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AI-empowered Next-Generation Multiscale Climate Modelling for Mitigation and Adaptation
🎙️ Episode 24: AI-empowered Next-Generation Multiscale Climate Modelling for Mitigation and Adaptation
🔗 DOI: https://doi.org/10.1038/s41561-024-01527-w
🌐 Abstract
Despite decades of progress, Earth system models (ESMs) still face significant gaps in accuracy and uncertainty, largely due to challenges in representing small-scale or poorly understood processes. This episode explores a transformative vision for next-generation climate modeling—one that embeds AI across multiple scales to enhance resolution, improve model fidelity, and better inform climate mitigation and adaptation strategies.
📌 Bullet points summary
Existing ESMs struggle with inaccuracies in climate projections due to subgrid-scale and unknown process limitations.
A new approach is proposed that blends AI with multiscale modeling, combining fine-resolution simulations with coarser hybrid models that capture key Earth system feedbacks.
This strategy is built on four pillars:
Higher resolution via advanced computing
Physics-aware machine learning to enhance hybrid models
Systematic use of Earth observations to constrain models
Modernized scientific infrastructure to operationalize insights
Aims to deliver faster, more actionable climate data to support urgent policy needs for both mitigation and adaptation.
Envisions hybrid ESMs and interactive Earth digital twins, where AI helps simulate processes more realistically and supports climate decision-making at scale.
💡 The Big Idea
Integrating AI into climate models across scales is not just an upgrade—it’s a shift towards smarter, faster, and more adaptive climate science, essential for responding to the climate crisis with precision and urgency.
📖 Citation
Eyring, Veronika, et al. "AI-empowered next-generation multiscale climate modelling for mitigation and adaptation." Nature Geoscience 17.10 (2024): 963–971.
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By Amirpasha🎙️ Episode 24: AI-empowered Next-Generation Multiscale Climate Modelling for Mitigation and Adaptation
🔗 DOI: https://doi.org/10.1038/s41561-024-01527-w
🌐 Abstract
Despite decades of progress, Earth system models (ESMs) still face significant gaps in accuracy and uncertainty, largely due to challenges in representing small-scale or poorly understood processes. This episode explores a transformative vision for next-generation climate modeling—one that embeds AI across multiple scales to enhance resolution, improve model fidelity, and better inform climate mitigation and adaptation strategies.
📌 Bullet points summary
Existing ESMs struggle with inaccuracies in climate projections due to subgrid-scale and unknown process limitations.
A new approach is proposed that blends AI with multiscale modeling, combining fine-resolution simulations with coarser hybrid models that capture key Earth system feedbacks.
This strategy is built on four pillars:
Higher resolution via advanced computing
Physics-aware machine learning to enhance hybrid models
Systematic use of Earth observations to constrain models
Modernized scientific infrastructure to operationalize insights
Aims to deliver faster, more actionable climate data to support urgent policy needs for both mitigation and adaptation.
Envisions hybrid ESMs and interactive Earth digital twins, where AI helps simulate processes more realistically and supports climate decision-making at scale.
💡 The Big Idea
Integrating AI into climate models across scales is not just an upgrade—it’s a shift towards smarter, faster, and more adaptive climate science, essential for responding to the climate crisis with precision and urgency.
📖 Citation
Eyring, Veronika, et al. "AI-empowered next-generation multiscale climate modelling for mitigation and adaptation." Nature Geoscience 17.10 (2024): 963–971.