GRA · Climate and Nature Financial Risk
Spatial financeWhere capital meets hazard, exposure and transition
Physical climate risk
Physical climate risk is the financial risk from climate hazards: acute events such as floods, storms and wildfire, and chronic shifts such as heat, drought and sea level rise. It reaches finance through damaged collateral, interrupted operations, falling property values and rising insurance costs. This page sets out how physical risk transmits to financial institutions, how it is measured, and who decides.
Physical climate risk in seven parts.
- 01The questionPhysical climate risk: how the risk develops
- 02IndicatorsWhat is measured, and how well
- 03SourcesWhere the evidence comes from
- 04DecisionsWho decides, and what the evidence serves
- 05Core questionsWhat risk modellers ask
- 06MechanismsFrom hazard to financial loss
- 07Methods and dataHow exposure is assessed, with limits
Physical climate risk: how the risk develops.
Direct and indirect asset exposures. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Collateral loses value
Property in flood zones or exposed coasts can lose value as damage, insurance costs and buyer awareness rise. Mortgages and real estate loans secured on it carry higher loss given default.
Operations and supply chains break
Heat, flood and drought interrupt production, logistics and labour. Firms' revenues and ability to repay fall, often at suppliers far from the hazard.
Insurance retreats
Rising losses push premiums up and capacity out. Uninsured assets transfer losses to owners and lenders and can lower property values further.
Losses correlate regionally
A lender concentrated in one region suffers many borrower losses at once. Regional banks and local governments are most exposed.
Assets on the grid, and the portfolio they make.
Where a portfolio's assets sit, and how much of its value is most exposed. Hypothetical assets, not an assessment.
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Loan exposure to high physical risk areas | currency and share of portfolio | annual | Bank disclosures and supervisory data | DECLARED |
| Collateral in flood zones | share of mortgage collateral value | annual | Bank data with hazard maps | MODELLED |
| Expected annual damage to portfolio assets | currency per year | per assessment | Physical risk models | MODELLED |
| Insurance coverage of collateral | share insured against relevant perils | periodic | Bank and insurer data | REPORTED |
| Physical risk score by asset | score from vendor or internal model | annual | Physical risk providers | MODELLED |
| Economic losses from climate-related disasters | currency | annual | Disaster loss databases | ESTIMATED |
Climate scenario analysis.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Climate scenario analysis
Physical climate risk · Bank loan book · Exercise 3
Scenario pipeline
- Select scenariosorderly · disorderly · hot house
- Pathwayscarbon price · GDP
- Sector impactsmargins
- Physical hazardsassets
- Credit parametersPD · LGD
- Portfolio losscapital
- Discloselimits
PD uplift by sector and scenario
basis points, illustrative
Expected loss path
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| ECB climate-related indicators | Experimental physical risk indicators for euro area financial exposures | Free, ECB terms |
| NGFS climate scenarios physical risk data | Chronic and acute physical risk damage functions | Free, NGFS terms |
| Copernicus Climate Data Store | Climate projections and indicators | Free and open, Copernicus licence |
| First Street Foundation and similar property-level hazard data | Property-level flood, fire and heat risk scores | Proprietary, terms to check |
| EIOPA and ECB reports on climate physical risk | Analysis of physical risk in EU insurance and banking | Free, EU reuse terms |
| FEMA National Risk Index | County-level natural hazard risk in the United States | Public domain |
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. The map on this page shows Southeast Asia; the model itself is not tied to a place.
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
Who decides, and what the evidence serves.
Climate and Nature Financial Risk prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Bank credit risk committees | Whether to adjust lending, pricing or collateral valuation for physical risk | Exposure, hazard and insurance evidence with sources |
| Prudential supervisors | Whether physical risk is adequately managed and capitalised | Supervisory data, scenario results and model reviews |
| Insurers | Whether to continue writing cover in high-hazard areas | Hazard trends and loss experience |
| Investors | How physical risk affects asset values in portfolios | Physical risk data with uncertainty |
Outputs this topic produces
- Guide to physical risk transmission channels for banks, insurers and investors
- Method note on linking hazard maps to collateral data
- Brief on reading vendor physical risk scores
- Questions for boards on regional concentration
Trace a shock in physical climate risk to the balance sheet.
Assembled from the Nexus Standards area profile Climate risk standards: the shocks it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Pick an initiating shock and step through the cascade to see which exposures it reaches and where losses could concentrate. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise, not a forecast, a valuation, a rating or investment advice. To model a place of your own choosing, open the full System Builder.
Hazards
- Sea-level rise
- Coastal flood (set off downstream)
- Storm surge (set off downstream)
- High-tide flooding (set off downstream)
- Coastal erosion (set off downstream)
- Saltwater intrusion (set off downstream)
- Estuary flood (set off downstream)
- Coastal habitat squeeze (set off downstream)
- Wetland loss (set off downstream)
- Mangrove loss (set off downstream)
- Groundwater flood (set off downstream)
- Climate-driven migration and relocation (set off downstream)
- Mass displacement (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-3bDataset and product metadata profile (STAC, DCAT, PROV-O)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H62Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)NRS-H71Hazard family: Deep-time and cosmic catastrophes (NHS-1 planet.deep-time)NRS-H79Hazard family: Mental health crises (NHS-1 health.mental)NRS-H75Hazard family: Climate-sensitive illness (NHS-1 health.climate-sensitive)NRS-H7Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)
Observation
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- CMIP6 climate projections (Copernicus Climate Data Store) (listed for reference)
- NGFS Scenario Explorer (listed for reference)
- INFORM Risk Index (listed for reference)
- Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population
- Total greenhouse gas emissions per year
- Direct economic loss attributed to disasters in relation to global GDP
Example geography
- Pacific Island states: 150 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
What risk modellers ask.
- Which assets are exposed to which hazards, and how vulnerable are they?
- How will hazard frequency and severity change over the relevant horizon?
- How do indirect effects, through suppliers, customers and infrastructure, add to direct damage?
- How do exposures concentrate across portfolios and institutions?
What physical climate risk 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 physical climate 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? |
From hazard to financial loss.
Risk is commonly expressed as the combination of hazard, exposure and vulnerability. A flood of a given depth causes damage that depends on building type, elevation and protection. Damage becomes insurance claims, repair costs, lost revenue and, for borrowers, reduced ability to repay. Chronic changes erode value more slowly, for example as heat lowers labour productivity or rising seas raise the cost of protecting coastal property.
Indirect effects can exceed direct damage. A factory may be undamaged but unable to operate because a supplier, port or power plant is. Many institutions underestimate these effects because they are hard to trace.
How exposure is assessed, with limits.
- 01
Catastrophe and hazard models
Probabilistic models of events and damage, informed by climate and atmospheric science. Many were built for current climate and need adjustment for change.
- 02
Geospatial exposure mapping
Linking asset locations to hazard maps, using spatial statistics and geostatistics. Asset locations are often imprecise. See Model and measurement gaps.
- 03
Damage functions
Relating hazard intensity to damage. Functions are uncertain and vary by region and asset type.
- 04
Supply-chain analysis
Tracing indirect exposure through suppliers and infrastructure. Supply-chain data are incomplete.
How it is studied, and what the methods cannot say.
- 01Climate and atmospheric scienceHazard projections for portfolios · Tail and compound hazards · Scenario physical variablesApplied here
- 02Spatial statistics and geostatisticsGeolocating exposures · Aggregating location risk · Resolution sensitivityApplied here
- 03Financial economics and macro-financeCredit risk transmission · Market pricing studies · Cross-sector transmissionApplied here
- 04Scenario design and stress testingTranslating NGFS scenarios · Short-term climate scenarios · Dynamic balance sheetsApplied here
Questions and answers.
What is the difference between acute and chronic physical risk?
Why do physical risk scores disagree?
How does physical risk affect a mortgage?
Why are indirect effects important?
Does the platform map individual firms' assets?
Can historical losses guide future risk?
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