A
Acute risks: see physical risks
Adaptation: The process of adjusting natural or human systems in response to the actual and expected impacts of climate change, including extreme weather events, sea-level rise, and changes in ecosystems. Adaptation measures aim to reduce harm, improve resilience, and capitalise on beneficial opportunities, such as building sea walls to protect against floods and rising sea levels. We adjust the CER and CRR ratings based on companies’ resilience measures (see ClimaTech).
Aggregate damage function: see damage function
B
Benchmark: A quantitative or qualitative reference standard to compare an asset’s performance against a (selective) group of assets. In the context of the CER and CRR, we offer two types of benchmark comparisons:
Universe benchmark: A reference standard to compare an asset’s overall CER or CRR rating performance against all assets included in the CER or CRR infrastructure universe.
Peer Group benchmark: A reference standard to compare an asset’s overall CER or CRR rating performance against assets within the most similar asset group, considering their TICCS sector group and climate zone.
Basel Framework: A set of international banking regulations issued by the Basel Committee on Banking Supervision (BCBS) designed to ensure financial stability by setting standards for bank capital adequacy, stress testing, and market liquidity. It is structured around three mutually reinforcing pillars:
Pillar 1 ensures banks hold enough capital to cover core risks, specifically credit, market, and operational risks (minimum capital requirements).
Pillar 2 describes how to evaluate each bank’s internal risk management and ensures that banks hold capital in excess of the standard Pillar 1 minimums. This supervisory review pillar requires banks to follow an internal capital and liquidity assessment process (see ICAAP) and increasingly includes the evaluation of climate-related physical risks and transition risks. Our rating products provide quantitative metrics suitable for incorporation into Pillar 2 internal assessments and regulatory disclosures.
Pillar 3 mandates public disclosures so that investors, analysts, and customers can accurately evaluate a bank's risk profile and capital strength.
C
Carbon costs: We define carbon costs for an asset as the product of its Scope 1 and 2 carbon emissions and a country’s carbon tax, based on the country in which the asset operates.
Carbon emissions (CO2 equivalent): Emissions from all types of greenhouse gases (GHG; carbon dioxide, methane, nitrous oxide, and water vapour) that are generated by asset operations, expressed in terms of their equivalent amount of CO2 to generate the same global warming effect. Following the GHG Protocol standards, carbon emissions are divided into three scopes:
Scope 1 (S1) emissions: Direct carbon emissions, including emissions from facilities and vehicles owned by a company.
Scope 2 (S2) emissions: Indirect carbon emissions from purchased electricity, steam, heating or cooling, ventilation, and lighting.
Scope 3 (S3) emissions: Indirect carbon emissions from other sources, including upstream and downstream activities.
Upstream emissions encompass activities that occur before a product reaches the company’s operations, including raw material extraction, supplier production processes, and the transportation of inputs.
Downstream emissions occur after a product leaves the company and include emissions from its distribution, use, and disposal.
Carbon footprint: The total amount of carbon emissions generated by an asset’s operations. It is the sum of Scope 1, Scope 2, and Scope 3 emissions.
Carbon intensity: Provides insights into a company’s or sector’s carbon footprint. It is typically measured as the ratio of Scope 1 and 2 carbon emissions to an operation-related financial metric (e.g., production, revenues). In the context of the CER and CRR, we calculate carbon intensities per revenue in USD. For more details on this approach, refer to the technical documentation.
Carbon tax: The direct tax levied on an asset’s carbon emissions required to produce goods and services.
Cash Flow Available for Debt Service (CFADS): A key financial metric used primarily in project finance and infrastructure investments to assess a project’s ability to meet its debt obligations. CFADS represents the actual cash flow generated by a project that is available to service debt, including interest and principal repayments. CFADS excludes financing-related cash flows such as interest income, debt drawdowns, and repayments, making it a reliable indicator of a project’s underlying operating performance.
Chronic risks: see physical risks
ClimaTech: ClimaTech is a comprehensive initiative designed to assess and evaluate the effectiveness of infrastructure decarbonisation and resilience strategies in response to the increasing risks posed by climate change. The ClimaTech project distinguishes between decarbonisation and resilience strategies:
Decarbonisation strategies: These strategies aim to lower carbon footprints by employing technologies and practices that minimise the use of fossil fuels and enhance energy efficiency (e.g., integrating renewable energy sources or adopting low-carbon construction materials) to mitigate climate change.
Resilience strategies: These strategies ensure that infrastructure can withstand climate-related disruptions and continue functioning effectively in the face of extreme weather events (e.g., building flood defences, improving structural integrity, using fire-resistant building materials). Resilience is the main strategy to adapt to climate change.
We use the ClimaTech database to adjust the CER and CRR: If companies share their strategies, the database provides information on the extent to which our model-estimated carbon emissions, as well as expected damages and disruptions, can be reduced, and hence, the ratings adjusted.
Climate change (anthropogenic): A change of climate which is attributed directly or indirectly to human activity (including the burning of fossil fuels, deforestation, and industrial processes) that alters the composition of the global atmosphere. Anthropogenic climate change is distinct from natural climate variability and can be observed over long time periods.
Climate exposure: Exposure refers to the presence of assets that could be adversely affected by transition risks and physical risks from climate change. We measure and rate assets’ climate exposure in the CER. We understand “exposure” in a financial and strategic sense to demonstrate assets’ vulnerability and position to risk, which goes beyond their geographical presence (similar to market exposure, duration exposure, carbon exposure, etc.). Under this logic, the CER measures an asset’s exposure and vulnerability to climate forces before any financial modelling. This means, under our framework, a wooden and a concrete bridge at the same location would not be equally exposed to storms because we include vulnerability in the exposure concept.
Climate Exposure Rating (CER): A rating developed by Scientific Climate Ratings that reflects infrastructure companies’ sensitivity to present and future climate exposure. This measure of future climate exposure is provided for five time horizons – 2030, 2035, 2040, 2045, and 2050 – under eight climate scenarios and a probability-weighted expected scenario, and incorporates transition risks as well as physical risks. Compared to the Climate Risk Rating (CRR), it focuses on physical damages, operational disruptions, carbon costs, and market demand shifts, without a direct relation to companies’ cash flows and value. Accordingly, it represents an “exposure” rather than a “risk” rating. For more details on the CER, refer to the technical documentation.
Climate risks: Compared to climate exposure, climate risks describe the negative consequences resulting from an asset’s exposure and vulnerability to climate change. We measure and rate assets’ climate risks in the CRR, taking into account their financial materiality based on Net Asset Value.
Climate Risk Rating (CRR): A rating developed by Scientific Climate Ratings that reflects infrastructure companies’ sensitivity to present and future climate risks. This measure of future climate risks is provided for five time horizons – 2030, 2035, 2040, 2045, and 2050 – under eight climate scenarios and a probability-weighted expected scenario, and incorporates transition risks as well as physical risks. Compared to the Climate Exposure Rating (CER), it reflects the financial materiality of physical and transition risks on companies’ cash flows and value. Accordingly, it represents a “risk” rather than an “exposure” rating. For more details on the CRR, refer to the technical documentation.
Climate scenarios: Climate scenarios are projections of future climate change-influenced macroeconomic conditions, based on varying assumptions about greenhouse gas emissions, socioeconomic developments, and technological advancements. Climate scenario frameworks have evolved significantly over the past two decades. The Representative Concentration Pathways (RCPs) were among the first standardised scenarios developed at the request of the Intergovernmental Panel on Climate Change (IPCC) to explore the effects of varying greenhouse gas concentration trajectories on future climate conditions. These were subsequently integrated into the broader SSP-RCP framework, which pairs each physical hazard pathway (the RCP component) with a Shared Socioeconomic Pathway (SSP) describing the underlying socioeconomic conditions — such as population growth, economic development, and policy ambition — that give rise to those emissions. This combined framework was formally adopted in the Sixth Assessment Report (IPCC AR6) and is now the standard reference in climate risk literature. The Scientific Climate Scenarios developed by the EDHEC Climate Institute (ECI) align with this global framework. Overall, we follow the Network for Greening the Financial System (NGFS).
Climate scenario probabilities: As part of the Scientific Climate Scenarios framework, the EDHEC Climate Institute (ECI) has developed a methodology to calculate the probability of each climate scenario happening. In the CER and CRR, we provide the respective climate metrics also for an expected scenario, calculated as the weighted average of eight climate scenario projections (6 NGFS scenarios + 2 extended scenarios by ECI). For more details on this methodology, refer to the technical documentation.
Climate zone: The Köppen-Geiger climate classification categorises the world into five primary climate zones based on temperature and precipitation. Following Beck et al. (2018), we differentiate between tropical, arid, temperate, cold, and polar. Additionally, we consider a sixth category - offshore - to include the specific climate conditions at sea. We use climate zones to provide a more precise reference standard with our Peer Group benchmark.
Tropical: regions with temperatures above 18°C throughout the year and significant precipitation
Arid: regions with low precipitation that do not fit the polar criteria
Temperate: regions with a moderate climate with distinct seasons
Cold/continental:: regions with at least one month averaging below 0°C and at least one month averaging above 10°C
Polar: regions with a monthly average temperature below 10°C throughout the year
Offshore: oceans or large water bodies characterised by marine conditions that differ from adjacent land climates
Corporate Sustainability Reporting Directive (CSRD): An EU directive that significantly expands and strengthens sustainability reporting requirements for companies. It replaces the Non-Financial Reporting Directive (NFRD) and mandates detailed disclosures on environmental, social, and governance (ESG) issues, based on the European Sustainability Reporting Standards (ESRS). The CSRD aims to enhance transparency and comparability of sustainability information, enabling investors and other stakeholders to assess a company’s performance and related risks. It applies to large companies and listed Small and Medium Enterprises (SMEs), with phased implementation having started with the 2024 financial year.
Counterfactual baseline: A reference scenario in the Sovereign Climate Risk Rating against which all climate-induced impacts are measured. The scenario assumes no additional warming beyond the 2024 baseline. All projected impacts on Gross Regional Product (GRP) per capita are expressed as percentage deviations from this no-additional-warming counterfactual, not from current economic conditions.
Coupled Model Intercomparison Project Phase 6 (CMIP6): An internationally coordinated scientific exercise and leading global framework for climate modelling, managed by the World Climate Research Programme. It synthesises the work of over 100 climate models from 49 modelling groups worldwide to project future climate change and inform the Intergovernmental Panel on Climate Change (IPCC) reports. Across all our rating products, we use the open-access CMIP6 data from NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), which includes bias-corrected and spatially downscaled climate projections under the SSP-RCP climate scenario framework.
Cyclone: see storm
D
Damage: see expected damage
Damage factor: The output of a damage function, typically defined as a ratio of repair to replacement costs. Additionally, the damage factor can be interpreted as the extent of the damage to an asset. This is presented as the percentage of the asset damaged.
Damage function: A function that translates the magnitude of hazard events to quantifiable damage by factoring in an asset’s exposure and vulnerability to such hazard events.
Aggregate damage function: A specific damage function applied in the Sovereign Climate Risk Rating that links projected changes in Global Mean Temperature (GMT) to estimated macroeconomic impacts at the global, national, or regional level.
Database of Global Administrative Areas (GADM): An open geographic database that provides subnational administrative boundary shapefiles worldwide. GADM boundaries serve as the spatial reference for aggregating climate projections and economic data from gridded datasets (e.g., GLDAS, CMIP6) to the administrative region level.
Database of Subnational Economic Output (DOSE): A dataset developed by MCC-PIK (a collaboration between the Mercator Research Institute on Global Commons and Climate Change and the Potsdam Institute for Climate Impact Research) that provides harmonised historical Gross Regional Product (GRP) per capita records for sub-national regions across 166 countries, covering the period from the early 1970s to 2018. The Sovereign Climate Risk Rating uses DOSE as the primary macroeconomic data source in the econometric estimation of regional temperature-output response functions.
Data Quality Score (DQS): The DQS system is part of the methodology developed by the Partnership for Carbon Accounting Financials (PCAF) to assess the reliability and accuracy of carbon emissions data linked to financial assets. This scoring system is a central feature of PCAF’s approach to financed emissions accounting. The scores range from 1 to 5, with 1 indicating the highest quality of (reported) emissions data, while 5 represents estimated emissions based on generalised data or proxies. For more details on how Scientific Climate Ratings includes DQSs, refer to the technical documentation.
Discounted Cash Flow: A finance method used to value a security, project, company, or asset that incorporates the time value of money. The result is the Net Asset Value (NAV).
Disruption: Compared to expected damages, disruptions are interruptions of normal operations, services, and asset functioning that are directly caused by hazard events. The calculation of business-day disruption enables the evaluation of impacts on companies’ revenues in the event that their activities are disrupted by climate hazards that damage their assets. We consider both damage and disruption when calculating physical risks for the CER and CRR.
E
Emission Factor (EF): A modelling factor that expresses the amount of carbon emissions generated by an activity of a given technology, hence measured in reference to an operational variable. For example, the EF for a car represents the car’s emissions for a given amount of distance travelled, and the EF for a power plant specifies the plant’s emissions for a given amount of MWh of electricity produced.
European Sustainability Reporting Standards (ESRS): A comprehensive set of mandatory standards developed by the European Financial Reporting Advisory Group (EFRAG) under the Corporate Sustainability Reporting Directive (CSRD) to harmonises corporate sustainability disclosures across the EU. The ESRS covers topics such as climate change, biodiversity, social matters, and governance, ensuring consistency, comparability, and reliability of sustainability information.
EU Taxonomy for Sustainable Activities: A classification system established by the EU to define what qualifies as an environmentally sustainable economic activity. It aims to prevent greenwashing and helps investors, companies, and policymakers identify and compare green investments based on six environmental objectives, including climate change mitigation and adaptation.
Expected damage: A metric the EDHEC Climate Institute (ECI) developed for all physical hazards covered in our CER and CRR ratings. While the expected damage from floods, storms, and wildfires is calculated as the Physical Damage at Risk (PDaR), heat hazards (see thermal stress) focus on operational revenue loss due to impacts on workers’ productivity. We use these baseline metrics for our physical damage metrics, which we then translate into respective scores and ratings.
Expected scenario: A probability-weighted scenario that considers the likelihood of each climate scenario happening (see climate scenario probabilities). The EDHEC Climate Institute (ECI) calculates the probabilities as part of its Scientific Climate Scenarios framework. In the CER and CRR reports, we provide probability-weighted climate metrics under the expected scenario across five time horizons.
Exposure (to physical risks): The presence of infrastructure assets in places and settings that could be adversely affected by hazard events. Different from an asset’s vulnerability to physical risks. See climate exposure for details on how we measure exposure in the CER.
Extended climate scenarios: The NGFS climate scenarios span a broad range of transition pathways but underestimate global warming and physical risk-related impacts. As part of the Scientific Climate Scenarios framework, the EDHEC Climate Institute (ECI) has developed a methodology to extend the NGFS scenarios by two additional pathways aligned with the more adverse warming outcomes considered in the IPCC literature: Climate Destabilisation, reaching approximately 3.6°C by 2100, and Climate Breakdown, reaching approximately 4.4°C. For more details on this approach, refer to the technical documentation.
Extreme Value Analysis (EVA): A statistical approach to model and estimate the probability of hazard events and calculate return periods. It focuses on the tail ends of probability distributions to assess the likelihood and magnitude of events that lie outside typical observations.
F
Flood: A type of hazard event defined by the overflowing of the normal confines of a stream or other water body or the accumulation of water over areas that are normally not submerged. Different types of floods include fluvial, pluvial, and coastal floods. We include the exposure to and risks from floods in our CER and CRR ratings. For more details on this approach, refer to the technical documentation.
G
Geolocation: The process of identifying the geographic location of an object and associating it with geographic coordinates (e.g., in latitude and longitude).
Geospatial data: Data that relates to the geographic position and characteristics of features or phenomena on the Earth’s surface.
Geospatial transformation: This process refers to the cleaning, processing, and structuring of geospatial data for subsequent analysis.
Global Climate Models (GCMs): Also known as General Circulation Models, GCMs are numerical models and programmes that simulate the Earth’s climate system. They model interactions among the atmosphere, oceans, land surface, and ice, and are used to project future climate change under specified emissions scenarios.
Global Land Data Assimilation System (GLDAS): A NASA dataset providing spatially gridded land surface climate variables at a 0.25° spatial resolution, including historical temperature and precipitation.
Global Mean Temperature (GMT): The global average surface temperature is the combined average of near-surface air temperatures over land and sea-surface temperatures across the oceans. It is typically expressed as an anomaly relative to a pre-industrial reference period (1850–1900). GMT is the primary climate variable used in the NGFS framework to characterise the degree of warming associated with each climate scenario pathway.
Granularised climate scenarios: The NGFS climate scenarios span a broad range of transition pathways that project climate impacts at the country level. As part of the Scientific Climate Scenarios framework, the EDHEC Climate Institute (ECI) has developed a methodology to granularise climate impacts at the sector-country level. For more details on this approach, refer to the technical documentation.
Gridded Population of the World (GPW): A global, high-resolution set of geospatial data that models the distribution of human population on continuous, rectangular grids (pixels). Instead of relying on traditional borders, it converts census data into a standardised grid format, allowing users to analyse population metrics alongside geographic or environmental data.
Gross Regional Product (GRP): The total monetary value of all final goods and services produced within a specific geographic region over a given period. It acts as the local equivalent of a country’s Gross Domestic Product (GDP). We use the GRP as the primary economic output metric at the sub-national level in the Sovereign Climate Risk Rating.
H
Hazard event: A physical climate event or trend that may cause loss of life, injury, or other health impacts, as well as damage, loss, and disruption to property, infrastructure, livelihoods, service provision, ecosystems, and environmental resources. Floods and storms are among the most impactful types of hazard events.
Hazard map: A map that illuminates areas that are affected by or exposed to a particular hazard. They are typically made for natural hazards and contain hazard values.
Hazard value: These values contain measurements of hazard events (e.g., the depth of a flood).
Heat: see thermal stress
I
Infrastructure universe: The Unlisted Infrastructure Universe is a database of tracked assets that represent the fair value- and risk-adjusted performance of the unlisted infrastructure asset class. It includes more than 9,000 unique infrastructure companies across the 27 most active national markets for infrastructure investors to define an investible universe of private infrastructure companies. These companies have a minimum of USD 1 million in total asset book value, are privately owned, and can be categorised using the Infrastructure Company Classification Standard (TICCS).
Integrated Assessment Models (IAMs): A class of large-scale computational models that couple a macroeconomic core to representations of the energy system, land use, and the carbon cycle, under a stated set of climate-policy assumptions to generate climate scenarios. NGFS uses three IAMs – REMIND-MAgPIE, MESSAGEix-GLOBIOM, and GCAM – that primarily differ in their optimisation approach.
REMIND-MAgPIE and MESSAGEix-GLOBIOM perform intertemporal optimisation, identifying the least-cost transition pathway over the entire century while accounting for future climate constraints, technology developments, and policy choices. Here, MESSAGEix-GLOBIOM is particularly well-suited to analyse trade-offs between energy, agriculture, forests, biomass, and land use, making it especially relevant for assessing carbon removal and bioenergy pathways. In contrast, GCAM solves for cost-minimising decisions period by period through market equilibrium. As a result, REMIND-MAgPIE and MESSAGEix-GLOBIOM tend to produce globally optimal long-term pathways, whereas GCAM focuses on path-dependent transitions reflecting sequential decision-making.
Because these models represent decision-making differently, they can produce distinct transition pathways and, hence, different likelihood assessments of specific scenarios. The output of these IAMs is a rich, multi-decade dataset spanning emissions, temperature, gross domestic product (GDP), population, sector-level energy demand and supply, carbon prices, and other macro-financial variables, typically resolved at the regional level.
Intergovernmental Panel on Climate Change (IPCC): The body of the United Nations, made up of 195 member countries, that is responsible for assessing the science related to climate change. Every five to seven years, the IPCC releases massive Assessment Reports that are considered the global standard for climate science and serve as the foundation for global climate negotiations, such as the Paris Agreement. Our research follows IPCC’s assessments and guidelines.
Internal Capital Adequacy Assessment Process (ICAAP): An internal risk-governance framework mandated for banks to identify, measure, and manage all material risks (including climate risks) against their capital resources. It ensures that an institution has sufficient capital to survive severe economic stress. The process is legally enforced in the European Union under the Capital Requirements Directive (CRD IV), which is the regional legislative package that translates the global banking standards of the Basel Framework into binding European law.
International Financial Reporting Standards (IFRS): A globally recognised set of accounting standards designed to bring consistency, transparency, and comparability to financial reporting across countries. IFRS governs how companies prepare and disclose their financial statements. In 2021, IFRS launched the International Sustainability Standards Board (ISSB) to create a comprehensive global baseline for sustainability disclosures. These include IFRS S1 (general sustainability-related financial disclosures) and IFRS S2 (climate-related disclosures aligned with TCFD recommendations).
M
Magnitude (of hazard events): A hazard magnitude scale measures the strength of a hazard event, considering the natural forcing phenomena and the severity of the event. The physical risk methodology adopts the description of magnitude based on the probability of occurrence of hazard events, also known as return periods.
Market demand shift: We developed two market preference metrics for the CER and CRR ratings. These metrics serve as proxies for companies’ exposure to adverse risks arising from market preferences and demands and shifts in consumer behaviours and values.
Mitigation: Mitigation refers to efforts and actions that limit the impacts of climate change. Mitigation measures aim to reduce or prevent greenhouse gas emissions or enhance carbon sinks that help absorb and store carbon. We adjust the CER and CRR ratings based on companies’ decarbonisation measures (see ClimaTech), such as switching from coal to renewable energy sources.
Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC): A reduced-complexity climate model emulator used by the NGFS framework to derive Global Mean Temperature (GMT) anomaly projections across climate scenarios and IAMs. In the Sovereign Climate Risk Rating, MAGICC’s GMT outputs serve as the climate input to the aggregate damage function, enabling the translation of SSP-RCP-based regional damage estimates into NGFS-compatible projections.
Multi-Regional Input-Output (MRIO): An economic modelling technique that tracks the complex financial flows, trade interdependencies, and supply chains between different industries across various countries or regions. Because MRIO models describe how economic sectors across different countries purchase goods and services from one another, they represent upstream and downstream emissions (see carbon emissions) across global supply chains. The models allow for systematic and consistent Scope 3 emissions estimates. For more details on this approach, refer to the technical documentation.
N
NACE: The Nomenclature statistique des Activités économiques dans la Communauté Européenne (English: Statistical Classification of Economic Activities in the European Community) is an industry-standard classification system used in the European Union.
Network for Greening the Financial System (NGFS): A global network of central banks and financial supervisors committed to enhancing the role of the financial system in managing climate and environmental risks. Founded in 2017, NGFS shares research, guidance, and tools, such as >climate scenarios, to promote sustainable finance and risk management. The NGFS scenarios combine socioeconomic projections, energy system models, and climate outcomes and align with frameworks like the Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Overall, NGFS considers four main climate scenario categories:
Orderly Transition scenarios, including Low Demand, Net Zero 2050, and Below 2°C:
In these scenarios, immediate and coordinated climate policies are implemented, enabling the containment of physical risks while avoiding significant transition risks. These scenarios aim to reach net-zero emissions by 2050 to limit global warming.
Disorderly Transition scenario, namely Delayed Transition:
In this scenario, climate policies are not applied immediately. To compensate for the delay while maintaining the goal of mitigating global warming, carbon taxes are introduced as a shock, entailing high transition risks.
Too Little, Too Late scenario, namely Fragmented World:
In this scenario, governments not only delay climate policies but also introduce climate actions in an uncoordinated and insufficient manner, failing to limit both transition and physical risks.
Hot House World (No Transition), including Nationally Determined Contributions (NDCs) and Current Policies:
In these scenarios, climate policies remain mostly unchanged from their current state. Transition risks are low but come at the cost of significant physical risks.
O
Operational stress: see thermal stress
P
Panel fixed-effects ordinary least squares (OLS): A statistical method used to analyse panel data (data where multiple subjects are observed over multiple time periods). It uses OLS to establish relationships while isolating unobserved, time-invariant differences between the subjects. The Sovereign Climate Risk Rating uses this technique to identify the causal relationship between climate variables and regional economic growth. By including region-specific fixed effects, the model absorbs all time-invariant characteristics of each sub-national region, enabling the identification of climate impacts from plausibly exogenous within-region variation over time rather than from cross-sectional differences between regions, which would conflate climate with other structural factors.
Partnership for Carbon Accounting Financials (PCAF): A global initiative that provides a standardised methodology for financial institutions to measure and disclose the greenhouse gas emissions associated with their loans and investments. A key feature is PCAF’s focus on transparency and its Data Quality Score method, enabling institutions to disclose emissions with clarity about methodology and uncertainty. PCAF is widely adopted by banks, asset managers, and insurers and supports alignment with net-zero targets and climate-related disclosure frameworks (e.g., TCFD, IFRS).
Penn World Table (PWT): A widely used macroeconomic database that provides internationally comparable Gross Domestic Product (GDP), productivity, and price level data for 166 countries over the post-war period. The PWT serves as the national macroeconomic anchor for the DOSE sub-national dataset, ensuring consistency between Gross Regional Product (GRP) records and national accounts across countries and over time.
Physical Damage at Risk (PDaR): PDaR refers to the asset-level damage factor calculated during the modelling process. PDaR can be understood as the percentage of an asset’s area that is exposed and vulnerable to a hazard event.
Physical risks: Risks related to the physical and material impacts of climate change. Physical risks can be either acute or chronic, which can both disrupt supply chains, reduce asset values, and increase operational and maintenance costs for businesses and communities. In the context of the CER and CRR, we measure physical risks as the expected damages and disruptions caused by hazard events.
Acute risks: A type of physical risk referring to immediate, short-term hazard events, such as the increased severity of extreme weather events (e.g., floods, storms, or wildfires) that can cause sudden and significant damage to infrastructure assets and disrupt operations.
Chronic risks: A type of physical risk referring to long-term shifts in climate patterns, such as rising sea levels, increasing temperatures, and prolonged droughts, which can gradually affect asset values, operational costs, and overall economic stability.
Physical Value at Risk (PVaR): PVaR can be understood as the tangible value of an asset exposed and vulnerable to a hazard event. This is derived by multiplying the asset’s financial information, specifically its tangible asset value, by the Physical Damage at Risk (PDaR). The quantified PVaR is the dollar amount that needs to be repaired or replaced, considering all potential hazard events of a given magnitude in a year.
R
Reclassification: The process of taking input cell values and replacing them with new output cell values. The EDHEC Climate Institute (ECI) uses this process to transform the initial hazard maps, which provide information on the hazard value (e.g., flood depth for each raster band on the map), into hazard maps with damage factors to receive the level of damage in percent for each region and asset class.
Representative Concentration Pathways (RCPs): At the request of the IPCC, the scientific community developed the RCPs, one of the first scenarios to explore the impacts of (future) greenhouse gas concentrations in the atmosphere on the climate. These climate scenarios primarily focus on the expected radiative forcing values (i.e., the imbalance between the amount of energy that enters the Earth’s atmosphere from the sun and the amount of energy reflected into space) until 2100. However, the RCPs are nonspecific regarding the underlying socioeconomic conditions, as described by the Shared Socioeconomic Pathways (SSPs).
Reputation: see market demand shift
Return period: The return period is a statistical estimate of how often a specific hazard event of a given magnitude is likely to occur. This probability is expressed as an estimate of the average time interval between occurrences, typically expressed in years. For example, a 100-year flood has a return period of 100 years, which means that there is a 1 percent chance of such a flood occurring in any given year. To obtain return periods, the EDHEC Climate Institute (ECI) uses Extreme Value Analysis (EVA), which models the behaviour of extreme events to estimate the likelihood of occurrence.
Risk-Weighted Assets (RWA): A regulatory capital metric representing a bank’s assets weighted by their risk level, used to determine minimum capital requirements under the Basel Framework. Climate-stressed Gross Domestic Product (GDP) projections (as provided by the Sovereign Climate Risk Rating) can affect RWA calculations within banks’ internal models, particularly for sovereign bond portfolios in jurisdictions with material physical climate exposure.
S
Scenario probabilities: see climate scenario probabilities
Scientific Climate Scenarios: An advanced climate scenario framework developed by the EDHEC Climate Institute (ECI) to support forward-looking climate risk analysis, valuation, and investment decision-making. Building on existing NGFS climate scenarios, the framework enhances their usability for financial institutions and investors through three major innovations: granularised climate scenarios, extended climate scenarios, and climate scenario probabilities.
Scope 1, 2, and 3 emissions: see carbon emissions
S3-to-S1+2 ratio: This ratio is part of the approach to building Scope 3 (S3) carbon emission models. To estimate S3 emissions, the EDHEC Climate Institute (ECI) uses its Scope 1 and 2 (S1+2) emission estimates, combined with sector-specific S3-to-S1+2 ratios, assuming that emissions generally scale with activity levels. For more details on this approach, refer to the technical documentation.
Shared Socioeconomic Pathways (SSPs): Global climate scenarios used in climate modelling and impact assessment to explore how different trajectories of societal development affect greenhouse gas emissions (see carbon emissions) and climate risks. SSPs describe alternative futures based on mitigation and adaptation challenges, and are often combined with Representative Concentration Pathways (RCPs).
Shapefile: A widely used geospatial file format for storing and sharing vector-based geospatial data in Geographic Information Systems (GIS). Shapefiles contain information about geometric shapes (such as points, lines, or polygons) along with associated attribute data (e.g., names, population, land use).
Sovereign Climate Risk Rating (SovCRR): A rating developed by Scientific Climate Ratings that reflects sovereigns’ exposure to present and future climate risks. The rating is derived from econometrically estimated, probability-weighted expected macroeconomic impacts, enabling investors to price sovereign climate risk rather than merely rank it. Headline ratings are published under the expected scenario for two time horizons (2035 and 2050) across more than 3,400 regions, collectively covering 191 countries. Additionally, we provide scenario-specific ratings across all seven NGFS pathways plus 2 extended climate scenarios developed by the EDHEC Climate Institute (ECI). For more details on the SovCRR, refer to the technical documentation.
Storm: A type of hazard event referring to strong winds resulting from a low-pressure atmospheric system. Storms are among the most significant natural hazards, resulting in substantial global damage and major economic losses. Different types of storms include tropical cyclones and extratropical storms. Tropical cyclones are driven by warm ocean waters and generate extreme winds, storm surges, and heavy rainfall. In contrast, extratropical storms are more prevalent in mid-latitudes and can cause severe disruptions due to high winds, flooding, and snow. We include the exposure to and risks from storms in our CER and CRR ratings. For more details on this approach, refer to the technical documentation.
Supervisory Review and Evaluation Process (SREP): An annual in-depth assessment conducted by banking supervisors (such as the European Central Bank) to evaluate a bank’s risk profile, governance, and capital and liquidity adequacy. It ensures that individual institutions have robust strategies and resources to handle their specific risk exposures. SREP is the practical implementation of Pillar 2 of the Basel Framework. While the Basel Framework sets the international standards for risk and capital, ICAAP is the internal process banks use to meet those standards, and SREP is the supervisory process regulators use to evaluate banks’ efforts. From the 2026 cycle onward, SREP makes climate risk integration under Pillar 2 mandatory.
T
Task Force on Climate-Related Financial Disclosure (TCFD): An international initiative developed in 2015 by the Financial Stability Board to develop a framework for climate-related financial disclosures and improve transparency on climate-related financial risks. The TCFD recommends voluntary, but widely adopted, disclosures on governance, strategy, risk management, and metrics related to climate impacts on business. The TCFD fulfilled its remit and disbanded in 2023. The IFRS Foundation is now monitoring the progress of companies’ climate-related disclosures.
The Infrastructure Company Classification Standard (TICCS): A classification standard of infrastructure companies that provides investors with a frame of reference to approach the infrastructure asset class. It offers an alternative to investment categories inherited from the private equity and real estate universe, which are less informative when classifying infrastructure. For more details on this infrastructure standard, refer to Scientific Infra & Private Assets.
Thermal stress: Refers to the adverse impacts on living organisms and systems resulting from excessive temperature conditions, such as extreme cold or heat stress.
Extreme heat stress: A type of hazard event defined by heat wave periods that bring consistently abnormal high temperatures. Heat stress risk and its impact can be understood in three categories: direct physical damage (e.g., deformation of road surfaces), disruptions affecting supply chains, transportation networks, or energy systems, and operational issues. We focus our heat stress assessment on operational issues, where heat impacts workers’ chronic health and productivity. For more details on this approach, refer to the technical documentation.
Tangible asset value: The sum of the total replacement value of a company’s physical assets, including buildings, equipment, and infrastructure, while excluding intangible components such as financial assets, goodwill, patents, and market reputation.
Targeted Review of Internal Models (TRIM): A supervisory programme conducted by the European Central Bank (ECB) to assess whether Eurozone banks’ internal models used for regulatory capital calculation comply with applicable requirements. While it focuses primarily on risks covered in Pillar 1 of the Basel Framework, it increasingly integrates climate risks, as set out in Pillar 2.
Transfer function: A mathematical model that defines the relationship between a system’s input and output. In the first stage of the Sovereign Climate Risk Rating methodology, the transfer function uses global Gross Regional Product (GRP) per capita to define the estimated relationship between local climate fluctuations and regional economic growth. Based on this “stable manifold”, the function allows the relationship to be transferred to regions not included in the estimation sample and, hence, the extrapolation of damage estimates to more than 3,400 regions.
Transition risks: Transition risks refer to the financial risks arising from the shift towards a low-carbon economy. These include changes in policies and regulations that impact carbon costs, technological advancements, and consumer preferences and market dynamics that can impact assets’ and companies’ values and reputations. In the context of the CER and CRR, we measure transition risk as a combination of direct carbon costs and market demand shifts.
Transition scenarios: see climate scenarios
V
Vulnerability (to physical risks): The propensity or predisposition of an asset to be adversely affected by a hazard event. Different from an asset’s exposure to physical risks. See climate exposure for details on how we measure vulnerability in the CER.
W
Wet Bulb Globe Temperature (WBGT): The WBGT is a composite temperature metric that combines air temperature, humidity level, wind speed, and solar radiation to assess direct thermal stress for each day from 1990 to 2060. An increased WBGT corresponds directly to decreased productivity, and hence, it is a useful measure for workplace safety.
Wildfire: Also known as forest fires or bushfires, these uncontrolled and fast-spreading fires are a type of hazard event that occurs in vegetation, such as forests, grasslands, or shrublands. Wildfires are influenced by the “fire triangle”: fuel (i.e., dry vegetation), weather (heat, wind, low humidity), and ignition source. Wildfires are increasingly seen as both a hazard and a climate-related risk, with frequency and severity rising in many regions due to hotter, drier conditions, and changing land-use patterns. We include the exposure to and risks from wildfires in our CER and CRR ratings. For more details on this approach, refer to the technical documentation.
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Zonal statistics: An operation that calculates statistics on cell values of a raster within the zones defined by another dataset. This methodological step is crucial for accurately calculating the physical damage to assets within their boundaries.