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UID:submissions.pasc-conference.org_PASC24_sess108_msa295@linklings.com
SUMMARY:AtmoRep: A Probabilistic Multi-Purpose Model for Atmospheric Dynam
 ics
DESCRIPTION:Minisymposium\n\nChristian Lessig (ECMWF, Otto-von-Guericke-Un
 iversitat Magdeburg) and Ilaria Luise (CERN)\n\nAtmoRep is a first example
  of probabilistic multi-purpose model that extends the concept of represen
 tation learning to Earth system science, and in particular to atmospheric 
 dynamics. Starting from a single pre-trained architecture used as a backbo
 ne, AtmoRep is able to achieve skilful results in multiple zero-shot appli
 cations such as nowcasting, temporal interpolation and scenario generation
 , compared to the state-of-the-art approaches. Thanks to a novel definitio
 n of the loss, the model is also probabilistic by design, as it outputs a 
 set of ensemble members for each task, with well calibrated distributions 
 as proven for weather forecasting. The first part of the talk will focus o
 n the innovative aspects of the model architecture, with particular attent
 ion to the local space-time approach and the flexible plug-and-play design
 . The second part of the talk will show the current results for the most r
 elevant applications, while the last part of the talk will focus on the fu
 ture foreseen developments.\n\nDomain: Climate, Weather, and Earth Science
 s, Computational Methods and Applied Mathematics\n\nSession Chair: Christi
 an Lessig (ECMWF, Otto-von-Guericke-Universitat Magdeburg)
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