How it works

CLIMATIG uses data from different climate models for multiple scenarios (RCP4.5, RCP 8.5), satellite data and historical data to create its own climate risk prediction models for all hazards and calculate the costs that will arise due to climate change.

We create our own datasets using high-computing machine learning to train models using user-generated data sources on the historical course of events at micro-locations.

All climate risks calculated by CLIMATIG are assessed at a high resolution of 10 meters, providing exceptionally detailed insights into the potential impacts on assets. Additionally, the temporal resolution is on an annual basis, ensuring that users receive comprehensive and reliable data for their climate risk assessments.

In order to calculate physical climate risks, the results of climate models are used for the selected scenario (RCP4.5 or RCP8.5). Variables such as the total daily amount of precipitation, mean, minimum and maximum daily temperature, relative humidity, etc. were obtained from these climate models for the selected time period. Various climate indices which give us information about the frequency, length or magnitude of an extreme event are then calculated. In addition to climate models, data from satellites were also used. For example, we get information about the distance of the asset from the forest, river or sea, or the type of soil from satellite data.


The CLIMATIG Score (CS) is a composite risk index calculated for each individual hazard. It includes the data on specific climate variables and the asset location information. CLIMATIG Score accounts for the hazard as well as the vulnerability and exposure of the asset to that hazard.

Climatig Score values are between 0 and 100, where 0 indicates minimum risk and 100 maximum risk.

The Asset CLIMATIG Score (CS) is calculated according to the CLIMATIG Scores for each individual hazard. MAX CS is the maximum hazard CLIMATIG Score for the chosen asset, MIN Asset CS is the minimum hazard CLIMATIG Score for the chosen asset, and AVG CS is the average value of the hazards’ CLIMATIG Scores for the chosen asset.

Overall Portfolio Climatig Score (CS) represents the average Climatig Score of all assets in that portfolio.


The CLIMATIG Cost (CC) is the change in costs (increase or decrease) due to the consequences of climate change compared to the reference historical period, in a selected period of time, assuming a selected climate scenario.

To calculate CLIMATIG Cost, we use the calculated climate risks with entered asset’s cost data to create estimated cost predictions for the future. This calculation takes climate change into consideration, for the selected climate scenarios and time period.



Utilizing the CLIMATIG API, developers can effortlessly incorporate climate risk and raw climate data into their applications, enhancing the functionality and value proposition of their products. This feature is particularly valuable for users with a large number of assets, such as insurance companies and banks.

To retrieve climate risks, users simply need to provide the address or coordinates of the asset, along with specifying the type of asset. This ensures that the API delivers tailored and relevant climate risk information for accurate decision-making.

What-If analysis

In addition to its robust climate data retrieval capabilities, CLIMATIG also offers a powerful WHAT-IF analysis feature. This functionality allows enterprise users to modify key parameters, such as forest density, proximity to the coastline, or the elevation of an asset. By doing so, they can assess how such changes will impact future climate risks.

This feature is particularly invaluable for architects and urban planners, as it provides them with a dynamic tool to evaluate and adapt their designs in response to potential climate variations. Through the ‘what if’ analysis, users can gain critical insights into the resilience of their projects against changing climate conditions.

In the economic part of CLIMATIG, users can adjust parameters such as property value, annual costs, and income to obtain tailored estimates of the costs associated with future climate changes. This feature is particularly valuable for financial analysts, property investors, and policymakers.


Users have the capability to input polygons within CLIMATIG. By drawing polygons, users can input spatially larger assets such as campgrounds, hotel complexes, wind farms, or railway tracks. Through this polygon feature, users receive climate risk assessments for points within the designated polygon. This provides a more realistic and precise understanding of the potential climate impacts on their assets.

This functionality is particularly advantageous for enterprises managing extensive infrastructure or complex facilities. By utilizing the polygon input feature, users gain a comprehensive assessment of climate risks for their entire spatial footprint, allowing for more informed decision-making and proactive climate adaptation strategies.


In addition, users have the capability to create portfolios within CLIMATIG, allowing them to allocate and manage assets effectively. This functionality provides a managerial perspective on portfolios, enabling users to gain insights into their asset distributions.

Users can also compare portfolios, including both the climate aspect (CLIMATIG Score) and the economic aspect (CLIMATIG Cost). This feature facilitates data-driven decision-making by allowing users to evaluate the performance and resilience of different portfolios against climate risks and associated costs.


CLIMATIG offers a powerful Map View feature, allowing users to visualize all assets and assets within portfolios on a map. These are colour-coded based on their respective climate risk categories. This provides users with a clear and intuitive representation of the distribution of climate risks across their assets.

Users can explore the overall risk level or delve into specific CLIMATIG Scores associated with different hazards. This level of detail empowers users to make strategic decisions about their assets, enabling them to prioritize mitigation efforts based on the specific climate risks they face.

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