Page Text: Analysing climate impacts on infrastructure
Images Copyright Copernicus Climate Change Service
A drive towards sustainable and future-proofing infrastructure means that climate change is beginning to be embedded into the standards that drive the design and maintenance of industries such as transport, buildings and power distribution networks. Alongside this drive for sustainability, the world of climate data is developing at a rapid pace. Computer models simulating possible future climate and weather events are being created and improved upon in an on-going cycle of world-class scientific research. The options are seemingly endless. Do you want a model that captures the entire world, such as one from the CMIP5 family (Coupled Model Intercomparison Project)? Or one for a specific region, such as the CORDEX (Coordinated Regional Climate Downscaling Experiment) models? Maybe maximum detail for a specific country is required, like the UKCP18 for the UK. For most businesses, this all means confusion. Where do you obtain trusted climate data? How do you use it? What are its strengths and weaknesses? What do the numbers mean? The questions are never-ending and not many of them have a simple yes/no answer.
Process
A recent project commissioned by the European climate data supplier - Copernicus Climate Change Service (C3S) - saw the IEA and several European partners using the C3S Climate Data Store, an online repository of climate data, to try to address these questions using five use cases where infrastructure design might be impacted by climate change: (i) long term design and planning of roads in Spain (ii) climate change adaptation in railway infrastructure planning in the Netherlands/UK (iii) a climate stress-test for urban infrastructures in the city of Amersfoort, the Netherlands and Basque municipalities, Spain (iv) design of power station and district heating in Vitoria, Spain and (v) water and sewage infrastructure management in Rome.
During the project, feedback from industry partners regarding data presentation, structure and areas of uncertainty were taken into account and used to improve documentation around datasets. For example, while daily data can be provided, it was made clear that the output of the model for a certain date in the future is not a forecast for that day.
Solution
Our analysis found that the large uncertainty that exists in the future projections of extreme events, the inherent limitations and inadequacies of climate models and the need for very high-resolution data (due to the local features of a site being of utmost importance) often limit the possibility to feed climate model data directly into standards. This means there is currently an absence of simple, practical examples of climate projections being used to design and operate infrastructure. The project tackled this by highlighting a number of case studies and by providing improved documentation to guide activity.
Impact
The project aimed to provide a realistic, traceable and robust methodology for dealing with climate models of all types, signposting users to sources of climate data that are well referenced. Whilst the project focused on Europe, the lessons and outcomes are equally applicable to other regions. Work was also undertaken to communicate with standards bodies such as the European standards organisations (CEN-CENLEC) to highlight the complexities of using climate data and how to start renewing it into standards.
Back to project stories
Tell us about your data challenge
Get in touch
The University of Reading's Data Protection policy .
The icons in How we do it are from Icons8 .