Abstract
In this paper we present a dataset that contains daily mean, maximum and minimum values of 12 heat stress indices averaged over Greek communes from January 1998 to December 2022. The heat indices contained in the dataset include Apparent Temperature (AT), Heat Index (HI), Humidity Index (Humidex), Normal Effective Temperature (NET), Wet Bulb Globe Temperature (simple version WBGT), Wet Bulb Globe Temperature (thermofeelWBGT), Wet Bulb Temperature (WBT), Wind Chill Temperature (WCT), Mean Radiant Temperature (MRT), and Universal Thermal Climate Index (UTCI) with two variations (UTCI indoor and UTCI outdoor). To develop the dataset, we used hourly climate variables, acquired from the ERA5 and ERA5-Land datasets, produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which are accessible through the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) Application Program Interface (API) client. We used freely available python scripts and resources (HiTiSEA repository, thermofeel library), to calculate 12 heat stress indices for Greece at an enhanced spatial resolution of 0.1° × 0.1°. To facilitate geospatial analysis over the Greek communes, boundary data in shapefile format were obtained from the Hellenic Statistical Authority (ELSTAT). The execution of a built-in QGIS function was implemented to geospatially aggregate the NetCDF files of 12 daily mean, maximum and minimum, indices to 326 Greek communes for 9131 days. The high spatial and temporal resolution of the data, makes the dataset appropriate for analysis and comparison of climate change impacts, heatwave patterns, and the development of climate adaptation strategies at a regional scale in Greece. Additionally, it can be used as a basis of a system to inform and devise targeted interventions and policies aimed at mitigating the effects of extreme heat events. The attribution of heat stress indices at the commune level (also referred as municipalities or municipal units), which is the lowest level of government within the organizational structure in Greece, enhances the usefulness of the data for statistical analysis against other parameters, such as epidemiological or socio-economic data, which are often available at this level. Finally, the dataset can support educational purposes, providing a practical example of climate data analysis and geospatial statistics applications.