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SUMMARY:Panel: Towards Coupled AI Climate Models
DTSTART:20261127T140000Z
DTEND:20261127T150000Z
DTSTAMP:20261009T001100Z
UID:indico-event-587@events.ecmwf.int
CONTACT:destine-ml-training@ecmwf.int
DESCRIPTION:\nOutline\n\nECMWF will host a live panel on 27 November 2026\
 , under the Destination Earth (#DestinE) initiative of DG-CNECT at the Eur
 opean Commission. The session will explore the opportunities and challenge
 s of developing coupled AI models for climate and Earth system modelling\,
  as part of the online training course Machine Learning for Earth System 
 Modelling: Applications and Future Directions. \n\n\nThis third and last 
 course in ECMWF’s three-course ML learning pathway focuses on the techni
 cal foundations of machine learning for weather prediction. It explores ho
 w advanced AI-based methods are applied\, evaluated and extended across re
 al-world Earth system applications and emerging modelling approaches. \n\
 n\nThe panel will explore current developments and future directions in co
 upled AI climate modelling\, bringing together different perspectives on t
 he opportunities and challenges of extending AI-based modelling across the
  Earth system. \n\n\nThe discussion will consider the current state of th
 e field\, progress towards representing interactions between different Ear
 th system components\, and the scientific and technical challenges involve
 d in developing more integrated AI-based modelling approaches. \n\n\nThe 
 experts will reflect on where the field stands today\, which capabilities 
 are beginning to emerge\, where important limitations remain\, and what di
 rections may shape the next generation of coupled AI models for weather an
 d climate research. \n\n\nThe panel will be recorded and made available a
 s part of Module 12 of the online training course. \n\nSpeakers\n\n\n\nCl
 aire Monteleoni\, INRIA \n\n\n\n\n\n\nNiklas Boers\, Potsdam Institute fo
 r Climate Impact Research (PIL) and Technical University of Munich (TUM) 
 \n\n\n\n\n\n\nNina Raoult\, ECMWF \n\n\n\n\n\n\nWilliam Gregory\, Univers
 ity College London (UCL) \n\n\n\nWho should attend?\n\nThis event is aime
 d at researchers\, practitioners\, technical specialists\, operational for
 ecasters\, climate and weather service professionals\, and industry expert
 s interested in coupled AI climate models and the future of AI-based Earth
  system modelling. \n\n\nThe event is open to the public and to learners 
 of the course Machine Learning for Earth Systems Modelling: Applications a
 nd Future Directions. If you are following the course\, you will still nee
 d to register here to attend the live panel. \n\nRegistration\nParticipat
 ion is free of charge. To register for the event\, click the "Registration
 " link on the left side of this page.\nMore information\n\nTo find out mor
 e about our ML training under Destination Earth\, take a look at our ML tr
 aining page. \n\n\nIf you are interested\, join the free online course Ma
 chine Learning for Earth Systems Modelling: Applications and Future Direct
 ions. \n\n\nThe panel will be recorded and made available shortly after t
 he event on our YouTube channel\, and accessible through our eLearning pla
 tform as part of the course. \n\n\nhttps://events.ecmwf.int/event/587/
IMAGE;VALUE=URI:https://events.ecmwf.int/event/587/logo-3416862995.png
LOCATION:Virtual
URL:https://events.ecmwf.int/event/587/
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