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001049641 037__ $$aFZJ-2025-05426
001049641 041__ $$aEnglish
001049641 1001_ $$0P:(DE-Juel1)207675$$aMelidonis, Savvas$$b0$$eCorresponding author$$ufzj
001049641 1112_ $$aAI in Science Summit$$cCopenhagen$$d2025-11-03 - 2025-11-04$$wDenmark
001049641 245__ $$aHClimRep: AI Climate Model for Capturing the Atmosphere, Ocean, and Sea Ice Interactions
001049641 260__ $$c2025
001049641 3367_ $$033$$2EndNote$$aConference Paper
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001049641 520__ $$aClimate change poses a significant threat to ecosystems and human society. Accurate climate projections are crucial for developing effective policies for mitigating extreme weather events that are expected to increase due to global warming. However, traditional climate models have limitations, including biases and high computational costs. Under the Helmholtz Foundation Model Initiative (HFMI), we propose a new data-driven climate model, namely HClimRep, which uses foundation model principles and machine learning to analyze diverse climate datasets. This approach enables flexible and customizable outputs, providing a versatile tool for climate applications. Keywords: Foundation Model, AI Model, Deep Learning, Climate Modelling, Climate Simulations
001049641 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001049641 536__ $$0G:(DE-Juel-1)ESDE$$aEarth System Data Exploration (ESDE)$$cESDE$$x1
001049641 536__ $$0G:(DE-HGF)HClimRep2024050120270431$$aHClimRep2024050120270431 - Helmholtz Representation Model for Climate Science (HClimRep) (HClimRep2024050120270431)$$cHClimRep2024050120270431$$x2
001049641 7001_ $$0P:(DE-Juel1)186635$$aPatnala, Ankit$$b1$$ufzj
001049641 7001_ $$0P:(DE-Juel1)203330$$aSemcheddine, Asma$$b2$$ufzj
001049641 7001_ $$0P:(DE-Juel1)6952$$aSchultz, Martin$$b3$$ufzj
001049641 7001_ $$0P:(DE-HGF)0$$aPolz, Julius$$b4
001049641 7001_ $$0P:(DE-HGF)0$$aNowak, Kacper$$b5
001049641 8564_ $$uhttps://cdn.prod.website-files.com/68a7113a28bc36a9033775bf/6903613bfba9f2d65bde4275_32.pdf
001049641 8564_ $$uhttps://juser.fz-juelich.de/record/1049641/files/AIS2025_paper_0024.pdf$$yRestricted
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001049641 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)207675$$aForschungszentrum Jülich$$b0$$kFZJ
001049641 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)186635$$aForschungszentrum Jülich$$b1$$kFZJ
001049641 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)203330$$aForschungszentrum Jülich$$b2$$kFZJ
001049641 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)6952$$aForschungszentrum Jülich$$b3$$kFZJ
001049641 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Karlsruher Institut für Technologie$$b4
001049641 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Alfred Wegener Institute$$b5
001049641 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001049641 9141_ $$y2025
001049641 920__ $$lyes
001049641 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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