The vector dataset presents the percentage of green space in densely built-up areas for a series of individual European cities (included in Urban Audit) for the year 2012. The presence and proportion of green space in densely built-up urban areas is an important aspect of adaptation to climate change. Green space regulates the microclimate of the city, reducing the temperatures. It also reduces the risk of flooding related to heavy precipitation, as vegetation and permeable surfaces retain and infiltrate rainwater, reducing the amount that comes into the drainage system. Data on green space was obtained from Copernicus Urban Atlas 2012, extracting the Urban Atlas classes treated as green space. The Urban Morphological Area (UMZ) dataset for 2012 and the Eurostat Urban Audit dataset (polygon, 2011-2014) were been used to calculate the total area within the core city. The values were then allocated to the city centroids from the same Eurostat Urban Audit dataset.

This raster dataset provides the modelling of the climate suitability index values (0-100%) for tiger mosquito (Aedes albopictus) for 100 European cities for the years 2008-2009, with a resolution of 100 m. Aedes Albopictus has become a common occurrence in Southern Europe and transmits diseases such as Zika, dengue and chikungunya. The climatic suitability for tiger mosquito depends on factors such as sufficient amounts of rainfall, high summer temperatures and mild winters. Climate change is anticipated to further facilitate the spread of tiger mosquitoes across Europe by changing temperature and precipitation patterns, thereby increasing the suitable habitat. In the framework of the Copernicus Climate Change Service (C3S) SIS European Health, VITO has provided to the Climate Data Store 100m resolution hourly temperature data for 100 European cities, based on simulations with the urban climate model UrbClim (De Ridder et al., 2015). From this dataset, this climate suitability dataset has been generated based on annual precipitation and the average temperature in January and during the summer period (months June, July and August) for the years 2008-2009, following the methodology by European Centre for Disease Prevention and Control (ECDC, 2009). The 100 European cities for the urban simulations were selected based on user requirements within the health community.

This vector dataset provides the climate suitability index values (0-100%) for tiger mosquito (Aedes albopictus) for 100 European cities for the years 2008-2009 (P90 - 90th percentile). Aedes Albopictus has become a common occurrence in Southern Europe and transmits diseases such as Zika, dengue and chikungunya. The climatic suitability for tiger mosquito depends on factors such as sufficient amounts of rainfall, high summer temperatures and mild winters. Climate change is anticipated to further facilitate the spread of tiger mosquitoes across Europe by changing temperature and precipitation patterns, thereby increasing the suitable habitat. In the framework of the Copernicus Climate Change Service (C3S) SIS European Health, VITO has provided to the Climate Data Store 100m resolution hourly temperature data for 100 European cities, based on simulations with the urban climate model UrbClim (De Ridder et al., 2015). From this dataset, this climate suitability dataset has been generated based on annual precipitation and the average temperature in January and during the summer period (months June, July and August) for the years 2008-2009, following the methodology by European Centre for Disease Prevention and Control (ECDC, 2009). This approach considers empirical suitability functions, which link a number of (aggregated) climate variables to the suitability of a habitat for a given vector species, e.g. for a species to be active a minimum threshold of temperature is required below which the species is not active. Similarly some species cannot overwinter if the winter is too cold (e.g. January temperature lower than a given value). The P90 indicator represents the specific exposure of single cities and is independent of the model domain or size of a city. The 100 European cities for the urban simulations were selected based on user requirements within the health community.