Climate change is leading to an increase in the frequency and intensity of heatwave events across the globe. These events typically generate thermal discomfort, lack of productivity, more energy consumption, health problems or even deaths. However, not all regions, urban areas and, hence, inhabitants will be hit equally hard.
To reduce or at least mitigate these impacts we developed the easy-to-use Thermal Assessment Tool (TAT) to visualize heat-related data which offer added-value information regarding the impact of heatwave events at both regional and local scale.
This information is crucial to improve the adaptative capacity of regions and cities and supports different stakeholders in the design of adaptation plans and regional policies.
The tool analyses, processes and simplifies large volumes of data through different interactive maps and plots that make it easier to understand past and future extreme hot events at different regional scales to support decision making. In that sense, the tool offers two main services each providing the following benefits:
Heatwaves Service: This service provides customized panels to easily visualize the frequency and severity of past experienced and future projected heatwaves in Europe at different regional scales which is of great use for public health users, urban planning managers, climate change researchers and other stakeholders to raise awareness about what is going to come and support climate adaptation plans at both regional and city scale.
Heatmaps Service: This service provides high resolution (30m) summer mean surface temperature maps at city level to better visualize areas of higher surface heat concentration which is of great use for urban and sustainable managers to plan future building retrofitting or city scale interventions.
The tool is used in the Analysis phase, as it supports the heat hazard assessment.
Overall level of complexity: Level 1 (Ready to use light approach).
More information at https://thermal-assessment.urban.tecnalia.dev/
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036599.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036599.
