Climate models

What Are Climate Models?

Climate models are sophisticated computer programs designed to simulate the interactions of the Earth's climate system, including the atmosphere, oceans, land surface, and ice. These models are fundamental tools within the broader field of climate finance and are used to project future climate conditions based on various inputs, such as greenhouse gas concentrations and land-use changes. By providing insights into potential future climatic states, climate models help financial institutions and other organizations understand and manage various forms of financial risk related to climate change.

History and Origin

The concept of modeling the Earth's climate has roots in early scientific endeavors to understand atmospheric processes. Pioneering work in the late 19th and early 20th centuries laid theoretical foundations, such as Swedish chemist Svante Arrhenius's mathematical basis for the greenhouse effect in 1896²⁹. However, the advent of high-speed computing in the mid-20th century transformed climate modeling.

In 1956, American meteorologist Norman Phillips developed what is widely regarded as the first "general circulation model" (GCM) of the atmosphere, realistically depicting seasonal patterns. His work marked a significant step toward using computers to simulate global atmospheric circulation over longer periods²⁶, ²⁷, ²⁸. Later, in 1967, Syukuro Manabe and Richard Wetherald published a seminal paper that introduced a one-dimensional radiative-convective model, offering the first credible predictions of how atmospheric temperature would respond to changes in carbon dioxide (CO2) levels²³, ²⁴, ²⁵. The sophistication and accuracy of climate models have continuously improved since then, incorporating more complex Earth system components like oceans, land, and sea ice²¹, ²².

Key Takeaways

• Climate models are computer programs that simulate the Earth's climate system.
• They project future climate conditions under different scenarios of greenhouse gas emissions and other factors.
• These models are essential for assessing physical risk and transition risk in financial contexts.
• Outputs from climate models inform strategic planning and risk management across various sectors.

Interpreting Climate Models

Climate models are not designed to provide precise forecasts of specific weather events years into the future. Instead, their outputs are probabilistic projections and scenarios that illustrate a range of plausible future climate states based on different assumptions about human activities and their impact on the climate system. For instance, these models can project changes in global temperature, sea levels, and the frequency of extreme weather events over decades or centuries.

Interpreting climate model outputs involves understanding the underlying assumptions and the inherent uncertainties. The Intergovernmental Panel on Climate Change (IPCC) extensively evaluates climate models and their ability to simulate observed climate changes, confirming a clear human influence on the climate system¹⁹, ²⁰. Financial institutions utilize these projections to conduct scenario analysis and stress testing, helping them evaluate how different climate pathways could impact their assets, liabilities, and overall resilience.

Hypothetical Example

Consider a global real estate investment fund managing a diverse investment portfolio that includes properties in coastal regions. To assess the potential impacts of climate change, the fund might use climate models.

The fund's risk assessment team could input various climate policy scenarios into a climate model, such as one where global carbon emissions are significantly reduced, or another where they continue to rise unchecked. The model would then project localized impacts like rising sea levels, increased frequency of coastal flooding, or changes in storm intensity for the regions where the fund owns properties.

If a climate model projects a high likelihood of a 1-meter sea-level rise by 2050 under a "business-as-usual" scenario, the fund might identify specific properties at high risk assessment. This insight could prompt them to divest from highly exposed assets, invest in protective measures like seawalls, or adjust their future investment strategies to favor less vulnerable regions. This use of climate models allows for proactive financial planning based on potential long-term environmental changes.

Practical Applications

Climate models have become indispensable tools across various financial and regulatory domains. Central banks and financial supervisors leverage these models to understand macro-financial implications of climate change. For example, the Network for Greening the Financial System (NGFS), a group of central banks and supervisors, develops and publishes a range of climate scenarios based on climate models to help financial institutions analyze potential economic impacts¹⁶, ¹⁷, ¹⁸. These scenarios explore different futures, categorized as orderly, disorderly, or "hot house world," reflecting varying levels of climate action and associated physical and transition risks¹³, ¹⁴, ¹⁵.

Regulators also increasingly recognize the importance of climate models for disclosures. The U.S. Securities and Exchange Commission (SEC), for instance, proposed rules to enhance and standardize climate-related disclosures for public companies, aiming to provide investors with more consistent and reliable information on climate-related risks⁹, ¹⁰, ¹¹, ¹². Although the SEC's climate disclosure rule faced legal challenges and its defense was later ended in March 2025, the intent was to require companies to report on material climate-related risks, including those identified through scenario analysis using climate models⁵, ⁶, ⁷, ⁸. This regulatory emphasis highlights the growing need for robust data analysis and modeling capabilities to quantify and report climate-related financial exposures.

Limitations and Criticisms

Despite their advancements, climate models have inherent limitations and face criticisms. One significant challenge is the complexity of Earth's climate system, which involves countless interacting variables across different scales. While models have improved, uncertainties persist, particularly in quantifying human influence on regional climate indicators and accurately representing all processes³, ⁴. Factors such as the brevity of observational records and limitations in understanding certain processes contribute to these uncertainties².

Furthermore, projections from climate models depend heavily on assumptions about future socioeconomic development, technological advancements, and policy decisions, which are inherently difficult to predict. The IPCC acknowledges that some differences from observations, for example in regional precipitation patterns, still exist¹. While climate models are continually refined, they are not perfect predictors. Financial decision-makers must consider these uncertainties, alongside model limitations, when integrating climate model outputs into their risk mitigation and capital allocation strategies. The goal is to use them as decision-support tools rather than definitive forecasts, incorporating a comprehensive understanding of potential environmental, social, and governance (ESG) factors.

Climate Models vs. Climate Scenarios

The terms "climate models" and "climate scenarios" are often used interchangeably, but they represent distinct concepts within the field of climate risk analysis.

Climate models are the computational frameworks and scientific tools (i.e., the programs themselves) that simulate the Earth's climate system. These complex mathematical representations incorporate fundamental laws of physics, chemistry, and biology to project how various climate factors—like temperature, precipitation, and sea level—might change over time given specific inputs, such as greenhouse gases emissions pathways.

In contrast, climate scenarios are plausible descriptions of future climate conditions, often derived from the outputs of climate models. A climate scenario provides a coherent, internally consistent narrative about potential future climate developments, usually under different assumptions about global policy actions (e.g., strong mitigation efforts vs. limited action) and their resulting emissions. Organizations like the NGFS develop sets of standardized climate scenarios (e.g., Orderly, Disorderly, Hot House World) that financial institutions use to assess climate-related financial risks. Thus, climate models are the engines that generate the data and projections, while climate scenarios are the structured narratives and data sets used for analysis.

FAQs

What is the primary purpose of climate models in finance?

The primary purpose of climate models in finance is to help assess and quantify climate-related financial risks and opportunities. By projecting potential future climate conditions, these models enable financial institutions to conduct asset allocation, analyze portfolio vulnerabilities, and inform strategic decisions related to climate change impacts.

Are climate models the same as weather forecasting models?

No, climate models are distinct from weather forecasting models. Weather models predict short-term atmospheric conditions (hours to days), while climate models simulate long-term climate trends (decades to centuries). Climate models focus on average conditions and variability over extended periods, providing insights relevant for strategic planning rather than daily operational decisions.

How do climate models account for human activity?

Climate models account for human activity by incorporating inputs such as historical and projected anthropogenic emissions of greenhouse gases, aerosols, and land-use changes (e.g., deforestation). These human-driven factors are integrated into the model's equations to simulate their impact on the Earth's energy balance and subsequent climate responses.

What are the main types of climate risks assessed using climate models?

The main types of climate risks assessed using climate models are physical risks and transition risks. Physical risks include the impacts of extreme weather events (e.g., floods, heatwaves) and long-term changes (e.g., sea-level rise). Transition risks stem from the economic and regulatory changes associated with shifting to a low-carbon economy, such as carbon pricing, technological disruptions, and changes in consumer preferences.

How accurate are climate models?

Climate models have demonstrated significant skill in simulating observed climate changes, particularly on global and continental scales, and have consistently projected warming trends that align with real-world observations. However, their accuracy can vary depending on the scale and complexity of the phenomena being modeled, and they contain uncertainties related to future human behavior and natural climate variability. Their continuous refinement relies on ongoing research and improved computational capabilities.