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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 spatialdistribution of bioclimatic comfort indicators at the global or continental level. One of the mostapplicable 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, rapidenvironmental changes, and often sparse network of in situ observations. In this paper, we presenta conceptually new dataset for the most popular thermal comfort indices, namely heat index (HI),humidex (HUM), wind chill temperature, mean radiant temperature, physiologically equivalenttemperature (PET) and Universal Thermal Comfort Index (UTCI) derived from ERA-Interimreanalysis 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), temporalresolution of 3 h, and covers the period from 1979 to 2018 (40 years), which corresponds to thestandard of the World Meteorological Organization in determining the parameters of the modernclimate. Time series of indices are supplemented with a set of 8092 pre-calculated statisticalparameters characterizing climatology of the thermal stress conditions. We further present severalexamples of the North Eurasian Thermal Comfort Indices Dataset (NETCID) data application,including analysis of the spatial heterogeneity of thermal stress conditions, assessment of theirchanges and analysis of specific extreme events. Presented examples demonstrate a pronounceddifference between considered indices and highlight the need of their accurate selection for appliedtasks. In particular, for the whole study areas HI and HUM indices show much smaller thermalstress 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.