FAQs
A list of our frequently asked questions.
Jump to FAQ section
What is a hazard?
FAQs about hazard coverage, types, and granularity.
What models does XDI use?
FAQs about model coverage, types, and granularity.
What RCPs?
More information about the IPCC RCPs and how XDI uses them.
What about NGFS?
More information about NGFS.
Climate Risk Engines
Developed by scientists, engineers and climate risk experts, this was the first time the cost of physical climate risk had been quantified in this way.
Glossary and other
Definitions of commonly used terms, as well as other FAQs
Hazards FAQs
Learn more about the hazards XDI covers
XDI provides global coverage for all hazards, with some variation in coverage resolution existing depending on the underlying datasets. While the hazard coverage is global, some hazards pose no risk in certain areas. For example, there are no tropical cyclones in Switzerland.
There are instances where some metrics do not apply.
For example, heat wave events (Extreme Heat hazard) don’t cause physical damage to assets, so the Maximum to date Value at Risk (MVAR%) will be zero while the Failure Probability (FP%) may have results.
XDI assesses 10 climate risk hazards, each with its own level of granularity, typically ranging from 5 to 50 metres.
Although climate change is generally anticipated to cause an increase in hazard risk to certain regions, the change in risk will vary by location and by hazard. Not everywhere is anticipated to have an increase in hazard risk due to climate change - for example, some places might actually experience a reduction in temperature compared to the start of the century due to changes in the ocean currents and prevailing winds.
Our award-winning Climate Risk Engines have been stress tested and reviewed by clients and subject matter experts over a 15 year development period. The development of an external peer review process is underway which will include a scientific review panel comprised of academic experts.
Hurricane & Tropical Cyclone, Extreme Wind, Coastal Inundation, Forest Fire, Fluvial Flood, Pluvial Flood, Extreme Heat, Soil Movement, Freeze-Thaw Cycle. Both Landslip & Storm Surge are in development.
The Climate Risk Group’s science team is continually adding new hazards to our analysis. We prioritise those that have the greatest impact on people, business and finance, and the widest application. We currently offer analysis using nine hazards, including pluvial, fluvial and coastal flooding, extreme heat and extreme wind, with three more soon to be added.
Climate change influences a range of physical processes and these impact on people and businesses in different ways. The Taskforce on Climate-related Financial Disclosures (TCFD) divides physical risks into "acute" event driven risks, like storms, floods and wildfires and "chronic" risks associated with long term shifts and state changes in the climate, like heat and sea-level rise.. The TCFD did not specify a list of hazards associated with these risks, but the IPCC's Sixth Assessment Report summarises 33 "climate impact drivers" and their relevance for different natural and human assets, such as extreme heat, heavy precipitation, relative sea level, and hydrological, agricultural and ecological drought. The EU Taxonomy on sustainable activities similarly classifies 27 climate change hazards. Not all of these hazards are material for all analysis.
Models FAQs
Learn more about the models XDI uses
Elevations come from from multiple national digital elevation model (DEM) datasets.
We offer annual, 5-year or 10-year increments from 1990 to 2100.
We do not currently include biodiversity in our analysis, however it is included in some capacity in our two-year roadmap for science and technology developments. If you wish to partner with XDI in developing metrics around biodiversity, please contact us.
The Climate Risk Group uses climate models most suitable to each hazard analysed, these are typically not able to be interchanged.
Flexibility in our analyses can be provided by using different archetypes, return frequencies and climate scenarios.
A baseline flood climatology is obtained from flood model providers, to which the projected change in maximum annual daily rainfall is used to scale this flood climatology into the future.
There are many different types of wind, including synoptic (on a relatively large spatial scale), tropical cyclone (intense tropical low pressure systems), convective wind (related to thunderstorms and large showers), and tornadoes.
Currently, our system includes synoptic wind and tropical cyclone winds, with convective thunderstorm-produced wind coming soon.
Elevations come from from multiple national digital elevation model (DEM) datasets.
Information about each dataset that is used in our analysis is copied through to the end of the analysis.
The climate projections we use come from the CORDEX downscaling project. Which takes global climate models and simulates these at a higher reoslution over each region of the world. These downscaled projections have an approximately 50km resolution. For some regions we will have much higher resolution data because there have been projects that have produced finer scale modelling (e.g. over southeast Australia there is data at 10 km resolution).
Projections of the annual maximum of the 24 hour maximum temperature are used to assess how extreme heat changes into the future.
Hazard data:
Annual cumulative precipitation
Context data:
Pluvial flood maps (baseline) with severity and return frequency
Often referred to as depth grids.
Coastal inundation is modelled taking into consideration the following climate and hazard metrics:
- Sea level rise projections
- Global tidal gauge data (real and synthetic)
And then combining those with the following context data:
- Digital elevation model
- Astronomic tides model
- Recorded tide gauge data
- Tectonic land movement data
- Storm surge and wave set-up model
Tropical Cyclone/Hurricane winds are currently modelled using a relationship between their wind speeds and the sea surface temperature, with a degradation in wind speed as you move further inland due to the effects of land surfaces on Tropical Cyclone intensity.
Most third party global flood maps use a generalised assumption that any areas classified as ‘urban’ can accommodate the 5-year rainfall volume in storm drains before flooding occurs. The rainfall amount that is calculated as having a 5-year return period is therefore removed from rainfall totals (i.e. those calculated for the 20, 50, 100, 200, 500 and 1500-year return periods) before hydraulic models are run.
There are two exceptions that have used different urban drainage assumptions, the US and Canada.
XDI has the capability to analyse the risk of the physical impacts from climate change to the built environment at a global scale. Sovereign risk analysis is based on an archetype-driven gridded risk profile of the global built environment combined with climate change and extreme weather models. Sovereign risk analysis can be aggregated to the city, province or country scale.
Coverage rates vary per company and sector. If there is a specific request for coverage of companies or company groups, please share them with us and we can assess suitability or current coverage from our proprietary company database.
Data is regularly reviewed and generally updated in our system once these updates become available and have been evaluated.
Location-specific flood data is generally updated several times a year.
Climate data is generally updated as
(a) new Coupled Model Inter-comparison (CMIP) models are released, and
(b) as downscaling is created by global research teams to the accuracy required for use by our Climate Risk Engines.
All data sets got through quality assurance (QA) tests - sample QA reports are agreed at the time of contracting.
XDI analysis works to identify the edge of the risk envelope, so that decision makers can see the maximum modelled risk. To stress-test an asset, multiple climate models are tested and the model that appears to create the greatest increase in a particular hazard is selected for that hazard.
RCPs FAQs
Learn more about the RCPs XDI covers
Outputs for Representative Concentration Pathway (RCP) 8.5, 6.0, 4.5 and 2.6 are available as standard.
As a standard of practice for physical risk analysis from extreme weather and climate change events, RCP 8.5 is used to stress test assets or portfolios under a worst-case emissions scenario. RCP 2.6 is used for 'best' case scenario. RCP 4.5/6.0 can be added for a moderate mitigation pathway.
RCP stands for Representative Concentration Pathway. Scenarios that include time series of emissons and concentrations of the full suite of greenhouse gases (GHGs) and aerosols and chemically active gases, as well as land use/land cover (Moss et al., 2008). The word representative signifies that each RCP provides only one of many possible scenarios that would lead to the specific radiative forcing characteristics. The term pathway emphasises that not only the long-term concentration levels are of interest, but also the trajectory taken over time to reach that outcome (Moss et al., 2010).
We do not perform our own downscaling of global climate models. Currently, the majority of our models use data from the coordinated regional downscaling experiment (CORDEX). This simulation data uses CMIP5 projection data, which is a global projection based on the RCP scenarios, and downscales them to individual regions such as North America, Europe or Australia.
Newer hazard models use CMIP6 data, which is the updated version of CMIP5 that uses shared socio-economic pathways (SSPs) as scenarios, which are similar to the RCPs for physical risk (though some additional SSPs exist). There currently is no version of CORDEX that downscales the CMIP6 data set.
XDI aims to ensure that the full extreme weather and climate change risk space has been properly explored. Practically this means selecting high emission pathways and testing hazards using the individual regional models which most exacerbate each hazard.
By default, XDI uses RCP8.5 as the reference scenario most appropriate for ‘stress testing’ a portfolio. RCP8.5 provides concentration of greenhouse gases that cause global warming temperature increase of between 3.2°C to 5.4°C by the end of 2100, relative to pre-industrial temperatures. Current emissions most closely follow RCP8.5 and it is sometimes referred to as Business-as-Usual as it assumes high growth without significant decarbonisation of the economy.
Other emission pathways will generally result in impacts that are slower to occur or less severe. Therefore, derived impacts for RCP2.6 are mapped from RCP8.5 based on global heat projection differences in the IPCC Fifth Assessment Report.
NGFS FAQs
Learn more about XDIs approact to NGFS
The Network of Central Banks and Supervisors for Greening the Financial System (NGFS), launced at the Paris One Planet Summit on 12 December 2017, is a group of Central Banks and Supervisors willings, on a voluntary basis, to share best practices and contribute to the development of environment and climate risk management in the financial sector and to mobilize mainstream finance to support the transition toward a sustainable economy. (From the NGFS website).
XDI RCP8.5 aligns with NGFS Current Policies (high range)
XDI RCP6.0 aligns with NGFS Current Policies (median)
XDI RCP4.5 aligns with NGFS Delayed Transition
XDI RCP2.6 aligns with NGFS Net Zero 2050
Climate Risk Engines FAQs
Learn more about the world renowned Climate Risk Engines from XDI
XDI can provide risk assessments at multiple levels of aggregation. Group-level aggregation is not a standard output but if required we are able to provide this level of detail.
XDI has over 130 different archetypes. For residential properties, we have seven archetypes ranging from free-standing single dwellings to high-rise residential buildings.
For some hazards, climate projections are used to modify much higher resolution context data. For example, we use high resolution flood data to analyse flood, and coarser resolution climate projection data to adjust this to account for climate change.
Climate Risk Engines extract dynamically downscaled global and regional climate change models and combine these with global and local data sets, applying bespoke probabilistic algorithms to produce decision-ready financial and risk metrics.
Climate Risk Engines use engineering-based methods to assess exposure and vulnerability of asset archetypes to understand the likely damage and failure probability of assets caused by extreme weather and climate change hazards.
The coverage is global, granular, sophisticated and under constant improvement.Results are expressed in a range of engineering or financial metrics to inform decision-making at all scales.
To compute the cost of climate change risks so that the financial consequences of rising greenhouse emissions could be understood.
Climate Risk Engines were created in 2011. Developed by scientists, engineers and climate risk experts, this was the first time the cost of physical climate risk had been quantified in this way.Today, Climate Risk Engines are one of the most flexible, powerful and trusted sources of physical climate risk data in the world.
Climate Risk Engines uses Coordinated Regional Downscaling Experiment (CORDEX) model to generate baseline 1990 flood projections.
While we are able to share these information, more specifics are considered commercially sensitive intellectual property. Please ask a company representative for further information.
Glossary FAQs
Get an insight into what the different terms mean
RCP stands for Representative Concentration Pathways.
Scenarios that include time series of emissions and concentrations of the full suite of greenhouse gases (GHGs) and aerosols and chemically active gases, as well as land use/land cover (Moss et al., 2008).
The word representative signifies that each RCP provides only one of many possible scenarios that would lead to the specific radiative forcing characteristics. The term pathway emphasises that not only the long-term concentration levels are of interest, but also the trajectory taken over time to reach that outcome (Moss et al., 2010).
RCPs usually refer to the portion of the concentration pathway extending up to 2100, for which Integrated Assessment Models produced corresponding emission scenarios.
Extended Concentration Pathways (ECPs) describe extensions of the RCPs from 2100 to 2500 that were calculated using simple rules generated by stakeholder consultations, and do not represent fully consistent scenarios.
Four RCPs produced from Integrated Assessment Models were selected from the published literature and are used in the Fifth IPCC Assessment as a basis for the climate predictions and projections presented in WGI AR5 Chapters 11 to 14:
RCP2.6 One pathway where radiative forcing peaks at approximately 3 W m-2 before 2100 and then declines (the corresponding ECP assuming constant emissions after 2100);
RCP4.5 and RCP6.0 Two intermediate stabilisation pathways in which radiative forcing is stabilised at approximately 4.5 W m-2 and 6.0 W m-2 after 2100 (the corresponding ECPs assuming constant concentrations after 2150);
RCP8.5 One high pathway for which radiative forcing reaches greater than 8.5 W m-2 by 2100 and continues to rise for some amount of time (the corresponding ECP assuming constant emissions after 2100 and constant concentrations after 2250).
The Technical Insurance Premium (TIP) is defined as the Annual Average Loss (AAL) per representative property for all hazard impacts combined. The TIP is based on the cost of damage to a property, expressed in current day dollars with no discounting or adjustments for other transaction costs.
Actual insurance premiums may not include the hazards we cover - for example Coastal Inundation and Soil Movement are excluded in some countries.
Yes, we can present resultsets for the physical risk component of a TCFD report. We also produce a TCFD physical risk report.
No, the IPCC reports are a summary of climate science research to date. We are working on integrating CMIP6 data (the data underlying much of this climate science research) into our system. However, the results from this update are broadly unlikely to cause any major changes in our results.
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