Established in December 2017, the Network for Greening the Financial System (NGFS) represents a consortium of central banks, financial institutions, and supervisors committed to enhancing the role and capability of the financial sector to identify, measure, and manage environmental, and climate-based risks; and to mobilize capital and financial investments to support the transition to a sustainable economy in alignment with the goals established in the Paris Climate Accord1. The NGFS serves as a voluntary platform to promote best practices and methods with respect to climate- and nature-risk management, and to devise standardized climate change stress tests and climate scenarios for use both within and outside of its membership. This article provides a primer on the climate scenarios developed by the NGFS.
The NGFS, in partnership with leading academic institutions,2 have developed six distinct climate scenarios that provide a global, harmonized, and common framework for quantifying the impacts of climate change to the economy and global financial system. These climate scenarios, listed below, represent a wide array of possible climate futures. A complete description of these scenarios can be found in the NGFS technical documentation.3
The NGFS categorizes climate scenarios into one of three transition types including Orderly, Disorderly, or Hot house world, based on the climate scenario narrative and modeled global response to climate change. NGFS climate scenarios span varying degrees of climate change mediated transition and physical risk. Table 1 provides a qualitative summary of high-level indicators of climate induced risk. For scenarios in the Orderly transition, the global response to climate action is immediate and coordinated, resulting in low variability in regional climate policies, a moderate-to-fast pace of technological change, and a modest deployment of Carbon Dioxide Removal (CDR4) technologies. These actions limit global warming to < 2 °C, and thus result in low physical risk and low-to-moderate transition risks. In the Disorderly transition, failure to coordinate climate policy across sectors and/or a delay to climate action may result in significant regional differences in climate mitigation and strategy, as well as periods of rapid technological change. Climate scenarios in the Disorderly case can limit warming to < 2 °C resulting in low physical risks but may demonstrate higher transition risks compared to the Orderly case. Scenarios in the Hot house world case reflect climate ambitions extrapolated from nationally determined contributions or current climate policies. For scenarios in the Hot house world case, global action on climate change is incremental and ultimately insufficient to limit significant global warming, resulting in >~2.5 °C+ by the end of the century. Hot house world scenarios demonstrate low transition risk but result in severe physical risks including irreversible impacts such as increases in global sea level.
Table 1. NGFS Climate Scenarios – Qualitative Macro-Financial Risk Assessment (adapted from Ref3)
Transition type | Climate scenario | Policy ambition | Policy reaction | Technology change | CDR | Regional policy variation |
---|---|---|---|---|---|---|
Orderly | Net zero 2050 | 1.5 °C | Immediate and smooth | Fast change | Medium use | Medium variation |
Below 2 °C | 1.7 °C | Immediate and smooth | Moderate change | Medium use | Low variation | |
Disorderly | Divergent net zero | 1.5 °C | Immediate but divergent | Fast change | Low use | Medium variation |
Delayed transition | 1.8 °C | Delayed | Slow/Fast change | Low use | High variation | |
Hot house world | Nationally determined contributions (NDCs) | ~2.5 °C | NDCs | Slow change | Low use | Low variation |
Current policies | 3 °C+ | None – current policies | Slow change | Low use | Low variation |
The NGFS evaluates each climate scenario independently across three separate Integrated Assessment Models (IAMs), see Table 2. IAM’s are a class of scientific computational modeling that captures interactions between human activities, society, economy, and earth systems. IAM’s rely on key assumptions regarding the future state of the world, which encompass policy, technological, and societal dimensions (such as policy targets, energy costs, population growth, etc.). These assumptions may be defined based on the climate scenario narrative (e.g., setting specific constraints on global warming), as well as exogenous and endogenous modeling assumptions. For each climate scenario, NGFS aligns the three IAMs to reflect consistent socioeconomic conditions and climate policy assumptions. However, IAM’s may differ in several key regards such as their model formulation, spatial and temporal resolution, sectoral granularity, technology representation, climate mitigation options, and other key variables (see Table 2), resulting in differences in climate outcomes across IAMs.
NGFS reports modeling results across unique combinations of IAM’s and climate scenarios, which enables stakeholders to explore model and scenario uncertainty by: (1) for a fixed climate scenario comparing climate outcomes across multiple IAMs, or (2) for a fixed IAM comparing climate outcomes across climate scenarios.
Table 2. Integrated Assessment Models used in constructing NGFS Climate Scenarios (adapted from Ref3)
Integrated Assessment Model | Global Change Analysis Model [GCAM] | MESSAGE + ix modeling platform /Global Biosphere Management Model [MESSAGEix-GLOBIOM] | Regional Model of Investment |
---|---|---|---|
Organization | University of Maryland (UMD) | International Institute for Applied | Potsdam Institute for Climate |
Solution concept | Partial equilibrium (price elastic demand) | General equilibrium (closed economy) | REMIND: General Equilibrium (closed economy) MAgPIE: Partial Equilibrium model of the agriculture sector |
Anticipation | Recursive dynamic (myopic) | Intertemporal (perfect foresight) | REMIND: Inter-temporal (perfect foresight) MAgPIE: recursive dynamic (myopic) |
Solution method | Cost minimization | Welfare maximization | REMIND: Welfare maximization MAgPIE: Cost minimization |
Spatial resolution | 32 World regions | 11 World regions | 12 World regions |
Temporal resolution | Base year: 2015 Time steps: 5 years Horizon: 2100 | Base year: 1990 Time steps: 5 (2005–2060) and 10 years (2060–2100) Horizon: 2100 | Base year: 2005 Time steps: 5 (2005–2060) and 10 years (2060–2100) Horizon: 2100 |
Technology representation | 58 Conversion technologies | 64 Conversion technologies | 50 Conversion technologies |
The number of mitigation | Demand side: 14 Supply side: 18 AFOLU5 options: 8 | Demand side: 16 Supply side: 20 AFOLU5 options: 8 | Demand side: 15 Supply side: 17 AFOLU5 options: 7 |
Climate scenario analysis is a powerful tool for quantifying and contextualizing the impact of human development and societal changes on the earth’s global climate system. As the drivers for climate change are deeply embedded in human-environmental systems, climate scenario analysis enables a broad comparison of climate outcomes across different ensembles of environmental, social, political, technological, economic, and cultural change. Moreover, climate scenario analysis can aid central banks and supervisors in understanding the long-term physical and transition risks to the economy and financial system across possible climate futures. To demonstrate the utility of this perspective, Figure 1 highlights the physical-transition risk tradeoff in NGFS climate scenarios at the end of the century (2100).
Figure 1. Climate-Mediated Transition and Physical Risk Tradeoff6
Figure 1. Climate-Mediated Transition and Physical Risk Tradeoff6
Here, global mean temperature (°C rel. to 1850–1900) and carbon price (US$2010/t CO2) are used as proxies for climate-mediated physical and transition risks, respectively. The evolution of the physical-transition risk tradeoff can guide and empower financial stakeholders in their investment decisions, portfolio management, and risk-management practices.
KPMG has extensive experience in climate scenario analysis and climate-stress testing as well as deep industry knowledge. Our risk consulting professionals can help you: