘ New Paper!
Have you ever wondered, in which ways #ArtificialIntelligence can help us to better predict and respond to #ExtremeEvents?
π Find out what #AI can already do, its challenges and opportunities:
www.nature.com/articles/s41...
π‘ New Paper!
Check out how to better represent the formation of thin low-level clouds in atmospheric models! Our #MachineLearning model enhances vertical detail in temperature and humidity profiles to improve cloud fraction.
π Learn more: https://buff.ly/3CMZoKu
π Registration Now Open for the @ELLISforEurope Summer School: AI for Earth & Climate Sciences! ππ€
Join us in Jena, Germany from September 1β5, 2025
π
Apply now through March 31. Notifications by April.
π www.ellis-jena.eu/summer-schoo... π―
@uni-jena.de, @MPI-BGC, @carlzeissstiftung.bsky.social
π‘ New Preprint!
What are the benefits of an online versus offline learning approach? Explore our application of online training approach to learning subgrid parameterisations of baroclinic ocean #eddies.
π Find out more: https://buff.ly/3WtdEPk
#ESMs
π‘ New Preprint!
Find out how recent significant improvements of ESMValTool allows a more effective evaluation of complex #ESMs and high-resolution models while needing less computational resources.
π Join the discussion: gmd.copernicus.org/preprints/gm...
@schlunma.bsky.social
π‘ New Paper!
How to improve #DeepLearning submodels for hybrid numerical modelling systems? Ouala et al. showcase an efficient and practical online learning approach using Euler Gradient Approximation for #HybridModels.
π Learn more: https://buff.ly/3C7uwUU