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Authors/Creators/ Team Members: Sara R. Ronnkvist, Zoe Haskell-Craig, Risto Conte Keviabu, Abbie Robinson, Mathew E. Hauer, Domenico Bovienzo, Emilio Zagheni

Specific purpose of code: This GitHub repository contains a collection of scripts that generate datasets quantifying extreme temperature exposure in Europe using a variety of metrics at two sub-national spatial scales (NUTS 2 and NUTS 3) and three temporal scales (daily, extreme temperature wave, and yearly) from 1980-2024. These datasets capture the breadth of temperature metrics used in epidemiology, demography and environmental literature with 67 different metrics: including regionally-unusual temperature events (defined as temperatures above/below the 95th/5th percentile of historical temperatures) and periods of sustained (consecutive day) exposure to extreme temperatures. Additionally, these scripts can be adapted to construct temperature extremes for other geographic regions or scales with a few minor revisions. 

General Application: The TEE datasets can be linked to any data that contains NUTS identifiers(e.g.Eurostat)using a simplemergeto study the impacts of extreme temperatures on populations.

How does or could this code allow researchers to assess research questions related  to aging or life course?: The TEE datasets provide temperature data in a user-friendly format which can easily be linked to EuroStat or other datasets with NUTS identifiers. Additionally, our code is reproducible and easily adaptable to other geographic regions and/or time frames. Researchers who wish to study other regions may adapt our code to construct extreme temperature measures.

Data sets used: 

Are all the data publicly available or are some restricted-access? Publicly available.

Links to data: TEE dataset are available on FigSharehttps://springernature.figshare.com/articles/dataset/Temperature_Extremes_in_Europe_TEE_/28063226

Coding Language: We use Python to download the extreme temperature data from Copernicus and aggregate the hourly data to daily temperature measures. We use R for everything else.

Tools and Packages used:

R: terra, exactextractr, sf, tidyverse, foreign, zoo 

Python: os, glob, shutil, zipfile, cdsapi,  xarray, numpy 

Output(s):

16 datasets: 

  • Annual measures of extreme temperature 
  • tee_yearly_nuts2.csv 
  • tee_yearly_nuts3.csv 
  • Extreme temperature waves (consecutive days of temperature extremes) 
  • tee_wave_nuts2.csv 
  • tee_wave_nuts3.csv 
  • Daily temperature measure datasets split into 10-year files to reduce file size 
  • tee_daily_nuts2_[START YEAR]_[END YEAR].csv 
  • tee_daily_nuts3_[START YEAR]_[END YEAR].csv 

Spatial extent: European Union countries

Temporal extent: 1980-2024 

Comments: Ronnkvist et al (2025) contains detailed information on how the datasets were constructed and the included metrics. We provide replication instructions in the TEE-dataset GitHub repository (https://github.com/haskellcraigz/TEE-dataset/tree/main). 

Citation: 

Ronnkvist, S.R., Haskell-Craig, Z., Robinson, A., Conte Keivabu, R., Hauer, M.E., Bovienzo, D., & Zagheni, E. (2025) What’s the TEE: Metrics of Temperature Extremes in Europe NUTS Regions (1980-2024). Scientific Datahttps://doi.org/10.1038/s41597-025-05352-7 

Published papers that use this code:

Scientific Data publication associated with the TEE datasets: 

Ronnkvist, S.R., Haskell-Craig, Z., Robinson, A., Conte Keivabu, R., Hauer, M.E., Bovienzo, D., & Zagheni, E. (2025) What’s the TEE: Metrics of Temperature Extremes in Europe NUTS Regions (1980-2024). Scientific Datahttps://doi.org/10.1038/s41597-025-05352-7