The power of bridging decision scales: Model coupling for advanced climate policy analysis

Area of Science:

• Environmental science and policy modeling.
• Socioeconomic systems analysis.
• Computational sustainability.

Background:

• Climate policy faces complex challenges across multiple scales in nature-society systems.
• Existing climate policy models struggle to capture multiscale socioeconomic decisions.
• Need for integrated approaches to address climate-economy interactions.

Purpose of the Study:

• To highlight the power of coupling different modeling families for climate policy analysis.
• To examine the unique contributions and synergies of Integrated Assessment Models (IAM), Computable General Equilibrium (CGE), and Agent-Based Models (ABM).
• To demonstrate how coupled models can support effective and equitable climate policies.

Main Methods:

• Reviewing and synthesizing the strengths of IAM, CGE, and ABM.
• Examining the feasibility and effectiveness of coupling these modeling approaches.
• Presenting examples of effective IAM-ABM-CGE coupling.

Main Results:

• Model coupling is increasingly feasible and effective due to computational advances and data availability.
• Coupling IAM, CGE, and ABM leverages complementary strengths for nuanced insights.
• Effective coupling maintains model integrity while enhancing policy relevance.

Conclusions:

• Coupled models provide deeper understanding of climate-economy interactions.
• Bridging human decision scales through model coupling supports more effective and equitable climate policies.
• Integrated modeling approaches are crucial for addressing complex global environmental challenges.