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The atmospheric composition component of the ICON modeling framework : ICON-ART version 2025.10

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Hoshyaripour, Gholam Ali ; Baer, Andreas ; Bierbauer, Sascha ; Bruckert, Julia ; Brunner, Dominik ; Förstner, Jochen ; Hamzehloo, Arash ; Hanft, Valentin ; Keller, Corina ; Klose, Martina ; Kumar, Pankaj ; Ludwig, Patrick ; Metzner, Enrico ; Muth, Lisa ; Pauling, Andreas ; Porz, Nikolas ; Ramezani Ziarani, Maryam ; Reddmann, Thomas ; Reißig, Luca ; Ruhnke, Roland ; Satitkovitchai, Khompat ; Seifert, Axel ; Sinnhuber, Miriam ; Steiner, Michael ; Versick, Stefan ; Vogel, Heike ; Weimer, Michael ; Werchner, Sven ; Hoose, Corinna:
The atmospheric composition component of the ICON modeling framework : ICON-ART version 2025.10.
In: Geoscientific model development. 19 (27. Februar 2026) 4. - S. 1645-1681.
ISSN 1991-9603 ; 1991-959x

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Volltext Link zum Volltext (externe URL):
https://doi.org/10.5194/gmd-19-1645-2026

Kurzfassung/Abstract

Accurate and efficient modeling of atmospheric composition, including aerosols and trace gases and their interactions with radiation, clouds, and dynamics is essential for improving predictions and understanding of air quality, weather, climate, and related health impacts. The Aerosols and Reactive Trace gases (ART) component extends the ICOsahedral Nonhydrostatic (ICON) modeling framework by enabling online, fully coupled simulations of atmospheric composition processes across scales. ICON-ART includes modules for emissions, transport, gas-phase chemistry, and aerosol microphysics in both the troposphere and stratosphere, allowing for the investigation of feedbacks between atmospheric composition and physical processes from the large-eddy to global scale.

This paper presents an updated overview of the ICON-ART framework as implemented in version 2025.10, highlighting recent developments in emission parameterizations, chemical mechanisms, aerosol processes, and coupling to the physical core of ICON via aerosol–radiation and aerosol–cloud interactions. We summarize the structure of the code infrastructure and demonstrate the model’s flexibility and scalability across a wide range of applications. ICON-ART provides a unified and modular platform for research and operational use in atmospheric composition, bridging the gap between regional air quality modeling and global Earth system simulations.

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Publikationsform:Artikel
Sprache des Eintrags:Englisch
Institutionen der Universität:Mathematisch-Geographische Fakultät > Mathematik > Mathematisches Institut für Maschinelles Lernen und Data Science (MIDS)
DOI / URN / ID:10.5194/gmd-19-1645-2026
Open Access: Freie Zugänglichkeit des Volltexts?:Ja
Peer-Review-Journal:Ja
Verlag:Copernicus
Die Zeitschrift ist nachgewiesen in:
Titel an der KU entstanden:Ja
KU.edoc-ID:36579
Eingestellt am: 24. Apr 2026 11:04
Letzte Änderung: 24. Apr 2026 11:04
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/36579/
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