π‘ New Paper!
β΅ Can sailboats improve estimates of the ocean COβ sink?
Citizen-science measurements help reveal a stronger Southern Ocean sink, but current sampling is still too sparse to fully constrain long-term trends.
The official account of the AI4PEX Project "Artificial Intelligence and Machine Learning for Enhanced Representation of Processes and Extremes in Earth System Models" (2024-2028).
This project receives funding from the European Union #HorizonEU Research and Innovation Programme. Any related posts reflect only the views of the project partners.
| Website | https://ai4pex.org |
π‘ New Paper!
β΅ Can sailboats improve estimates of the ocean COβ sink?
Citizen-science measurements help reveal a stronger Southern Ocean sink, but current sampling is still too sparse to fully constrain long-term trends.
π Next up in the #AI4PEX Science Talks!
π Hadi Shokati
AI for soil erosion, flood segmentation & rainfall erosivity forecasting
π§ RenΓ© Geist
SoftJAX & SoftTorch: differentiable programming for scientific ML
π Thursday, 25. June 2026 at 13:00 CEST
Join us for a deep dive into Earth observation, AI & scientific machine learning.
π Register now! https://survey.academiccloud.de/f/668874?lang=en
π₯ Looking back at the ELLIS Winter School 2026 in Athens!
A week full of AI, climate science, hands-on projects, inspiring discussions & new collaborations. ππ€
Watch our highlight video and hear from participants, instructors & organizers.
Special thanks to Olyvon for producing this amazing video and supporting the school.
π‘ New Paper!
π‘οΈ How much of recent summer warming is circulation-driven?
Our new study shows that atmospheric circulation trends explain up to 50% of Europeβs summer warming (1979β2023) β with strong but contrasting effects across the northern mid-latitudes.
Dynamics matter.
π‘ New Paper on global plant functional diversity ππΏ
Using remote sensing, biodiversity observations & trait databases, this study maps key plant traits worldwide at 1-km resolution β offering new insights into ecosystem functioning, biodiversity & resilience under environmental change. π°οΈπ±
π https://www.nature.com/articles/s41467-026-72111-6
#AI4PEX #Ecology #RemoteSensing #Biodiversity #EarthObservation
π AI4PEX 2nd General Assembly in Brest, France!
The week combines scientific exchange, collaboration & hands-on sessions on CNNs, AI agents, Generative approaches & Uncertainty Quantification.
A highlight: dedicated discussions for ECRs on careers, funding & supervision β followed by a beautiful coastal hike π
Thanks to for hosting us!
π‘ New Paper on physics-aware AI for #EarthObservation ππ€
By combining physical models with symbolic regression & sparse ML, this work moves toward more interpretable and trustworthy emulators for atmospheric radiative transfer.
πhttps://doi.org/10.1109/TGRS.2026.3676858
A step toward explainable AI in Earth system science π
π€ #EGU26 Spotlight
AI must go beyond prediction π
Gustau Camps-Valls on AI for climate resilience β from explainable AI to early warning systems & causal models.
π https://meetingorganizer.copernicus.org/EGU26/EGU26-22994.html
π€ #EGU26 Spotlight
Climate extremes donβt always happen alone π‘οΈ
Sonia Seneviratne on compound events β rising risks, near-permanent extremes, and limits to adaptation. How multiple climate extremes interact & amplify impacts.
π https://meetingorganizer.copernicus.org/EGU26/EGU26-14314.html
π€ #EGU26 Spotlight
How do soil moisture & temperature drive extremes? π
Feini Huang combines causal AI + ML to disentangle landβatmosphere feedbacks β and benchmark climate models.
π https://meetingorganizer.copernicus.org/EGU26/EGU26-12361.html