North Eurasian thermal comfort indices dataset (NETCID): new gridded database for the biometeorological studies
Global climate changes give us the important task of obtaining information about the spatial distribution of bioclimatic comfort indicators at the global or continental level. One of the most applicable tools can be based on reanalysis data (meteorological gridded data with global coverage). This issue is fully relevant for the territory of Northern Eurasia with its diverse climates, rapid environmental changes, and often sparse network of in situ observations. In this paper, we present a conceptually new dataset for the most popular thermal comfort indices, namely heat index (HI), humidex (HUM), wind chill temperature, mean radiant temperature, physiologically equivalent temperature (PET) and Universal Thermal Comfort Index (UTCI) derived from ERA-Interim reanalysis hourly data for the territory of Northern Eurasia (the area limited by 40° N–80° N, 10° W–170° W). The dataset has horizontal resolution of 0.75° × 0.75° (up to 79 km), temporal resolution of 3 h, and covers the period from 1979 to 2018 (40 years), which corresponds to the standard of the World Meteorological Organization in determining the parameters of the modern climate. Time series of indices are supplemented with a set of 8092 pre-calculated statistical parameters characterizing climatology of the thermal stress conditions. We further present several examples of the North Eurasian Thermal Comfort Indices Dataset (NETCID) data application, including analysis of the spatial heterogeneity of thermal stress conditions, assessment of their changes and analysis of specific extreme events. Presented examples demonstrate a pronounced difference between considered indices and highlight the need of their accurate selection for applied tasks. In particular, for the whole study areas HI and HUM indices show much smaller thermal stress repeatability and weaker trends of its changes in comparison to PET and UTCI indices. NETCID is available for free download at https://doi.org/10.6084/m9.figshare.12629861.