Climate Scenario Analysis & Stress Testing
Climate change has become a significant source of financial risk, causing increased market volatility and financial sector instability. Structural changes in the economic and financial systems caused by climate change are also one of the important sources of financial risks, which could have a systemic, long-term impact on economic growth and financial stability, and may even trigger a systemic financial crisis. Hence, financial institutions urgently need to establish a climate risk management mechanism. Quantitative assessment of climate risks is the key step for financial institutions to manage climate risk. Due to climate risks' unique features, forward-looking climate scenario analysis and stress testing have become the main tools for climate risk assessment.
Scenario analysis refers to the method of evaluating a series of hypothetical outcomes by considering various possible future states (i.e., scenarios) given a specific set of assumptions and constraints. Scenario analysis is ideal for classifying risks that are complex and difficult to assess in the medium-long term or whose impact can last for an uncertainly long time.
STGF Climate Scenario Model
The climate scenarios provided in STGF's Carbon Emissions Trajectory Projection model can be mapped to the Intergovernmental Panel on Climate Change (IPCC)'s Shared Socioeconomic Pathways (SSP1-5) and Representative Concentration Pathways (RCP1.9, RCP2.6, RCP4.5, RCP6.0, RCP8.5), as well as scenarios launched by the Network for Greening the Financial System (NGFS). STGF provides 8 climate scenarios in total, which includes 1) Business-As-Usual case where there are no climate policies enacted, 2) Current Policies, 3) Nationally Determined Contributions (NDCs), 4) Divergent Net Zero, 5) Delayed Transitions, 6) Below 2°C Target, 7) Below 1.5°C Target, and 8) Global Common Carbon Tax scenarios. Scenario relationship map is shown as below:
Model Features
The model is built based on emissions forecast data projected by multiple global integrated assessment models (IAMs) and domestic authoritative emissions accounting dataset
Provides city- and sectoral-level emissions projections under different sets of socioeconomic and emissions target constraints, by simulating dynamic evolution processes of city-level energy use structure across different industrial sectors, the rate of reduction of carbon intensity and energy intensity, industrial concentration ratio, average annual change of emissions in the past five years, etc.
Provides yearly carbon emissions gap data by industrial sectors and cities to reflect the total emissions reduction required by each city and sector under different scenarios
Scenarios provided in this model can be mapped to shared socioeconomic pathways (SSPs) used in IPCC's Sixth Assessment Report and representative concentration pathways (RCPs) used in IPCC's Fifth Assessment Report
Provides China's carbon emissions projection data under a global common carbon tax policy scenario (at a low-price path)
Using big data and cloud computing technologies, the model provides online data computation and visualization for a user-specified climate scenario, year, city, and sector
Climate change has become a significant source of financial risk, causing increased market volatility and financial sector instability. Structural changes in the economic and financial systems caused by climate change are also one of the important sources of financial risks, which could have a systemic, long-term impact on economic growth and financial stability, and may even trigger a systemic financial crisis. Hence, financial institutions urgently need to establish a climate risk management mechanism. Quantitative assessment of climate risks is the key step for financial institutions to manage climate risk. Due to climate risks' unique features, forward-looking climate scenario analysis and stress testing have become the main tools for climate risk assessment.
Scenario analysis refers to the method of evaluating a series of hypothetical outcomes by considering various possible future states (i.e., scenarios) given a specific set of assumptions and constraints. Scenario analysis is ideal for classifying risks that are complex and difficult to assess in the medium-long term or whose impact can last for an uncertainly long time.
STGF Climate Scenario Model
The climate scenarios provided in STGF's Carbon Emissions Trajectory Projection model can be mapped to the Intergovernmental Panel on Climate Change (IPCC)'s Shared Socioeconomic Pathways (SSP1-5) and Representative Concentration Pathways (RCP1.9, RCP2.6, RCP4.5, RCP6.0, RCP8.5), as well as scenarios launched by the Network for Greening the Financial System (NGFS). STGF provides 8 climate scenarios in total, which includes 1) Business-As-Usual case where there are no climate policies enacted, 2) Current Policies, 3) Nationally Determined Contributions (NDCs), 4) Divergent Net Zero, 5) Delayed Transitions, 6) Below 2°C Target, 7) Below 1.5°C Target, and 8) Global Common Carbon Tax scenarios. Scenario relationship map is shown as below:
| STGF Scenarios | NGFS Scenarios | Warming Target | SSP Scenarios | RCP Scenarios |
| Baseline | - | 4°C+ | SSP5 | RCP8.5 |
| Current Policies | Hot House World -Current Policies | 3°C+ | SSP4 | RCP6.0 |
| Nationally Determined Contributions | Hot House World-Nationally Determined Contributions | ～2.5°C | SSP2 | RCP4.5 |
| Divergent Net Zero | Disorderly - Divergent Net Zero | 1.5°C | SSP2 | RCP1.9 |
| Delayed Transitions | Disorderly - Delayed Transitions | 2°C | SSP2 | RCP2.6 |
| Below 2°C Target | Orderly - Below 2°C Target | 2°C | SSP1 | RCP2.6 |
| Below 1.5°C Target | Orderly - Below 1.5°C Target | 1.5°C | SSP1 | RCP1.9 |
| Global Common Carbon Tax | - | 1.5°C | SSP1 | RCP1.9 |
Model Features
The model is built based on emissions forecast data projected by multiple global integrated assessment models (IAMs) and domestic authoritative emissions accounting dataset
Provides city- and sectoral-level emissions projections under different sets of socioeconomic and emissions target constraints, by simulating dynamic evolution processes of city-level energy use structure across different industrial sectors, the rate of reduction of carbon intensity and energy intensity, industrial concentration ratio, average annual change of emissions in the past five years, etc.
Provides yearly carbon emissions gap data by industrial sectors and cities to reflect the total emissions reduction required by each city and sector under different scenarios
Scenarios provided in this model can be mapped to shared socioeconomic pathways (SSPs) used in IPCC's Sixth Assessment Report and representative concentration pathways (RCPs) used in IPCC's Fifth Assessment Report
Provides China's carbon emissions projection data under a global common carbon tax policy scenario (at a low-price path)
Using big data and cloud computing technologies, the model provides online data computation and visualization for a user-specified climate scenario, year, city, and sector
1 The NDC Scenario assumes that the current emissions reduction goals stated in China's NDC plans will be fully implemented. Because the underlying integrated assessment models update their data every five years, this scenario reflects China's reduction target announced back in 2015, that is, emissions peak around 2030 and strives to reach the peak as soon as possible. However, China updated its target in September 2020, which aims to peak by 2030, and achieve carbon neutrality by 2060. These "double carbon reduction goals" are not yet reflected in this scenario.
2 Divergent Net Zero scenario means that warming will be controlled below 1.5°C by 2100, but the transition risk is higher than the orderly Below 1.5°C scenario. Characteristics of disordered emissions path may change in speed and magnitude over time, driven by policy delays, uncoordinated or disjointed policy implementations, unanticipated technological changes or disruptions, or market or social changes due to climate change.
3 Delayed Transitions scenario assumes new climate policies are not introduced until 2030. Strong policies such as carbon taxes and cap-and-trade systems are then introduced to limit warming to below 2 °C.
4 Global Common Carbon Tax scenario assumes that every country in the world begins to levy a carbon tax at the same level for all economic activities. This carbon tax will increase over time, from $21 in 13 years to $128 per ton of CO2 in 2050.
2 Divergent Net Zero scenario means that warming will be controlled below 1.5°C by 2100, but the transition risk is higher than the orderly Below 1.5°C scenario. Characteristics of disordered emissions path may change in speed and magnitude over time, driven by policy delays, uncoordinated or disjointed policy implementations, unanticipated technological changes or disruptions, or market or social changes due to climate change.
3 Delayed Transitions scenario assumes new climate policies are not introduced until 2030. Strong policies such as carbon taxes and cap-and-trade systems are then introduced to limit warming to below 2 °C.
4 Global Common Carbon Tax scenario assumes that every country in the world begins to levy a carbon tax at the same level for all economic activities. This carbon tax will increase over time, from $21 in 13 years to $128 per ton of CO2 in 2050.