AI generated climate model of solar panels and wind turbines.

Can AI Solve Climate Change? Combining Climate Models for a Sustainable Future

Mira Elwood in Climate & Environment December 2025 • 4 min read.

"Discover how integrated assessment models (IAMs) and power sector models (PSMs) are merging to create a clearer picture of our energy future."

The urgency of climate change demands sophisticated strategies, and at the heart of this effort are Integrated Assessment Models (IAMs). These models help us quantitatively analyze different climate change mitigation approaches. However, because IAMs typically operate on a global scale across long timeframes, they often lack the specific temporal and spatial details needed to fully understand the critical role of Variable Renewable Electricity (VRE) in decarbonizing the power sector.

Enter Power Sector Models (PSMs). These models offer high resolution insights but tend to be more limited in scope, focusing on narrower sectors, geographies, and shorter time horizons. To harness the strengths of both, a new approach is emerging that combines these tools, promising more robust and actionable strategies.

This article explores how a novel methodology uses AI to combine the broad perspective of IAMs with the granular detail of PSMs. By iteratively linking these models, we aim for a more complete understanding and potentially more effective solutions to climate change.

Bridging the Gap: A New Approach to Climate Modeling

AI generated climate model of solar panels and wind turbines.

The innovative approach involves an iterative, automated “soft-coupling” framework. This framework allows a long-term IAM to interact with a detailed PSM, leveraging the strengths of both. The key is to use market values and capture prices from the PSM as price signals, influencing the IAM’s capacity and power mix.

This ensures that both models make endogenous investment decisions, working towards a joint solution. Here's a breakdown of what this means:

IAMs: Provide a broad, long-term view of the energy economy, but with simplified representations of the power sector.
PSMs: Offer detailed hourly analysis of the power sector, but lack the broader economic and global context.
Soft-Coupling: An iterative process where information (primarily price signals) is exchanged between the models, allowing each to influence the other's investment decisions.
Endogenous Investment: Both models can independently decide where and how much to invest in different energy technologies, based on the price signals they receive.

In simpler terms, imagine two experts, one in global economics and another in local energy grids, working together. The economics expert provides the general financial landscape, and the local grid expert offers insights on pricing. By collaborating and adjusting their strategies, they arrive at a more realistic and effective energy plan.

The Future of Climate Modeling

This novel coupling framework represents a significant step forward in climate modeling. By combining the strengths of both IAMs and PSMs and ensuring comprehensive coupling, scientists and policymakers gain a more nuanced and reliable understanding of the energy transition, paving the way for more effective and sustainable climate mitigation strategies.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.5194/gmd-16-4977-2023,

Title: Bidirectional Coupling Of A Long-Term Integrated Assessment Model Remind V3.0.0 With An Hourly Power Sector Model Dieter V1.0.2

Subject: econ.gn q-fin.ec

Authors: Chen Chris Gong, Falko Ueckerdt, Robert Pietzcker, Adrian Odenweller, Wolf-Peter Schill, Martin Kittel, Gunnar Luderer

Published: 06-09-2022

Everything You Need To Know

What are Integrated Assessment Models (IAMs), and how do they relate to climate change mitigation?

Integrated Assessment Models (IAMs) are sophisticated tools used to analyze various climate change mitigation approaches. They provide a broad, long-term view of the energy economy, which is crucial for understanding the overall impact of different strategies. IAMs help quantify the effects of different policies and technologies on climate change, offering insights into the most effective pathways for reducing greenhouse gas emissions. However, IAMs often lack the detailed information about specific sectors, such as the power sector, that is needed for comprehensive analysis.

What is the role of Power Sector Models (PSMs) in understanding climate change, and how do they differ from IAMs?

Power Sector Models (PSMs) offer detailed, high-resolution insights into the power sector, focusing on hourly analysis of energy production and distribution. They provide granular information about the operation of electricity grids, the integration of renewable energy sources, and the impact of different policies on the power sector. Unlike IAMs, PSMs are typically more limited in scope, focusing on narrower sectors, geographies, and shorter time horizons. PSMs excel at providing a detailed understanding of the power sector dynamics, which is essential for designing effective climate change mitigation strategies.

How does the "soft-coupling" framework between IAMs and PSMs work, and why is it important?

The "soft-coupling" framework is an iterative process that links IAMs and PSMs, allowing them to exchange information and influence each other's decisions. The framework uses market values and capture prices from the PSM as price signals, which then influence the IAM’s capacity and power mix. This ensures that both models make endogenous investment decisions, working towards a joint solution. This approach is important because it combines the strengths of both models: the broad, long-term view of IAMs and the detailed, high-resolution insights of PSMs. This collaboration results in a more realistic and effective energy plan, leading to more accurate climate change mitigation strategies.

Can you explain the concept of "endogenous investment" within the context of climate modeling?

Endogenous investment means that both IAMs and PSMs can independently decide where and how much to invest in different energy technologies based on the price signals they receive. In this framework, the models are not pre-programmed with investment decisions; instead, they dynamically adjust their investment strategies based on the economic signals and feedback they get from each other. For example, if the PSM indicates that solar power is becoming more cost-effective, the IAM will adjust its investment decisions accordingly, increasing the allocation for solar capacity. This dynamic process allows the models to adapt and evolve, leading to more accurate and realistic scenarios for the energy transition.

What are the potential benefits of combining IAMs and PSMs for climate modeling, and how might this approach impact climate change mitigation strategies?

Combining IAMs and PSMs offers several significant benefits for climate modeling. By integrating the broad perspective of IAMs with the granular detail of PSMs, scientists and policymakers gain a more nuanced and reliable understanding of the energy transition. This allows for the development of more effective and sustainable climate mitigation strategies. For instance, the combined approach can help identify the most cost-effective ways to decarbonize the power sector, assess the impact of different policy interventions, and forecast the long-term effects of various technologies. This integrated approach can lead to more informed decision-making and more impactful policies to combat climate change.