Accelerating Aerosol Hygroscopicity Prediction with Deep Learning and HPC Deployment

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-17
DOI
https://doi.org/10.5281/zenodo.21414089
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00
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article

Accelerating Aerosol Hygroscopicity Prediction with Deep Learning and HPC Deployment

Harri Kokkola, Billy Braithwaite, Anton Laakso, Radek Halfar et al.
Zenodo (CERN European Organization for Nuclear Research)
Atmospheric aerosols and clouds
article

Accelerating Aerosol Hygroscopicity Prediction with Deep Learning and HPC Deployment

Harri Kokkola, Billy Braithwaite, Anton Laakso, Radek Halfar, Juha Tonttila, Antti Vartiainen, Arup Sarkar
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
VSB - Technical University of Ostrava (CZ), University of Eastern Finland (FI), Finland University (FI), CSC - IT Center for Science (Finland) (FI)
Climate action
Openalex Percentile: Top 10%
Atmospheric aerosols and clouds
DOIOpen Access PDFOpenAlex
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Accelerating Aerosol Hygroscopicity Prediction with Deep Learning and HPC Deployment — Harri Kokkola, Billy Braithwaite, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS