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DTSTAMP:20260605T154540Z
LOCATION:Bldg. 6 - Room 103
DTSTART;TZID=Europe/Stockholm:20260701T140000
DTEND;TZID=Europe/Stockholm:20260701T160000
UID:submissions.pasc-conference.org_PASC26_sess162@linklings.com
SUMMARY:MS5E - Foundation Model for Weather and Climate
DESCRIPTION:Organizer(s): Xavier Lapillonne (MeteoSwiss), Ilaria Luise (EC
 MWF), and Sebastian Schemm (University of Cambridge)\n\nIn recent years we
 ather forecasting and to a lower extent climate modeling have been undergo
 ing a revolution driven by the emergence of machine learning-based models.
  After having been successfully developed and used in the field of Large L
 anguage Model, the foundation model concept is being applied to machine le
 arning-based weather-forecasting. The goal is to capture rich, multi-scale
  representations of the Earth system across space and time by training on 
 diverse datasets. These models can then be applied to a wide range of task
 s, much like traditional equation-based Earth system models. The first lar
 ge foundation models are now emerging, and their potential applications ar
 e actively being explored. The talks in this minisymposium will define the
  concept of foundation models for weather and climate, discuss both their 
 development and applications, and provide a comprehensive overview of the 
 current state of the field.\n\nPanel Discussion Foundation Model for Weath
 er and Climate\n\nThe panel discussion will explore the challenges and opp
 ortunities of using foundation models for weather and climate.\n\n\nXavier
  Lapillonne (MeteoSwiss)\n---------------------\nEarth System Foundation M
 odel - Heterogeneous Data Integration and Forecasting\n\nThe talk introduc
 es the Earth System Foundation Model (ESFM), a fully open foundation model
  tailored for weather and climate modeling tasks. Built upon the Swin Tran
 sformer backbone of the pioneering Aurora model, ESFM introduces several k
 ey extensions that allow it to process diverse and heterogene...\n\n\nFira
 t Ozdemir, Yun Cheng, and Salman Mohebi (Swiss data science center); Fanny
  Lehmann, Simon Adamov, Langwen Huang, Leonardo Trentini, Oliver Fuhrer, T
 orsten Hoelfer, and Siddhartha Mishra (ETH Zurich); Sebastian Schemm (Univ
 ersity of Cambridge); Benedikt Soja (ETH Zurich); and Mathieu Salzmann (Sw
 iss data science center)\n---------------------\nClimate in a Bottle: Towa
 rds a Foundation Model for Climate\n\nAI emulators offer a path to compres
 sing, boosting limited ensembles, and improving the latency of interacting
  with petabyte-scale climate prediction data. However, prevailing auto-reg
 ressive paradigms offer limited flexibility, and are challenging to train 
 on climate time horizons due to drifts, in...\n\n\nKarthik Kashinath (NVID
 IA Inc.)\n---------------------\nWeatherGenerator: A Foundation Model for 
 Weather and Climate\n\nThe WeatherGenerator project aims to develop a foun
 dation model for the European community that combines a wide variety of da
 tasets to improve a broad range of applications across spatial and tempora
 l scales. The WeatherGenerator model is a highly multimodal transformer ca
 pable of ingesting and pred...\n\n\nJulian Kuehnert (ECMWF)\n\nDomain: Cli
 mate, Weather, and Earth Sciences\n\nSession Chair: Xavier Lapillonne (Met
 eoSwiss)
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