The crossroads of observations and modelling motivate the theme of the Gordon Research Seminar (GRS) this year: advancing physical understanding of radiation and climate through observations, models, and other methodologies at the nexus of these approaches.
The Radiation and Climate GRS provides a unique forum for young doctoral and post-doctoral researchers to present their work, discuss new methods, cutting edge ideas, and pre-published data, as well as to build collaborative relationships with their peers. Experienced mentors and trainee moderators will facilitate active participation in scientific discussion to allow all attendees to be engaged participants rather than spectators.
This GRC will be held in conjunction with the “Radiation and Climate” Gordon Research Conference (GRC).
For additional information, visit https://www.grc.org/radiation-and-climate-grs-conference/2025/
Students will be introduced into fundamental processes of the atmosphere, ocean, sea-ice and land surface with relevance for the climate system. The course will deal with coupled atmosphere-ocean climate models, climate change, the greenhouse gas effect and other drivers of regional climate, dynamical downscaling, and the variability of circulation and regional climate. In additon, the possible impact of climate change on the marine ecosystem including biogeochemical cycles will also be studied.
With the help of teachers from several disciplines, a holistic Earth System approach will be presented although the main focus of the course is on the physical aspects of changing climate. In addition to lectures, tutorials, exercises and literature studies the course will give the students the opportunity to discuss the learned topics further during group exercises.
For details and to register, please visit https://www.io-warnemuende.de/bess-2025.html
Join us for the final webinar in the series:
General Discussion and Future Plans
All are Welcome to Join!
10 December 2025 | 15:30 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
See the website for the registration link! Links are added a few weeks before the webinar occurs. After you register, the link for the webinar will be emailed to you.
Join us for the tenth webinar in the series:
ML for Benchmarking Land Surface Models
Prof. Gab Abramowitz, UNSW
18 November 2025 | 10:00 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
See the website for the registration link! Links are added a few weeks before the webinar occurs. After you register, the link for the webinar will be emailed to you.
Join us for the ninth webinar in the series:
Machine Learning for Land Data Assimilation in Global NWP and Reanalysis Systems
Prof. Patricia de Rosnay, ECMWF
15 October 2025 | 14:30 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
See the website for the registration link! Links are added a few weeks before the webinar occurs. After you register, the link for the webinar will be emailed to you.
Join us for the eighth webinar in the series:
On the Use of ML for Modeling Land Surface Dynamics
Prof. Nuno Carvalhais, Max Plank Institute
9 September 2025 | 13:30 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
See the website for the registration link! Links are added a few weeks before the webinar occurs. After you register, the link for the webinar will be emailed to you.
Join us for the seventh webinar in the series on
Bridging Physics and Data: Parameter Estimation and Emulation of Land Surface Models with Machine Learning
Dr. Nina Raoult, ECMWF
9 July 2025 | 15:30 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
Register at https://gmu.zoom.us/webinar/register/WN_uweh-ZftQ7iwGwkvo-K_xQ! After you register, the link for the webinar will be emailed to you.
Join us for the sixth webinar in the series on
Exploring the Land-Atmosphere Coupled System with ML
Prof. Pierre Gentine, LEAP-STC, U. Columbia
9 June 2025 | 14:30 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
The registration link for June’s webinar is live! Register at https://gmu.zoom.us/webinar/register/WN_6-q29mmcT0OWKMscq-6iRQ and a link to participate will be emailed to you.
Join us for the fifth webinar in the ML4LM webinar series on
Physically-Based Land Modeling & ML—What Are the Complementarities?
Prof. Christoph Rüdiger, ECMWF
14 May 2025 | 13:30 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
See the website for the registration link! Links are added a few weeks before the webinar occurs. After you register, the link for the webinar will be emailed to you.
Join us for the fourth webinar in the ML4LM webinar series on
Advancing Predictive Understanding of Hydrological Systems through Trustworthy AI
Dr. Dan Lu, ORNL
3 April 2015 | 14:30 UTC
The Machine Learning for Land Surface Models (ML4LM) webinar series gathers eminent scientists to share their experience in the combined fields of machine learning and land modeling. ML4LM aims at exploring the extent and the role that machine learning could play for better land surface studies, especially identifying the main areas where it could be applied and providing tools and data to the land surface modeling community. It is a project of the GLASS Panel, which coordinates the evaluation and intercomparison of the latest generation of land models and their applications to scientific queries of broad interest.
See the website for the registration link! Links are added a few weeks before the webinar occurs. After you register, the link for the webinar will be emailed to you.
