24–26 August 2026 · Bonn, Germany

Workshop on Machine Learning for Earth System Modelling

About the Workshop

We are pleased to announce the fourth Workshop on Machine Learning for Earth System Modelling, following a series of three successful workshops. The workshop brings together leading researchers working on large-scale machine learning approaches for weather and climate science. It will take place in Bonn, Germany, and follows the Hackathon on Machine Learning for the Earth System.

The workshop will take place on August 24 – 26, 2026 in the Universitätsclub Bonn, Germany.
Registration and abstract submission will open soon

The event brings together researchers from Earth system science, mathematics, and computational science to discuss recent advances in machine learning for weather and climate applications.
Topics include:

Timeline Workshop & Hackathon

Timeline, Important Dates & Abstract Submissions

  • Workshop Registration opens: tba

  • Workshop dates: 24–26 August 2026

  • Abstract submission opens: tba

  • Notification of accepted abstracts: 22 June 2026

Abstract submission

We invite you to submit your abstracts with relevance to the topics to be discussed in this year’s workshop.

Submissions will only be via CMT* platform (https://cmt3.research.microsoft.com/About)

Authors will need to create an account on the platform (if they do not already have one) at: https://cmt3.research.microsoft.com/docs/help/general/account-creation.html

Each abstract should be a maximum of 1 page.

Notification of accepted abstracts will be communicated on 30 Jun 2026.

MLESM Hackathon

The workshop follows the Hackathon on Machine Learning for the Earth System on 19-21 August 2026 in Bonn. Please find more information on how to apply here:

Workshop Registration

On-site participation will cost 260 €, including access to the venue, coffee breaks, lunches, and a conference dinner.

Up to 30 student seats are available at a reduced rate of 150 € (proof of student status required).

Online participation will cost 75 €.

Registration will open soon.

Important Information

Information about the workshop for all registered participants will be sent via mlesm-workshop@cesoc.net or mlesm-registrations@cesoc.net. Please make sure to mark them as safe, i.e., not spam/junk.No time to attend our MLESM event but interested anyway, stay tuned and subscribe at mlesm-workshop@listen.uni-bonn.de.

For questions please contact us via email:  mlesm-workshop@cesoc.net

Supported by

We gratefully acknowledge the support by CESOCECMWF, the TRA Modelling at the University of Bonn, the Forschungszentrum Jülich and the University of Cologne.

Acknowledgement: The Microsoft CMT service will be used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

Programme

(tba)

Alternative Layouts mit komprimiertern Tabs

24–26 August 2026 · Bonn, Germany

24–26 August 2026 · Bonn, Germany

Workshop on Machine Learning for Earth System Modelling

The fourth Workshop on Machine Learning for Earth System Modelling brings together leading researchers working on large-scale machine learning approaches for weather and climate science.

About the MLESM Workshop

We are pleased to announce the fourth Workshop on Machine Learning for Earth System Modelling, following a series of three successful workshops. The workshop will take place in Bonn, Germany, and follows the Hackathon on Machine Learning for the Earth System.

The workshop will take place on August 24 – 26, 2026 in the Universitätsclub Bonn, Germany.
Registration and abstract submission will open soon

The event brings together researchers from Earth system science, mathematics, and computational science to discuss recent advances in machine learning for weather and climate applications.
Topics include:

Workshop Registration

On-site participation will cost 260 €, including access to the venue, coffee breaks, lunches, and a conference dinner.

Up to 30 student seats are available at a reduced rate of 150 € (proof of student status required).

Online participation will cost 75 €.

Registration will open soon.

Timeline & Abstract Submissions

  • Workshop Registration opens: tba

  • Workshop dates: 24–26 August 2026

  • Abstract submission opens: tba

  • Notification of accepted abstracts: 22 June 2026

We invite you to submit your abstracts with relevance to the topics to be discussed in this year’s workshop.

Submissions will only be via CMT* platform (https://cmt3.research.microsoft.com/About)

Authors will need to create an account on the platform (if they do not already have one) at: https://cmt3.research.microsoft.com/docs/help/general/account-creation.html

Each abstract should be a maximum of 1 page.

Notification of accepted abstracts will be communicated on 22 Jun 2026.

Timeline Workshop & Hackathon

MLESM Hackathon

The workshop follows the Hackathon on Machine Learning for the Earth System on 19-21 August 2026 in Bonn. Please find more information on how to apply here:

Workshop Programme 24 – 26 Aug 2026

All times are in CEST (UTC+2)

For the abstracts, please click the respective title.

Monday 24 Aug:

08:30 – 09:00 Registration 

9:00-10:30 NWP

11:00 – 11:55 NWP + Evaluation poster session

  • Lightning talks (15 mins)
  • Poster viewing

11:55 – 12:30 Evaluation

12:30 – 13:30 Lunch Break

13:30 – 15:00 Earth system components

15:30 – 16:30 Earth system component posters

  • Lightning talks (20 mins)
  • Poster viewing

16:30 – 17:30: Evaluation + NWP

19:00 – : Workshop Dinner @ Tuscolo Münsterblick (Gerhard-von-Are-Straße 8, 53111 Bonn)

————————————

Tuesday 25 Aug:

9:00 – 10:30 Observations

11:00 – 12:00 Observation + Evaluation posters

  • Lightning talks (20 mins)
  • Poster viewing

12:00 – 12:30 Datasets

12:30 – 13:30 Lunch Break

13:30 – 15:00 Foundation Models and NWP

15:30 – 16:30 Evaluation + Climate Posters

  • Lightning talks (20 mins)
  • Poster viewing

16:30 – 17:30: NWP +  Observations

————————————

Wednesday 26 Aug:

9:00 – 10:30 Climate

11:00 – 12:00 Observation + Earth system components

12:00 – 12:15 Closing remarks

————————————-

Important Note: Long talk = 20 min , Regular talk = 10 min

List of Posters

Posters sessions:

S1: Monday 24 Aug. 11:00 – 11:55                                                   S2: Monday 24 Aug. 15:30 – 16:30

S3: Tuesday 25 Aug. 11:00 – 12:00                                                  S4: Tuesday 25 Aug. 15:30 – 16:30

Poster SessionPaper TitlePrimary Author
S1 Towards ECMWF’s data-driven flood forecasting systemMaria Luisa Taccari
S1Regional ensemble weather forecasting using a stretched-grid approach over Western EuropeSerban Vadineanu
S1Exploring Explainability for Graph-Based Weather Forecasting Models Using Layer-Wise Relevance PropagationJens Pruschke
S1Comparison of Distribution Calibration in Machine Learning and Numerical Weather Prediction ModelsKornelius Raeth
S1Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss FunctionLeo Separovic
S1Transformer-Based Short-term Precipitation Post-Processing: Leveraging Extensive Data and Short TrainingMinchan Jeong + Cho
S1Advancing Heatwave Prediction with the Aurora Foundation Model: Insights from India and BeyondSeshagirirao Kolusu
S2Improved Neural Network Modeling of Plasmasphere Using Arase and RBSP DataSadaf Shahsavani
S2Emulating Significant Wave Height Forecasts Using Deep LearningKatherine Haynes
S2Autoregressive denoising diffusion for predicting trajectories of floating objects in oceansChristian Donner
S2A machine learning approach to recover cloud microphysical process rates from ICON model simulations with the two-moment microphysics schemeMiriam Simm
S2Unlocking the Future of Dry Intrusion Outflows with Deep LearningOwain Harris
S2Sea-Ice Simulation and Ocean-Coupled Processes in a Deep Learning Earth-System ModelDale Durran
S2Towards high-resolution land surface temperature forecasting for early detection of extreme eventsMarieke Wesselkamp
S2Bias-Correcting Arctic ERA5 Surface Air Temperatures using Deep LearningSabine Scholle
S2Machine Learning-Based Reservoir Storage Forecasting for Optimal and Climate-Resilient Operation of Multi-reservoir systems in the Blue Nile River Basin.Selam Sahlu
S3On the verification of weather forecasts for extremes: a statistical reviewRomain Pic
S3Leveraging machine learning to advance the assimilation of new types of satellite observations to better constraint the land carbon cycle in the ECMWF Integrated Forecast System (IFS)Sebastien Garrigues
S3Leveraging NOAA’s Joint Effort for Data assimilation Integration (JEDI) to force FourCastNet with Tomorrow.io’s microwave sounder dataBrandon Taylor
S3Convolutional Neural Network for the Assimilation of Diurnal Satellite Retrievals of Sea Surface Temperature in Ocean Reanalysis and Forecast SystemsMatteo Broccoli
S3Are observations all you need?Peter Lean
S3Out-of-sample Heat Extremes in AuroraGeorge Jordan
S3On simulating the 2019 European summer heatwave event using data-driven weather modelsPrabhakar Namdev
S3Learning to Faithfully Compress Sentinel-2 Satellite Data using Vector-Quantized AutoencodersSebastian Hoffmann
S4HClimRep: A Foundation Model for Capturing the Atmosphere, Ocean, and Sea Ice InteractionsAnkit Patnala
S4Harnessing Machine Learning for Climate Modeling: Towards the Development of a DestinE Climate EmulatorFernando Iglesias-Suarez
S4A machine learning emulator for paleoclimate: Using neural network to generate precipitation climatology in Southwest AsiaTrang Nguyen
S4Uncertainty-aware Masked Autoencoders for predicting El Niño Southern Oscillation dynamicsJannik Thuemmel
S4Sensitivity of Deep learning El Nino Southern Oscillation forecasts to model trainingJinhao Wu
S4Hierarchical Graph Diffusion Networks for ERA5 Reconstruction and Long-Term Climate ForecastingNishant Kumar
S4Verification of AI models – Adaptation and extension of an operational verification framework as part of the RAINA projectBritta Seegebrecht

Questions?

📩 Contact us at: mlesm-workshop@cesoc.net

Accommodation

Bonn offers a variety of hotels at different price points. We recommend booking early, as hotels can fill up quickly. Suggestions:
🏨 Motel One Bonn
🏨 IntercityHotel Bonn
🏨 Hotel Kurfürstenhof

Important Information

Information about the workshop for all registered participants will be sent via mlesm-workshop@cesoc.net or mlesm-registrations@cesoc.net. Please make sure to mark them as safe, i.e., not spam/junk.No time to attend our MLESM event but interested anyway, stay tuned and subscribe at mlesm-workshop@listen.uni-bonn.de.

For questions please contact us via email:  mlesm-workshop@cesoc.net

MLESM Hackathon

The workshop follows the Hackathon on Machine Learning for the Earth System on 19-21 August 2026 in Bonn. Please find more information on how to apply here:

Supported by

We gratefully acknowledge the support by CESOCECMWF, the TRA Modelling at the University of Bonn, the Forschungszentrum Jülich and the University of Cologne.

Acknowledgement: The Microsoft CMT service will be used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.