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.
This vector dataset shows the Urban Heat Island (UHI) intensity (in degrees Celsius °C) for 100 European cities, based on their elevation above sea level, land use, soil sealing, vegetation index and anthropogenic heat flux. The Urban Heat Island intensity exacerbates high temperatures in cities and thus may pose additional risks to human thermal comfort and health. The UHI intensity is represented by spatial P90 (90th percentile) urban heat island intensity of a given city ("P90" field in the dataset). This indicator is calculated by subtracting the rural (non-water) spatial P10 (10th percentile) temperature value from the average, height-corrected (to exclude terrain effects), air temperature map. This indicator represents the specific exposure of single cities and due to the height correction will be comparable across Europe. The dataset has been created by VITO within the Copernicus Health contract for C3S and is based on UrbClim model (De Ridder et al. 2015). The 100 European cities for the urban simulations were selected based on user requirements within the health community.
This metadata refer to the dataset presenting the annual change in the estimated West Nile Virus transmission risk between 1950 and 2020 by country. The risk varies between 0 (no risk) and 1 (very high risk). This indicator uses machine learning models incorporating WNV reported cases and climate variables (temperature, precipitation) to estimate WNV transmission probability. West Nile virus is a climate-sensitive multi-host and multi-vector pathogen. Human infection is associated with severe disease risk and death. In the past few decades, European countries have had a large increase in the intensity, frequency, and geographical expansion of West Nile virus outbreaks. The 2018 outbreak has been the largest yet, with 11 European countries reporting 1584 locally acquired infections. Increasing ambient temperatures are increasing the vectorial capacity of the Culex mosquito vector, and thus increasing the outbreak probability.
Corine Land Cover Change 1990-2000 (CHA9000) is one of the Corine Land Cover (CLC) datasets produced within the frame the Copernicus Land Monitoring Service referring to changes in land cover / land use status between the years 1990 and 2000. CHA is derived from satellite imagery by direct mapping of changes taken place between two consecutive inventories, based on image-to-image comparison. CLC service has a long-time heritage (formerly known as "CORINE Land Cover Programme"), coordinated by the European Environment Agency (EEA). It provides consistent and thematically detailed information on land cover and land cover changes across Europe. CLC datasets are based on the classification of satellite images produced by the national teams of the participating countries - the EEA members and cooperating countries (EEA39). National CLC inventories are then further integrated into a seamless land cover map of Europe. The resulting European database relies on standard methodology and nomenclature with following base parameters: 44 classes in the hierarchical 3-level CLC nomenclature; minimum mapping unit (MMU) for status layers is 25 hectares; minimum width of linear elements is 100 metres. Change layers have higher resolution, i.e. minimum mapping unit (MMU) is 5 hectares for Land Cover Changes (CHA), and the minimum width of linear elements is 100 metres. The CLC service delivers important data sets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as e.g. protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, monitoring urban land take, assessing developments in agriculture or dealing with water resources directives. CLC belongs to the Pan-European component of the Copernicus Land Monitoring Service (https://land.copernicus.eu/), part of the European Copernicus Programme coordinated by the European Environment Agency, providing environmental information from a combination of air- and space-based observation systems and in-situ monitoring. Additional information about CLC product description including mapping guides can be found at https://land.copernicus.eu/user-corner/technical-library/. CLC class descriptions can be found at https://land.copernicus.eu/user-corner/technical-library/corine-land-cover-nomenclature-guidelines/html/.
Corine Land Cover 1990 (CLC1990) is one of the Corine Land Cover (CLC) datasets produced within the frame the Copernicus Land Monitoring Service referring to land cover / land use status of year 1990. CLC service has a long-time heritage (formerly known as "CORINE Land Cover Programme"), coordinated by the European Environment Agency (EEA). It provides consistent and thematically detailed information on land cover and land cover changes across Europe. CLC datasets are based on the classification of satellite images produced by the national teams of the participating countries - the EEA members and cooperating countries (EEA39). National CLC inventories are then further integrated into a seamless land cover map of Europe. The resulting European database relies on standard methodology and nomenclature with following base parameters: 44 classes in the hierarchical 3-level CLC nomenclature; minimum mapping unit (MMU) for status layers is 25 hectares; minimum width of linear elements is 100 metres. Change layers have higher resolution, i.e. minimum mapping unit (MMU) is 5 hectares for Land Cover Changes (LCC), and the minimum width of linear elements is 100 metres. The CLC service delivers important data sets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as e.g. protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, monitoring urban land take, assessing developments in agriculture or dealing with water resources directives. CLC belongs to the Pan-European component of the Copernicus Land Monitoring Service (https://land.copernicus.eu/), part of the European Copernicus Programme coordinated by the European Environment Agency, providing environmental information from a combination of air- and space-based observation systems and in-situ monitoring. Additional information about CLC product description including mapping guides can be found at https://land.copernicus.eu/user-corner/technical-library/. CLC class descriptions can be found at https://land.copernicus.eu/user-corner/technical-library/corine-land-cover-nomenclature-guidelines/html/.
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 (https://vito.be/en) 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.
This metadata refer to the dataset presenting the annual change in the number of months suitable for the transmission of the Plasmodium vivax parasite causing malaria. The suitable months are those with precipitation above 80 mm, average temperature between 14.5°C and 33°C, and relative humidity above 60%, in land types highly suitable for Anopheles mosquitoes.
This metadata refer to the dataset presenting the annual change in heatwave exposure of people over 65, expressed as the deviation in annual person-days of heatwave exposure relative to the 1986-2005 baseline. Heat exposure poses acute health risks, particularly to older people (ie, people older than 65 years), people with underlying, chronic respiratory, kidney, or heart disease, people living in urban areas, and people with little means to access cooling mechanisms. These heat-related health risks are of particular relevance to Europe, as the continent is experiencing ageing populations, urbanisation, and a high prevalence of chronic diseases.
This metadata refer to the dataset presenting the modelled annual heat-related mortality incidence (annual deaths per million inhabitants) in Europe between 2000 and 2020 Heat-related deaths are estimated to have increased in 931 (94%) of the 990 regions monitored from 2000 to 2020, with an overall mean increase of 15·1 (95% CI –1·51 to 31·6) annual deaths per million inhabitants per decade for the general population, and 60·4 (–17·8 to 138·6) extra deaths per million inhabitants per decade for people 65 years and older.
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.