Click below for responses to frequently asked questions.
The Climate Risk Typology is a tool to visualise, describe, compare and analyse climate risk in European cities and regions. It clusters cities and regions according to their climate risk characteristics, creating a detailed risk profile for individual cities and regions and enabling comparisons between them. This online portal provides interactive maps, statistical data and supporting information related to the Climate Risk Typology.
The typology is intended for use by decision-makers, strategic planners and researchers involved in understanding and responding to climate risk. You can use it to inform climate change risk assessments, support the development of adaptation and resilience strategies and help encourage networking and sharing of knowledge and experience. It can also be used for exploratory work on spatial risk patterns. See the Uses page of this website for further guidance on the application of the typology.
The typology is not a tool for detailed climate change risk assessment and climate change adaptation planning and strategy development. Because it operates at larger spatial scales (NUTS3 regions), the typology and related climate risk indicators need to be supplemented with specific local data for more detailed assessment and planning. Nevertheless, the typology can provide an insight into the drivers of climate risk to explore in more detail locally.
Cities were considered as the main unit of analysis for the typology. However, there are significant gaps in climate risk data coverage and availability at this scale which would have held back the development of the typology. There is also a danger of isolating cities from their surrounding hinterland areas. Instead, the typology uses NUTS3 regions as a spatial unit which allows complete coverage of Europe. Also, many of Europe’s major cities are made up of one or more NUTS3 region, enabling a city-based perspective to be taken in many cases.
NUTS3 regions are part of a system that subdivides the economic territory of Europe to support statistical data gathering, socio-economic analysis and the framing of European policies. The system is population-based, and NUTS3 regions are defined as ‘small regions’ with a population between 150,000 and 800,000 people. There are 1379 NUTS3 regions in Europe, with varying densities seen across different countries.
Sometimes the typology might give you a surprising result for a city or region. Perhaps it is in a different class from what you expected would be the case, or it is classified alongside seemingly different regions in other parts of Europe. There are several things to consider when interpreting the typology classification that can help to address this question:
In some cases, indicator data for specific regions was missing or faulty due to problems with the original data. A technique called areal interpolation was used to fill those gaps and to enable the typology to be developed for all European NUTS3 regions. This technique allows missing values to be predicted by considering available data values for the whole European surface area. While this allows an indicator z-score to be developed for the region, it is not possible to give actual data values here as they are predicted. This is the case for example for some demographic indicators. See Methodology for more details.
The classes and sub-classes describe groups of NUTS3 regions with similar climate risk characteristics, based on climate hazards and exposure and vulnerability to these hazards. They are the outcome of a cluster analysis methodology incorporating around 50 indicators for each NUTS3 region (see Methodology for more details). There are 8 main classes, such as 'Inland and Urbanised' and 'Northern Lands', each of which is separated into 3 to 5 sub-classes that identify different clusters of NUTS3 regions within each class.
The indicator tables for each region and the indicator diagrams make reference to z-scores. This is a statistical measure showing how far above or below the European mean a particular data point lies for a selected NUTS3 region. The mean (or European average) has a z-score of 0. All values above the mean have a positive z-score, and all values below the mean have a negative z-score. The higher the positive value and the lower the negative one, the further away from the mean these values are. For example, the Landlocked and Elevated class has a z-score of -0.231 for the heat wave days indicator, meaning the projected increase in heat wave days compared to the baseline is slightly below the European average. For Southern Lands the z-score for this indicator is 1.363, which puts the NUTS3 regions within this class significantly above the European average for this indicator.
The indicator histogram shows how the values for an indicator are distributed, or in other words, where the regions lie relative to the European average for that indicator. The z-score values have been assigned to intervals (bands) having a distance of half standard deviation. The height of the bars indicate the frequency of the z-score belonging to each interval. The higher the bar, the more regions lie in a particular interval of z-score values. This enables an easy understanding of the distribution from a statistical perspective, and complements the spatial distribution shown by the indicator maps.
(See question: What do the indicator diagrams show? ).
The indicator diagrams are a visual representation of the indicator z-scores and are available for each class, sub-class and region. For the classes, the blue line at z-score 0 shows the European average, the red line indicates the average z-score for each indicator for the selected class. For the sub-classes, the blue line at z-score 0 shows the average for the class that it falls within, and the red line indicates the average z-score for each indicator for the selected sub-class. The indicator diagrams therefore allow a quick overview of those indicators which are significantly above or below European average. These correspond to important climate risk characteristic for each class/sub-class.
The online portal offers users the ability to map a range of hazard, exposure, sensitivity and adaptive capacity indicators on a European scale. The indicator maps visualise the values of a selected indicator across all NUTS3 regions in Europe. The maps are based on the indicator z-scores (see question: What is a z-score?), and indicate whether regions lie above or below the European average for the selected region. Thus they complement the histograms (see question: What do the histograms show?) by showing variation in climate risk indicators across the European territory from a spatial perspective. The visualisation can support users in placing their selected city or NUTS3 region in a European context.
In developing the typology, we cleaned and processed data to develop a large range of indicators. For statistical reasons, including excessive correlation, not all of them were employed in the final typology analysis, which the indicator diagrams are based on. Nevertheless, as these indicators might still be interesting for users, we have made them available for use via the online portal.
The online version of the European Climate Risk Typology should be cited as:
Carter, J.G, Hincks, S, Vlastaras, V, Connelly, A and Handley, J. 2018. European Climate Risk Typology. [ONLINE] Available at: http://european-crt.org/index.html