DOI: 10.5281/zenodo.10955208
title: Daily time series of 12 human thermal stress indices in Greece aggregated at commune level (1998-2022)

description: The overview table of the dataset containing 12 Human Thermal Stress Indices in Greece (HTSI-GR):








Heat indices names



Description



Units



Reference



Dataset file names





AT



Apparent Temperature



°C



Steadman, R. G. Norms of apparent temperature in Australia. Aust. Met. Mag. 43, 1–16 (1994).



AT_min_1998-01-01_2022-12-31.csv, AT_mean_1998-01-01_2022-12-31.csv, AT_max_1998-01-01_2022-12-31.csv





HI



Heat Index



°C



Rothfusz, L.P. Te heat index equation. National Weather Service Technical Attachment. Report No. SR 90–23 (1990).



HI_min_1998-01-01_2022-12-31.csv, HI_mean_1998-01-01_2022-12-31.csv, HI_max_1998-01-01_2022-12-31.csv





Humidex



Humidity Index



°C



Masterson, J. & Richardson, F.A. Humidex: a method of quantifying human discomfort due to excessive heat and humidity (Environment Canada, 1979).



Humidex_min_1998-01-01_2022-12-31.csv, Humidex_mean_1998-01-01_2022-12-31.csv, Humidex_max_1998-01-01_2022-12-31.csv





NET



Normal Effective Temperature



°C



Landsberg HE. The assessment of human bioclimate: a limited review of physical parameters. Technical Note No. 123, WMO-No. 331 (World Meteorological Organization, 1972).



NET_min_1998-01-01_2022-12-31.csv, NET_mean_1998-01-01_2022-12-31.csv, NET_max_1998-01-01_2022-12-31.csv





WBGT



Wet Bulb Globe Temperature (simple)



°C



Australian Bureau of Meteorology. Thermal comfort observations http://bom.gov.au/info/thermal_stress/ (2020).



WBGT_min_1998-01-01_2022-12-31.csv, WBGT_mean_1998-01-01_2022-12-31.csv, WBGT_max_1998-01-01_2022-12-31.csv





thermofeelWBGT



Wet Bulb Globe Temperature



°C



Stull, R. Wet-bulb temperature from relative humidity and air temperature. J. Appl. Meteorol. Climatol. 50, 2267–2269 (2011).



thermofeelWBGT_min_1998-01-01_2022-12-31.csv, thermofeelWBGT_mean_1998-01-01_2022-12-31.csv, thermofeelWBGT_max_1998-01-01_2022-12-31.csv





WBT



Wet Bulb Temperature



°C



Stull, R. Wet-bulb temperature from relative humidity and air temperature. J. Appl. Meteorol. Climatol. 50, 2267–2269 (2011).



WBT_min_1998-01-01_2022-12-31.csv, WBT_mean_1998-01-01_2022-12-31.csv, WBT_max_1998-01-01_2022-12-31.csv





WCT



Wind Chill Temperature



°C



Office of the Federal Coordinator for Meteorological services and supporting research (OFCM). Report on Wind Chill Temperature and extreme heat indices: evaluation and improvement projects. Report No. FCM-R19-2003 (U.S. Office of the Federal Coordinator for Meteorological Services and Supporting Research, 2003).



WCT_min_1998-01-01_2022-12-31.csv, WCT_mean_1998-01-01_2022-12-31.csv, WCT_max_1998-01-01_2022-12-31.csv





MRT



Mean Radiant Temperature



°C



Weihs, P. et al. The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from measured and observed meteorological data. Int. J. Biometeorol. 56, 537–555 (2012).



MRT_min_1998-01-01_2022-12-31.csv, MRT_mean_1998-01-01_2022-12-31.csv, MRT_max_1998-01-01_2022-12-31.csv





UTCI



Universal Thermal Climate Index (UTCI)



°C



Bröde, P. et al. Deriving the operational procedure for the Universal Thermal Climate Index (UTCI). Int. J. Biometeorol. 56, 481–494(2012).



UTCI_min_1998-01-01_2022-12-31.csv, UTCI_mean_1998-01-01_2022-12-31.csv, UTCI_max_1998-01-01_2022-12-31.csv





UTCI2



Indoor environment UTCI with 2 parameters (air temperature and humidity)



°C



Bröde, P. et al. Deriving the operational procedure for the Universal Thermal Climate Index (UTCI). Int. J. Biometeorol. 56, 481–494(2012).



UTCI2_min_1998-01-01_2022-12-31.csv, UTCI2_mean_1998-01-01_2022-12-31.csv, UTCI2_max_1998-01-01_2022-12-31.csv





UTCI3



Outdoor shaded space environment UTCI with 3 parameters (air temperature, humidity, and wind speed)



°C



Bröde, P. et al. Deriving the operational procedure for the Universal Thermal Climate Index (UTCI). Int. J. Biometeorol. 56, 481–494(2012).



UTCI3_min_1998-01-01_2022-12-31.csv, UTCI3_mean_1998-01-01_2022-12-31.csv, UTCI3_max_1998-01-01_2022-12-31.csv






 

The overview table of the HTSI-GR additional resources folder containing support files and instructions for dataset replication:






File names



Description





0. Calculate thermofeelWBGT.py



A python script that calculates the Wet Bulb Globe Temperature (WBGT) using the Thermofeel library. Processes NetCDF files containing daily meteorological data and outputs WBGT values in new NetCDF files for each day.





1. Merge_HI_by_max-mean-min.py



A python script that merges daily NetCDF files containing heat index (HI) data into three separate files based on mean, maximum and minimum values for further processing.





2. QGIS_zonal_statistics.py



A python script that calculates zonal statistics for heat indices using QGIS python console. Uses a shapefile of Greek communes and a raster NetCDF file containing daily index values, and outputs daily CSV files with computed statistics.





3. Zonal_format.py



A python script that formats the zonal statistics results into a comprehensive dataset. Combines daily CSV files into a single CSV, fills in missing data using nearest neighbour values, and produces a final formatted dataset.





Greek Communes.ZIP



Contains the shapefile of Greek communes derived from the Hellenic Statistical Authority (ELSTAT) required for zonal statistics calculations. KALCODE and Commune names are linked in the .shp.





Nearest Neighbour data table.csv



A support table to script 3.Zonal_format.py that lists communes with missing data and their nearest neighbour with data.





Read me.txt



Provides an overview and instructions for using the scripts. Describes the purpose of each script, lists prerequisites, and provides step-by-step instructions for replicating the dataset.





 

 
description: In this paper we present a dataset that contains daily mean, maximum and minimum values of 12 human thermal 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° x 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 health, 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.