More resilient city planning
Providing a heat stress index to allow urban planners to have a better understanding of the best adaptation practices against extreme temperatures in urban environments.
In a nutshell
- Heat stress in urban areas has detrimental effects on the public health and urban infrastructure and it is constantly amplified by the climate change.
- With the capabilities of Climate DT, this use case aims to develop advanced simulations that would help to address the challenges caused by the urban heat islands.
- It is expected that the use case will produce a heat stress index obtained from several indicators as well as from existing specific heat stress indicators, which will support better decision-making and data-driven adaptation policies in cities.
The heat island effect multiplies the consequences of extreme temperatures and with the better simulations of the global circulation systems included in the Climate DT we can improve our understanding of the expected evolution of heat islands under climate change conditions, to apply more effective adaptation measures.
This figure shows average maximum temperature (Tx) for JJA (June-July-August) in 2020 over the Iberian Peninsula at a horizontal resolution of 5 km. The average was computed using daily temperature values. Data comes from the ICON model. Grey shaded areas represent urban regions. Credit: BSC
Through this use case the Climate DT will provide a heat stress index obtained from several indicators as well as from existing specific heat stress indicators, commuted using the Thermofeel library, developed by ECMWF. The application will be coupled with a machine learning downscaling model developed by Portugal’s +ATLANTIC.
The application will produce a set of temperature extreme indicators such as tropical nights, warm nights, summer days, warm days, absolute maximum temperature, excess heat factor and heat wave magnitude index, to name a few, and thermal comfort indicators like cooling degree days, NOAA Heat Index, wet bulb globe temperature and Universal Thermal Climate Index, at several spatial and temporal scales.
Initially the use case will be demonstrated for selected cities across the 5 continents. Thanks to the +ATLANTIC machine learning processing, the Urban application will downscale the information about heat island effect at around 100-200m spatial resolution.
In the long term the vision for the Urban use case is to allow urban planners (architects, civil engineers, decision makers…) to interact with the simulations for a better understanding of the best adaptation practices against extreme temperatures in urban environments.