Artificial intelligence to support cross-disciplinary climate change research

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Ou, Y., Rodriguez-Pardo, C., Al Khourdajie, A. ORCID: https://orcid.org/0000-0003-1376-7529, Rogelj, J. ORCID: https://orcid.org/0000-0003-2056-9061, Zhou, P., Mukkavilli, S.K., Tavoni, M., Clarke, L., Liu, Y., Wang, T., Oh, A., & McJeon, H. (2026). Artificial intelligence to support cross-disciplinary climate change research. Nature Climate Change 10.1038/s41558-026-02624-x. (In Press)

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Project: Expanding Integrated Assessment Modelling: Comprehensive and Comprehensible Science for Sustainable, Co-Created Climate Action (IAM COMPACT, HE 101056306), Delivering the next generation of open Integrated Assessment MOdels for Net-zero, sustainable Development (DIAMOND, HE 101081179)

Abstract

Integrating knowledge across climate risks, societal responses and their interactions is a critical yet persistently challenging goal. We argue that advanced artificial intelligence frameworks, specifically foundation models, offer a new opportunity to unify these domains and support climate decision-making.

Item Type: Article
Research Programs: Energy, Climate, and Environment (ECE)
Energy, Climate, and Environment (ECE) > Integrated Assessment and Climate Change (IACC)
Energy, Climate, and Environment (ECE) > Transformative Institutional and Social Solutions (TISS)
Depositing User: Michaela Rossini
Date Deposited: 28 Apr 2026 12:32
Last Modified: 28 Apr 2026 12:32
URI: https://pure.iiasa.ac.at/21516

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