The need to understand the physical impacts of climate change grows by the day, with asset managers, investors, banks, corporations, and governments all under increasing pressure to identify and manage the impact of climate change on financial performance.

According to the Task Force on Climate-related Financial Disclosures (TCFD), “Financial markets need clear, comprehensive, high-quality information on the impacts of climate change.”

Similar to a growing number of regulators and organizations across the world, the TCFD is recommending that climate scenario analysis is leveraged to identify potential climate change implications.

Scenario analysis provides a framework to assess potential implications by capturing uncertainties across a range of plausible global outcomes.

But it is an incredibly complex task to encapsulate climate change risks and potential impact outcomes, as the assessment of climate change risks requires an understanding of the various drivers of uncertainty that could impact any predicted outcomes.

Global Climate Model Uncertainty and Scenario Analysis

The global risk management community leverages climate models from the Coupled Model Intercomparison Project (CMIP) to provide access to forward-looking climate risks. These models also underpin the Intergovernmental Panel on Climate Change’s (IPCC) reports.

Instrumental in modeling large-scale, long-term, global modes of variability and trends in atmospheric and ocean circulation systems, these models are used to understand the dynamical changes in the Earth’s physical system.

Trends include global mean temperature and large-scale convective changes that impact regional precipitation patterns.

The basis for the CMIP models and the results of the IPCC is the product of a dozen global model consortiums built on the contribution of thousands of highly skilled, Ph.D.-qualified individuals and many supercomputing hours. The result is an ensemble of global model results that each differs in their estimated outcomes.

As models somewhat vary in their methodology, the modeling of physical principles, and observational datasets, among other factors, all contribute to variability in modeled outcomes.

The benefit is that by using multi-model ensembles the scientific community can contextualize the range of climate outcomes across models from various scientific institutions giving equal credence to each modeled climate response.

Global Emission Scenarios

Underneath the model uncertainty in climatic outcomes is the uncertainty around which global emission scenario the global community will reach in the future.

Scenario uncertainty[1] is a large driver of differing climate outcomes by the end of the century due to unknowns like future population and economic growth, technological and policy change, and other factors that influence the amount of greenhouse gas emissions released into the atmosphere.

Climate models address this uncertainty by modeling a range of outcomes from Shared Socioeconomic Pathways (SSPs), which examine aspects like changing demographics and economic growth, and Representative Concentration Pathways (RCPs), which aim to capture the amount of additional greenhouse gas emissions given different SSPs.

In other words, climate change scenarios, such as RCPs, project future levels of greenhouse gas emissions which depend on policy choices by governments around the world and decisions made by individuals, businesses, and industries.

For example, RCP8.5 (associated with SSP5[2]), models the demographic, economic, political, and technological changes in a world where mitigation becomes more challenging than adaptation, leading to raised fossil fuel emissions.  

A middle-of-the-road scenario, RCP4.5 (associated with SSP2), represents greater fossil fuel usage reductions and less global warming overall. Combining results from RCP8.5 and RCP4.5 offers a range of outcomes and a highly nuanced view of plausible future climate impacts that accounts for intra-model and global scenario uncertainties.

Latest Version of Moody’s Climate on Demand

Moody’s Climate on Demand solution will be updated in April to include multiple climate change scenarios, in order to enable real asset scenario analysis. Additionally, this update will now leverage CMIP6 data from the latest iteration of the IPCC climate models with direct mapping to SSPs.

Scenario analysis capabilities available in Climate on Demand will now enable global location-specific climate projections starting from 2030 and extending to 2100 for any location.  

These scenarios will enable users to explore climate change outcomes across multiple scenarios capturing middle-of-the-road to more extreme global warming outcomes.

All this complexity can be difficult to untangle, so Moody’s Climate on Demand provides many climate indicators and helpful benchmarks to understand the evolution of hazard levels for assets in a global and local context.  

Our view of hazard is granular and includes multiple indicators per hazard in order to provide detailed data on the varying nature of how the hazards will evolve in a changing climate.

Climate on Demand will also deliver scenario analysis data for ten climate metrics, such as the decadal increase in extreme heat days, as well as contextualized, globally comparable scores.

For example, understanding the level of risk associated with an increased number of extreme heat days in a location is difficult in isolation, which is why we provide hazard risk scores on a 0-100 scale to contextualize this information for the user based upon global benchmarks.

Our data provides users with the ability to track how these climate metrics change over the subsequent decades along with scores calibrated to be consistent across both RCP climate scenarios and across all time horizons until the end of the century.

These hazard scores enable an apples-to-apples comparison globally, providing users with additional insight into rates of change and how that location compares to the global range of plausible climate outcomes.

Moody’s Climate on Demand now aligns with the best TCFD practices, which foundationally inform a number of climate regulations and reporting frameworks, such as the International Sustainability Standards Board (ISSB) Climate-Related Disclosures framework.[3]

Our approach also enables users to meet stress testing requirements from different regulators around the world, such as the European Central Bank (ECB).

In the United States, the Federal Reserve is currently undertaking a pilot climate scenario analysis exercise with six of the country’s largest banks in an effort to enhance the ability of supervisors and firms to measure and manage climate-related financial risks.[4]

This follows a similar exercise undertaken in Canada by the Office of the Superintendent of Financial Institutions (OFSI) and the Bank of Canada.[5]

Additionally, many regulations and scenario analyses call for specific global mean temperature-based scenarios, such as the International Energy Agency (IEA)[6] and NGFS (Network for Greening the Financial System) scenarios[7], which describe the efforts needed to reduce carbon dioxide emissions in line with the 1.5 degrees and 2 degree Celsius warming scenarios in the Paris Agreement, based on projected global mean temperature increases.

These types of scenarios are also enabled within Moody’s Climate on Demand by utilizing combinations of the RCPs and time horizons made available in the platform. For example, a two degree Celsius scenario can be evaluated with RCP4.5 at mid-century[8] according to the IPCC and the latest CMIP6 modeling.

New Pro Offering

In June, the Moody’s Climate on Demand solution will expand further to include the financial quantification of physical climate risk to locations with our Pro offering.

The introduction of Moody’s Climate on Demand Pro will integrate global physical climate risk models from Moody’s Risk Management Solutions (RMS), to leverage decades of expertise in climate science, engineering, and financial modeling originally built to quantify risk in the US$2.5 trillion (re)insurance market.

To learn more about Climate on Demand product updates and analysis on key trends shaping global climate change risk assessment and sustainable finance please visit Moody’s Climate on Demand and talk to an expert today.

[1] Also referred to as radiative forcing uncertainty.

[2] Referred to as “Fossil Fueled Development”; Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O’neill, B. C., Fujimori, S., ... & Tavoni, M. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global environmental change, 42, 153-168.


[4] “Federal Reserve Board announces that six of the nation’s largest banks will participate in a pilot climate scenario analysis exercise designed to enhance the ability of supervisors and firms to measure and manage climate-related financial risks”


[6] IEA (2021), World Energy Outlook 2021, IEA, Paris, License: CC BY 4.0

[7] The future is uncertain. The NGFS climate scenarios provide a window into different plausible futures.

[8], Page 14.

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About The Author

Josh Turner

Josh Turner

Product Manager, Data Product Management

Josh is a product manager with the data product management team, responsible for Climate on Demand and other physical climate change risk data products with Moody’s RMS.

He has been working in the physical climate risk space since 2016 with Moody’s and RMS, first developing models for risk assessment, and now within the product management organization.

Josh has a master’s degree in Climate and Society from Columbia University, and a bachelor’s degree in meteorology and applied mathematics from the University of Miami.

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