The raster dataset presents the median of the projected number of extreme heatwaves in the near future (2020–2052) in Europe, following the Representative Concentration Pathways (RCP) 8.5 scenario. The dataset is one of the multimodel ensemble used to project future occurrence and severity of heat waves under different RCP, which were adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5). The dataset is one of the output of the JRC “Number of heat waves” data described here: https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2014JD022098. The dataset has been used as a source for the EEA indicator “Global and European temperature”: https://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-8/assessment, which in the meantime has been already updated.

The dataset presents the annual number of Cooling Degree Days (CDD) in average for the period 1990-2015, for a series of individual European cities from Eurostat's Urban Audit 2011-2014 spatial dataset, based on the E-OBS dataset from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and around 10,000 meteorological stations across Europe. This dataset has been used in the EEA Report No 22/2018 "Unequal exposure and unequal impacts: social vulnerability to air pollution, noise and extreme temperatures in Europe" (https://www.eea.europa.eu/publications/unequal-exposure-and-unequal-impacts/at_download/file), where CDD is defined as the sum of the difference in degrees between 21 °C and the mean temperature over the year, for the days when the mean daily temperature is higher than 21 °C. The number of CDDs is useful in differentiating between areas based on the need for cooling homes or workplaces. As a measurement designed to quantify the demand for energy needed to cool a building in order to keep it at a comfortable temperature, it is relevant to issues of thermal comfort and energy affordability.

The gridded dataset presents the median of the projected number of extreme heatwaves in the future (2068–2100) in Europe, following the Representative Concentration Pathways (RCP) 8.5 scenario. The dataset is one of the multimodel ensemble used to project future occurrence and severity of heat waves under different RCP, which were adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5). The dataset is one of the output of the JRC “Number of heat waves” data described here: https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2014JD022098 The dataset has been used as a source for the EEA indicator “Global and European temperature”: https://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-8/assessment, which in the meantime has been updated.

The raster dataset of urban heat island modelling shows the fine-scale (100m pixel size) temperature differences (in degrees Celsius °C) across 100 European cities, depending on the land use, soil sealing, anthropogenic heat flux, vegetation index and climatic variables such as wind speed and incoming solar radiation. In the framework of the Copernicus European Health contract for the Copernicus Climate Change Service (C3S), VITO provided 100m resolution hourly temperature data (2008-2017) for 100 European cities, based on simulations with the urban climate model UrbClim (De Ridder et al., 2015). As the cities vary in size, so do the model domains. They have been defined with the intention to have a more or less constant ratio of urban vs. non-urban pixels (as defined in the CORINE land use map), with a maximum of 400 by 400 pixels (due to computational restraints). From this data set, the average urban heat island intensity is mapped for the summer season (JJA), which is the standard way of working in the scientific literature (e.g. Dosio, 2016). The UHI is calculated by subtracting the rural (non-water) spatial P10 temperature value from the average temperature map. The 100 European cities for the urban simulations were selected based on user requirements within the health community.