Published July 17, 2026
| Version v1
Poster
Open
Accelerating Aerosol Hygroscopicity Prediction with Deep Learning and HPC Deployment
Authors/Creators
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1.
VSB - Technical University of Ostrava
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2.
CSC - IT Center for Science (Finland)
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3.
University of Eastern Finland
Description
Aerosol hygroscopicity strongly influences clouds, radiation, and air quality, but physics-based simulations are computationally expensive. This project develops a machine-learning emulator to predict Ƙsu and Ƙca directly from atmospheric composition fields, as a step toward an AI-based aerosol process component for integration into high resolution global climate models within the DestinE Climate Digital Twin initiative.
Files
04_HPCSE26_Halfar-Radek_Billy-Braithwaite_Juha-Tonttila_Laakso-Anton_Kokkola-Harri_Sarkar-Arup_Antti-Vartiainen.pdf
Files
(2.2 MB)
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