Translating NGFS scenarios
Scenario variables are mapped to sector output, revenues and default probabilities, with each modelling choice documented.
GRA · Climate and Nature Financial Risk
Spatial financeWhere capital meets hazard, exposure and transition
Scenario design and stress testing for climate and nature financial risk
Scenario analysis tests how institutions would fare under climate and nature pathways that differ in policy, technology and physical outcomes. On this platform it is explained with attention to scenario design, translation into financial variables and the limits of each step.
01Register
Scenario design and stress testing for climate and nature financial risk on the record.
Method recordSTEM method
- MethodScenario design and stress testing
- StewardSystemic Risk Management
- Applied inClimate and Nature Financial Risk
- Data3 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What scenario design and stress testing does here.
Scenario design and stress testing construct plausible, severe future conditions to examine how systems and institutions would perform. They complement probabilistic analysis where data are scarce or futures are deeply uncertain. In climate and hazards, biodiversity and nature and capital markets and investment, stress tests reveal vulnerabilities that arise when several risks materialise together. They inform capital, contingency and coordination plans across sectors. The canonical description is on the STEM Commons.
Short-term climate scenarios
Shorter-horizon scenarios with acute shocks are used to examine near-term financial effects within planning horizons.
Dynamic balance sheets
Exercises allow institutions to respond over the scenario, revealing how management actions change their own outcomes and system effects.
03Scenario model
Transition and physical risk on a portfolio.
Three scenario families after the NGFS framework move a sector portfolio through carbon costs and warming damages; the transmission view follows the losses to lenders, investors, public finances and households. Scenario: named assumptions about the future, not a forecast.
Controls
- Carbon price at the horizon, orderly path
- 200 per tCO2
- Delay before a disorderly transition
- 50% of horizon
- Cost passed to customers
- 50%
- Warming today above pre-industrial
- 1.30°C
- Warming per decade, current policies
- 0.25°C
- Damage coefficient
- 0.24% per °C²
- Years ahead
- 25 years
Readouts
- Worst scenario at the horizon
- −33.6% of value
Numbers, methods and sources
| Year | Orderly transition (% value) | Delayed, disorderly transition (% value) | Current policies (% value) |
|---|---|---|---|
| 0 | −0.38 | −0.38 | −0.38 |
| 3 | −2.87 | −0.53 | −0.67 |
| 6 | −5.36 | −0.68 | −0.97 |
| 9 | −7.84 | −0.84 | −1.27 |
| 12 | −10.33 | −0.99 | −1.57 |
| 15 | −12.82 | −7.12 | −1.87 |
| 18 | −15.31 | −15.05 | −2.17 |
| 21 | −17.80 | −23.00 | −2.48 |
| 24 | −20.29 | −30.94 | −2.79 |
Methods
- Climate scenario families NGFS (2023), Climate Scenarios for central banks and supervisors, Phase IV
- Climate stress test of the financial system Battiston and others (2017), Nature Climate Change 7
- Damage function Nordhaus (2017), Revisiting the social cost of carbon, PNAS 114
- Transmission channels BCBS (2021), Climate-related risk drivers and their transmission channels
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
- Urban extents Natural Earth
- Seaports Natural Earth
- Past year, daily temperature (ERA5 via Open-Meteo) Open-Meteo.com (CC BY 4.0), Copernicus ERA5 (C3S/ECMWF) · register open-meteo.public-pages
- Surface air temperature, daytime (AIRS) NASA AIRS · register nasa.gibs.context-live-layers
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Climate and Nature Financial Risk in Foundry
- Tested at Climate and Nature Financial Risk in Universe
- Codified in Climate and Earth Systems in Standards
- Published in Climate and Nature Financial Risk in Reports
- Taught in Faculty of Earth and Environmental Sciences in Academy
04Data
What the method consumes.
Datasets and records used by scenario design and stress testing on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| NGFS scenarios | Pathways | MODELLED |
| Balance sheet data | Starting exposures | Published statistics |
| Sector models | Translation | MODELLED |
05Sector signature
Where exposure in scenario design and stress testing for climate and nature financial risk travels.
The sectors that carry exposure in scenario design and stress testing for climate and nature financial risk and how a loss in one passes to the others, across portfolios and public finances.
Select corners · hover lines6 / 15 relations
Signature
Biodiversity and its partners
Biodiversity gives pollination and soils to food (0.6), watershed regulation to water (0.5) and zoonotic spillover and medicines to health (0.4).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Food → Biodiversity · land conversion0.6
- Water → Food · irrigation0.8
- Water → Biodiversity · environmental flows0.6
- Food → Health · nutrition0.7
06Validation
How results are checked.
Scenarios are reviewed for plausibility, internal consistency and severity relative to history. Exercise outcomes are compared with actual events when they occur.
| Check | How it is done |
|---|---|
| Conditional framing | Results are presented as conditional, not forecasts |
| Model challenge | Translation models are reviewed independently |
| Sensitivity | Key assumptions are varied and reported |
Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.
07Exposure, loss and capital
What it means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Scenario pathways
How scenario design and stress testing for climate and nature financial risk could be stressed under the scenario families central banks and supervisors use.
| Scenario family | Transition risk | Physical risk | What a stress test asks |
|---|---|---|---|
| Orderly | Early, gradual policy | Lower | Can the book absorb a steady repricing? |
| Disorderly | Late, abrupt policy | Lower to medium | What breaks under a sudden repricing and credit migration? |
| Hot house world | Limited policy | High and rising | Where do physical losses concentrate in collateral and insurance? |
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
08Connections
Topics that rely on this method.
09Stewardship
Who maintains the method.
Systemic Risk Management stewards scenario design and stress testing for the Consortium and reviews how it is applied across platforms.
10Connected
Where this page leads across the Consortium.
11Questions
Questions and answers.
What are the limits of scenario design and stress testing in this field?
Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.
How are results checked?
Scenarios are reviewed for plausibility, internal consistency and severity relative to history. Exercise outcomes are compared with actual events when they occur.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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