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Examples of Datasets & Applications at urban level

Sectoral Information System, Copernicus Climate Change Service

Climate Change

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Dataset: Climate variables for cities in Europe from 2008 to 2017

Variables: air temperature, specific humidity, relative humidity and wind speed for 100 European cities for the current climate

Click here for the Data: https://bit.ly/3HW4z7m

Data generated using the urban climate model UrbClim, developed at VITO

Model designed to simulate and study the urban heat island effect (UHI) and other urban climate variables at a spatial resolution of 100 metres

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The dataset contains air temperature, specific humidity, relative humidity and wind speed for 100 European cities for the current climate.
The data were generated using the urban climate model UrbClim, developed at VITO. This model was designed to simulate and study the urban heat island effect (UHI) and other urban climate variables at a spatial resolution of 100 metres and hourly resolution.
The model is run by using the ERA5 reanalysis as large-scale weather conditions – this is a downscaling to agglomeration-scale.
The 100 European cities for the urban simulations were selected based on user requirements within the health community.

A few details:

The model uses as inout 18 variables from ERA5 (land and pressure levels)
3 datasets for terrain inputs: Land use, soil sealing, NDVI
1 digital elevation model
1 dataset for anthropogenic heat flux

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Application: Urban heat island intensity from 2008 to 2017 from reanalyses

Urban environment experiences higher temperatures than the surrounding rural areas

Click here for the App: https://bit.ly/3CpwbRm

𝑇_𝑖 =T2m @each gridpoint

𝑇_𝑟𝑢𝑟 = T2m averaged over the rural grid points

Urban Heat Island intensity

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Application : Urban heat island intensity for European cities from 2008 to 2017 derived from reanalysis

Why: Users and stakeholders managing urban areas are particularly interested in the spatial pattern of heat exposure within a city, as such datasets can be used to identify cool islands and hot spots on an urban scale.

The urban environment experiences higher temperatures than the surrounding rural areas. This local effect originates from the higher amount of paved surfaces and high anthropogenic heat in the urban environment.

The so-called Urban Heat Island is most pronounced during the nighttime. Differences of a few degrees up to 10 °C can be measured between urban and rural areas.

The Application is a simple viewer of the urban heat island effect. User can chosse: City, Season, Year

Output the user gets: Urban Heat Island-intensity (°C): difference in 2 m air temperature from UrbClim between a certain grid point and the rural area-average. Rural area represented by the rural classes of CORINE

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Application: Urban Climate for cities in Europe from 2008 to 2017

1) Click on a city in map

3) Outputs:

A carousel with maps of

season stats

A timeseries of the variable

A download of csv file

2) Choose:

a season

a variable

a statistic

https://cds.climate.copernicus.eu/apps/c3s/app-health-urban-climate

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DRR: Extremes & urban pluvial risk

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Statistics on users (from splunk)

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