The ML4LM webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. See the 2026 schedule below; the 2025 schedule with links to presentations and recordings is available here.
Recordings for previous webinars are available here or linked to below. Find links to individual presentations below.
Register for March’s presentation at https://gmu.zoom.us/webinar/register/WN_U4Rb2S6AQEierrAieBEQRQ! Prof. Sungmin O (Kangwon National University, Korea) will present “Machine Learning for Land Modeling: Lessons from Hydrologic Benchmarking”.
2026 ML4LM Webinar Series Schedule
| Date and Time (UTC) | Title | Presenter | Recording and Presentation |
|---|---|---|---|
| 13 January 2026, 15:30 UTC | EarthMind S2S: A Coupled Ocean-Atmosphere-Land Global AI Model for Subseasonal to Seasonal Forecasts | Prof. Manmeet Singh, Western Kentucky University | Presentation Recording Slides |
| 12 February 2026, 15:30 UTC | Putting land variables into the AIFS and an introduction to Direct Observation Prediction | Dr. Ewan Pinnington, ECMWF | Presentation Recording Slides |
| 17 March 2026, 11:00 UTC | Machine Learning for Land Modeling: Lessons from Hydrologic Benchmarking | Prof. Sungmin O, Kangwon National University | Register! |
| 15 April 2026, 15:30 UTC | Accelerating Land-Surface Modelling with Emulators: STEMMUS-SCOPE, Drought Detection, and SoilWat/ISMC Updates | Prof. Yijian Zeng, University of Twente | |
| 14 May 2026, 15:30 UTC | Clustering heterogeneity: The opportunities it enables for land surface models | Prof. Nate Chaney, Duke University | |
| 17 June 2026, 15:30 UTC | Enhanced land surface data exploitation using machine learning in weather prediction systems | Dr. Patricia de Rosnay, ECMWF | |
| 15 July 2026, 14:30 UTC | Using ML to identify conditions of underperformance in LSMs under the PLUMBER2 framework | Dr. Jon Cranko Page, University of Oulu | |
| 15 September 2026, 15:30 UTC | Sparky – A Hybrid Fire Model for LSMs | Dr. Joe McNorton, ECMWF | |
| 15 October 2026, 15:30 UTC | Leveraging in situ and remote sensing observations to support ML modeling of land surface processes | Prof. Marouane Temimi, Stevens Institute of Technology | |
| 12 November 2026, 14:00 UTC | Physics-informed Machine Learning for Land Data Assimilation | Prof. Xin Li, Chinese Academy of Science, ITPCAS | |
| 10 December 2026, 15:30 UTC | Key challenges and new scientific studies for improving our understanding of the L-A system | Prof. Volker Wulfmeyer, University of Hohenheim | |
