• ASHRAE, 1966: Thermal comfort conditions. ASHRAE Standards, American Society of Heating, Refrigerating and Air-Conditioning Engineers, 55–66.

  • Basarin, B., T. Lukić, M. Mesaroš, D. Pavić, J. Đorđević, and A. Matzarakis, 2018: Spatial and temporal analysis of extreme bioclimate conditions in Vojvodina, northern Serbia. Int. J. Climatol., 38, 142157, https://doi.org/10.1002/joc.5166.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bauche, J. P., E. A. Grigorieva, and A. Matzarakis, 2013: Human-biometeorological assessment of urban structures in extreme climate conditions: The example of Birobidzhan, Russian far east. Adv. Meteor., 2013, 749270, https://doi.org/10.1155/2013/749270.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blazejczyk, K., Y. Epstein, G. Jendritzky, H. Staiger, and B. Tinz, 2012: Comparison of UTCI to selected thermal indices. Int. J. Biometeor., 56, 515535, https://doi.org/10.1007/s00484-011-0453-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bleta, A., P. T. Nastos, and A. Matzarakis, 2014: Assessment of bioclimatic conditions on Crete Island, Greece. Reg. Environ. Change, 14, 19671981, https://doi.org/10.1007/s10113-013-0530-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, R. D., and T. J. Gillespie, 1986: Estimating outdoor thermal comfort using a cylindrical radiation thermometer and an energy budget model. Int. J. Biometeor., 30, 4352, https://doi.org/10.1007/BF02192058.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Büttner, K., 1938: Physikalische Bioklimatologie (Physical Bioclimatology). Akademische Verlagsgesellschaft, 155 pp.

  • Chernokulsky, A. V., O. N. Bulygina, and I. I. Mokhov, 2011: Recent variations of cloudiness over Russia from surface daytime observations. Environ. Res. Lett., 6, 035202, https://doi.org/10.1088/1748-9326/6/3/035202.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chi, X., R. Li, U. Cubasch, and W. Cao, 2018: The thermal comfort and its changes in the 31 provincial capital cities of mainland China in the past 30 years. Theor. Appl. Climatol., 132, 599619, https://doi.org/10.1007/s00704-017-2099-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coccolo, S., J. Kämpf, J. L. Scartezzini, and D. Pearlmutter, 2016: Outdoor human comfort and thermal stress: A comprehensive review on models and standards. Urban Climate, 18, 3357, https://doi.org/10.1016/j.uclim.2016.08.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Darack, E., 2013: The 10 worst weather places in the world. Weatherwise, 66, 1219, https://doi.org/10.1080/00431672.2013.839230.

  • de’Donato, F. K., and Coauthors, 2015: Changes in the effect of heat on mortality in the last 20 years in nine European cities. Results from the phase project. Int. J. Environ. Res. Public Health, 12, 15 56715 583, https://doi.org/10.3390/ijerph121215006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim Reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dematte, J. E., K. O’Mara, J. Buescher, C. G. Whitney, S. Forsythe, T. McNamee, R. B. Adiga, and I. M. Ndukwu, 1998: Near-fatal heat stroke during the 1995 heat wave in Chicago. Ann. Intern. Med., 129, 173181, https://doi.org/10.7326/0003-4819-129-3-199808010-00001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Di Napoli, C., F. Pappenberger, and H. L. Cloke, 2018: Assessing heat-related health risk in Europe via the Universal Thermal Climate Index (UTCI). Int. J. Biometeor., 62, 11551165, https://doi.org/10.1007/s00484-018-1518-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Égerházi, L. A., A. Kovács, and J. Unger, 2013: Application of microclimate modelling and on-site survey in planning practice related to an urban micro-environment. Adv. Meteor., 2013, 251586, https://doi.org/10.1155/2013/251586.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emelina, S. V., P. I. Konstantinov, E. P. Malinina, and K. G. Rubinshtein, 2014: Evaluation of the informativeness of several biometeorological indices for three areas of the European part of Russia. Russ. Meteor. Hydrol., 39, 448457, https://doi.org/10.3103/S1068373914070036.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fabbri, K., A. Di Nunzio, J. Gaspari, E. Antonini, and A. Boeri, 2017: Outdoor comfort: The ENVI-BUG tool to evaluate PMV values output comfort point by point. Energy Procedia, 111, 510519, https://doi.org/10.1016/j.egypro.2017.03.213.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fang, Z., Z. Lin, C. M. Mak, J. Niu, and K. T. Tse, 2018: Investigation into sensitivities of factors in outdoor thermal comfort indices. Build. Environ., 128, 129142, https://doi.org/10.1016/j.buildenv.2017.11.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fatichi, S., 2020: Mann-Kendall Test. MATLAB Central File Exchange, accessed 28 February 2020, https://www.mathworks.com/matlabcentral/fileexchange/25531-mann-kendall-test.

  • Fiala, D., G. Havenith, P. Bröde, B. Kampmann, and G. Jendritzky, 2012: UTCI-Fiala multi-node model of human heat transfer and temperature regulation. Int. J. Biometeor., 56, 429441, https://doi.org/10.1007/s00484-011-0424-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fröhlich, D., and A. Matzarakis, 2020: Calculating human thermal comfort and thermal stress in the PALM model system 6.0. Geosci. Model Dev., 13, 30553065, https://doi.org/10.5194/gmd-13-3055-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giannaros, T. M., V. Kotroni, K. Lagouvardos, and A. Matzarakis, 2018: Climatology and trends of the Euro-Mediterranean thermal bioclimate. Int. J. Climatol., 38, 32903308, https://doi.org/10.1002/joc.5501.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gleckler, P. J., K. A. Taylor, and C. Doutriaux, 2008: Performance metrics for climate models. J. Geophys. Res., 113, D06104, https://doi.org/10.1029/2007JD008972.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gorbarenko, E. V., 2019: Sunshine variability in Moscow in 1955–2017. Russ. Meteor. Hydrol., 44, 384393, https://doi.org/10.3103/S1068373919060037.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grigorieva, E., and A. Matzarakis, 2011: Physiologically equivalent temperature as a factor for tourism in extreme climate regions in the Russian far east: Preliminary results. Eur J. Tourism Hospitality Recreation, 2, 127142.

    • Search Google Scholar
    • Export Citation
  • Havenith, G., K. Błazejczyk, M. Richards, P. Bröde, I. Holmér, H. Rintamaki, Y. Benshabat, and G. Jendritzky, 2012: The UTCI-clothing model. Int. J. Biometeor., 56, 461470, https://doi.org/10.1007/s00484-011-0451-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Helsel, D. R., and R. M. Hirsch, 1992: Studies in Environmental Science. Vol. 49, Statistical Methods in Water Resources, Elsevier, 510 pp.

  • Hersbach, H., and Coauthors, 2019: Global reanalysis: Goodbye ERA-Interim, hello ERA5. ECMWF Newsletter, No. 159, ECMWF, Reading, United Kingdom, 17–24, https://www.ecmwf.int/en/newsletter/159/meteorology/global-reanalysis-goodbye-era-interim-hello-era5.

  • Höppe, P., 1997: Aspects of human biometeorology in past, present, and future. Int. J. Biometeor., 40, 1923, https://doi.org/10.1007/BF02439406.

  • Hwang, R. L., and T. P. Lin, 2007: Thermal comfort requirements for occupants of semi-outdoor and outdoor environments in hot-humid regions. Archit. Sci. Rev., 50, 357364, https://doi.org/10.3763/asre.2007.5043.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IPCC, 2013: Climate Change 2013: The Physical Science Basis. Cambridge University Press, 1535 pp., https://doi.org/10.1017/CBO9781107415324.

    • Search Google Scholar
    • Export Citation
  • Ippolitov, I. I., S. V. Loginov, E. V. Kharyutkina, and E. I. Moraru, 2014: Climate variability over the Asian territory of Russia during 1975–2012. Geogr. Nat. Resour., 35, 310318, https://doi.org/10.1134/S1875372814040027.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ivanov, V., M. Varentsov, T. Matveeva, I. Repina, A. Artamonov, and E. Khavina, 2019: Arctic sea ice decline in the 2010s: The increasing role of the ocean–air heat exchange in the late summer. Atmosphere, 10, 184, https://doi.org/10.3390/atmos10040184.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jacobs, S. J., A. B. Pezza, V. Barras, J. Bye, and T. Vihma, 2013: An analysis of the meteorological variables leading to apparent temperature in Australia: Present climate, trends, and global warming simulations. Global Planet. Change, 107, 145156, https://doi.org/10.1016/j.gloplacha.2013.05.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jendritzky, G., R. de Dear, and G. Havenith, 2012: UTCI—Why another thermal index? Int. J. Biometeor., 56, 421428, https://doi.org/10.1007/s00484-011-0513-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kajtar, L., J. Nyers, J. Szabo, L. Ketskemety, L. Herczeg, A. Leitner, and B. Bokor, 2017: Objective and subjective thermal comfort evaluation in Hungary. Therm. Sci., 21, 14091418, https://doi.org/10.2298/TSCI151005095K.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Katavoutas, G., and H. A. Flocas, 2018: Universal Thermal Climate Index (UTCI) and synoptic circulation patterns over the metropolitan city of Athens, Greece. Global NEST J., 20, 477487, https://doi.org/10.30955/gnj.002556.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kidston, J., D. M. W. Frierson, J. A. Renwick, and G. K. Vallis, 2010: Observations, simulations, and dynamics of jet stream variability and annular modes. J. Climate, 23, 61866199, https://doi.org/10.1175/2010JCLI3235.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kobysheva, N. V., Ed., 2001: The Climate of Russia (in Russian). Gidrometeoizdat, 656 pp.

  • Kocsis, T., I. Kovács-székely, and A. Anda, 2017: Comparison of parametric and non-parametric time-series analysis methods on a long-term meteorological data set. Cent. Eur. Geol., 60, 316332, https://doi.org/10.1556/24.60.2017.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Konstantinov, P. I., M. I. Varentsov, and E. P. Malinina, 2014: Modeling of thermal comfort conditions inside the urban boundary layer during Moscow’s 2010 summer heat wave (case-study). Urban Climate, 10, 563572, https://doi.org/10.1016/j.uclim.2014.05.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kottek, M., J. Grieser, C. Beck, B. Rudolf, and F. Rubel, 2006: World Map of the Köppen–Geiger climate classification updated. Meteor. Z., 15, 259263, https://doi.org/10.1127/0941-2948/2006/0130.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kovats, R. S., and S. Hajat, 2008: Heat stress and public health: A critical review. Annu. Rev. Public Health, 29, 4155, https://doi.org/10.1146/annurev.publhealth.29.020907.090843.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lindberg, F., B. Holmer, and S. Thorsson, 2008: SOLWEIG 1.0—Modelling spatial variations of 3D radiant fluxes and mean radiant temperature in complex urban settings. Int. J. Biometeor., 52, 697713, https://doi.org/10.1007/s00484-008-0162-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lindsay, R., M. Wensnahan, A. Schweiger, and J. Zhang, 2014: Evaluation of seven different atmospheric reanalysis products in the Arctic. J. Climate, 27, 25882606, https://doi.org/10.1175/JCLI-D-13-00014.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mąkosza, A., 2013: Bioclimatic conditions of the Lubuskie voivodeship. Geogr. Pol., 86, 3746, https://doi.org/10.7163/GPol.2013.5.

  • Matzarakis, A., H. Mayer, and M. G. Iziomon, 1999: Applications of a universal thermal index: Physiological equivalent temperature. Int. J. Biometeor., 43, 7684, https://doi.org/10.1007/s004840050119.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matzarakis, A., F. Rutz, and H. Mayer, 2007: Modelling radiation fluxes in simple and complex environments—Application of the RayMan model. Int. J. Biometeor., 51, 323334, https://doi.org/10.1007/s00484-006-0061-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matzarakis, A., M. De Rocco, and G. Najjar, 2009: Thermal bioclimate in Strasbourg—The 2003 heat wave. Theor. Appl. Climatol., 98, 209220, https://doi.org/10.1007/s00704-009-0102-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matzarakis, A., F. Rutz, and H. Mayer, 2010: Modelling radiation fluxes in simple and complex environments: Basics of the RayMan model. Int. J. Biometeor., 54, 131139, https://doi.org/10.1007/s00484-009-0261-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matzarakis, A., J. Rammelberg, and J. Junk, 2013: Assessment of thermal bioclimate and tourism climate potential for central Europe—The example of Luxembourg. Theor. Appl. Climatol., 114, 193202, https://doi.org/10.1007/s00704-013-0835-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matzarakis, A., S. Muthers, and F. Rutz, 2014: Application and comparison of UTCI and PET in temperate climate conditions. Finisterra, 49, 2131, https://doi.org/10.18055/finis6453.

    • Search Google Scholar
    • Export Citation
  • Mayer, H., and P. Höppe, 1987: Thermal comfort of man in different urban environments. Theor. Appl. Climatol., 38, 4349, https://doi.org/10.1007/BF00866252.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mayer, H., J. Holst, P. Dostal, F. Imbery, and D. Schindler, 2008: Human thermal comfort in summer within an urban street canyon in central Europe. Meteor. Z., 17, 241250, https://doi.org/10.1127/0941-2948/2008/0285.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meals, D. W., J. Spooner, S. A. Dressing, and J. B. Harcum, 2011: Statistical analysis for monotonic trends. U.S. Environmental Protection Agency Tech Notes 6, 23 pp., https://www.epa.gov/sites/production/files/2016-05/documents/tech_notes_6_dec2013_trend.pdf.

  • Mislan, K. A. S., and D. S. Wethey, 2011: Gridded meteorological data as a resource for mechanistic macroecology in coastal environments. Ecol. Appl., 21, 26782690, https://doi.org/10.1890/10-2049.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oke, T. R., 1987: Boundary Layer Climates. Routledge, 435 pp.

  • Parker, W. S., 2016: Reanalyses and observations: What’s the difference? Bull. Amer. Meteor. Soc., 97, 15651572, https://doi.org/10.1175/BAMS-D-14-00226.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Parsons, K. C., 2003: Human Thermal Environments: The Effects of Hot, Moderate and Cold Environments on Human Health, Comfort and Performance. Taylor and Francis, 527 pp.

    • Search Google Scholar
    • Export Citation
  • Potchter, O., P. Cohen, T. P. Lin, and A. Matzarakis, 2018: Outdoor human thermal perception in various climates: A comprehensive review of approaches, methods and quantification. Sci. Total Environ., 631–632, 390406, https://doi.org/10.1016/j.scitotenv.2018.02.276.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ricciu, R., A. Galatioto, G. Desogus, and L. A. Besalduch, 2018: Uncertainty in the evaluation of the predicted mean vote index using Monte Carlo analysis. J. Environ. Manage., 223, 1622, https://doi.org/10.1016/j.jenvman.2018.06.005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roshan, G., R. Yousefi, A. Kovács, and A. Matzarakis, 2018: A comprehensive analysis of physiologically equivalent temperature changes of Iranian selected stations for the last half century. Theor. Appl. Climatol., 131, 1941, https://doi.org/10.1007/s00704-016-1950-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salata, F., I. Golasi, R. de Lieto Vollaro, and A. de Lieto Vollaro, 2016: Outdoor thermal comfort in the Mediterranean area. A transversal study in Rome, Italy. Build. Environ., 96, 4661, https://doi.org/10.1016/j.buildenv.2015.11.023.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Semenov, V. A., and M. Latif, 2015: Nonlinear winter atmospheric circulation response to Arctic sea ice concentration anomalies for different periods during 1966–2012. Environ. Res. Lett., 10, 054020, https://doi.org/10.1088/1748-9326/10/5/054020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., A. P. Barrett, J. C. Stroeve, D. N. Kindig, and M. M. Holland, 2009: The emergence of surface-based Arctic amplification. Cryosphere, 3, 1119, https://doi.org/10.5194/tc-3-11-2009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shaposhnikov, D., and Coauthors, 2014: Mortality related to air pollution with the Moscow heat wave and wildfire of 2010. Epidemiology, 25, 359364, https://doi.org/10.1097/EDE.0000000000000090.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shartova, N., and P. Konstantinov, 2019: Climate change adaptation for Russian cities: A case study of the thermal comfort assessment. University Initiatives in Climate Change Mitigation and Adaptation, W. Leal Filho and R. Leal-Arcas, Eds., Springer, 265–267.

    • Crossref
    • Export Citation
  • Smoyer-Tomic, K. E., and D. G. C. Rainham, 2001: Beating the heat: Development and evaluation of a Canadian hot weather health-response plan. Environ. Health Perspect., 109, 12411248, https://doi.org/10.1289/ehp.011091241.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stepanova, N. A., 1958: On the lowest temperatures on Earth. Mon. Wea. Rev., 86, 610, https://doi.org/10.1175/1520-0493(1958)086<0006:OTLTOE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thorsson, S., M. Lindqvist, and S. Lindqvist, 2004: Thermal bioclimatic conditions and patterns of behaviour in an urban park in Göteborg, Sweden. Int. J. Biometeor., 48, 149156, https://doi.org/10.1007/s00484-003-0189-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tilgenkamp, A., 2020: Theil–Sen estimator. MATLAB Central File Exchange, accessed 28 February 2020, https://www.mathworks.com/matlabcentral/fileexchange/34308-theil-sen-estimator.

  • Urban, A., and J. Kyselý, 2014: Comparison of UTCI with other thermal indices in the assessment of heat and cold effects on cardiovascular mortality in the Czech Republic. Int. J. Environ. Res. Public Health, 11, 952967, https://doi.org/10.3390/ijerph110100952.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Hoof, J., 2008: Forty years of Fanger’s model of thermal comfort: Comfort for all? Indoor Air, 18, 182201, https://doi.org/10.1111/j.1600-0668.2007.00516.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Hove, L. W. A., C. M. J. Jacobs, B. G. Heusinkveld, J. A. Elbers, B. L. Van Driel, and A. A. M. Holtslag, 2015: Temporal and spatial variability of urban heat island and thermal comfort within the Rotterdam agglomeration. Build. Environ., 83, 91103, https://doi.org/10.1016/j.buildenv.2014.08.029.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vanos, J. K., J. S. Warland, T. J. Gillespie, and N. A. Kenny, 2010: Review of the physiology of human thermal comfort while exercising in urban landscapes and implications for bioclimatic design. Int. J. Biometeor., 54, 319334, https://doi.org/10.1007/s00484-010-0301-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Varentsov, M., H. Wouters, V. Platonov, and P. Konstantinov, 2018: Megacity-induced mesoclimatic effects in the lower atmosphere: A modeling study for multiple summers over Moscow, Russia. Atmosphere, 9, 50, https://doi.org/10.3390/atmos9020050.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • VDI, 1998: Methods for the human biometeorological evaluation of climate and air quality for the urban and regional planning. Part I: Climate. VDI guideline 3787-2, Verlag des Vereins Deutscher Ingenieure, 32 pp.

  • Vinogradova, V. V., 2009: Bioclimatic indexes in evaluation of modern climate warming on human life conditions of the Russian population. Izv. Akad. Nauk Ser. Geogr., 3, 8289.

    • Search Google Scholar
    • Export Citation
  • Vinogradova V. V., 2019: Universal thermal climate index in Russia. Izv. Ross. Akad. Nauk Ser. Geogr., 2, 319, https://doi.org/10.31857/s2587-5566201923-19.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vinogradova, V. V., and A. N. Zolotokrylin, 2014: Current and future role of climatic factor in the estimation of natural conditions of life in Russia. Izv. Akad. Nauk Ser. Geogr., 4, 1621, https://doi.org/10.15356/0373-2444-2014-4-16-21.

    • Search Google Scholar
    • Export Citation
  • Vitkina, T. I., L. V. Veremchuk, E. E. Mineeva, T. A. Gvozdenko, M. V. Antonyuk, T. P. Novgorodtseva, and E. A. Grigorieva, 2019: The influence of weather and climate on patients with respiratory diseases in Vladivostok as a global health implication. J. Environ. Health Sci. Eng., 17, 907916, https://doi.org/10.1007/s40201-019-00407-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weinberger, K. R., A. Zanobetti, J. Schwartz, and G. A. Wellenius, 2018: Effectiveness of National Weather Service heat alerts in preventing mortality in 20 US cities. Environ. Int., 116, 3038, https://doi.org/10.1016/j.envint.2018.03.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, F., X. Yang, and Z. Shen, 2019: Regional and seasonal variations of outdoor thermal comfort in China from 1966 to 2016. Sci. Total Environ., 665, 10031016, https://doi.org/10.1016/j.scitotenv.2019.02.190.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, J., X. Gao, F. Giorgi, and D. Chen, 2017: Changes of effective temperature and cold/hot days in late decades over China based on a high resolution gridded observation dataset. Int. J. Climatol., 37, 788800, https://doi.org/10.1002/joc.5038.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, J., J. Zha, D. Zhao, and Q. Yang, 2018: Changes in terrestrial near-surface wind speed and their possible causes: An overview. Climate Dyn., 51, 20392078, https://doi.org/10.1007/s00382-017-3997-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, B., T. Olofsson, G. Nair, and A. Kabanshi, 2017: Outdoor thermal comfort under subarctic climate of north Sweden—A pilot study in Umeå. Sustainable Cities Soc., 28, 387397, https://doi.org/10.1016/j.scs.2016.10.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, L., X. Zhou, L. Li, S. He, and R. Chen, 2016: Study on outdoor thermal comfort on a campus in a subtropical urban area in summer. Sustainable Cities Soc., 22, 164170, https://doi.org/10.1016/j.scs.2016.02.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Spatial Patterns of Human Thermal Comfort Conditions in Russia: Present Climate and Trends

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  • 1 Research Computing Center/Faculty of Geography, Lomonosov Moscow State University, and A.M. Obukhov Institute of Atmospheric Physics, Moscow, Russia
  • 2 Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia
  • 3 Faculty of Geography, Lomonosov Moscow State University, and Faculty of Geography and Geoinformatics, Higher School of Economics, Moscow, Russia
  • 4 Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia
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Abstract

The assessment of bioclimatic conditions at the national scale remains a highly relevant task. It might be one of the main parts of the national strategy for the sustainable development of different regions under changing climatic conditions. This study evaluated the thermal comfort conditions and their changes in Russia according to gridded meteorological data from ERA-Interim reanalysis with a spatial resolution of 0.75° × 0.75° using the two most popular bioclimatic indices based on the human energy balance: physiologically equivalent temperature (PET) and universal thermal comfort index (UTCI). We analyzed the summer and winter means of these indices as well as the repeatability of different thermal stress grades for the current climatological standard normal period (1981–2010) and the trends of these parameters over the 1979–2018 period. We revealed the high diversity of the analyzed parameters in Russia as well as significant differences between the contemporary climate conditions and their changes in terms of mean temperature, mean values of bioclimatic indices, and thermal stress repeatability. Within the country, all degrees of thermal stress were possible; however, severe summer heat stress was rare, and in winter nearly the whole country experienced severe cold stress. Multidirectional changes in bioclimatic conditions were observed in Russia against the general background of climate warming. The European part of the country was most susceptible to climate change because it experiences significant changes both in summer and winter thermal stress repeatability. Intense Arctic warming was not reflected in significant changes in thermal stress repeatability.

Corresponding author: Natalia Shartova, shartova@yandex.ru

Abstract

The assessment of bioclimatic conditions at the national scale remains a highly relevant task. It might be one of the main parts of the national strategy for the sustainable development of different regions under changing climatic conditions. This study evaluated the thermal comfort conditions and their changes in Russia according to gridded meteorological data from ERA-Interim reanalysis with a spatial resolution of 0.75° × 0.75° using the two most popular bioclimatic indices based on the human energy balance: physiologically equivalent temperature (PET) and universal thermal comfort index (UTCI). We analyzed the summer and winter means of these indices as well as the repeatability of different thermal stress grades for the current climatological standard normal period (1981–2010) and the trends of these parameters over the 1979–2018 period. We revealed the high diversity of the analyzed parameters in Russia as well as significant differences between the contemporary climate conditions and their changes in terms of mean temperature, mean values of bioclimatic indices, and thermal stress repeatability. Within the country, all degrees of thermal stress were possible; however, severe summer heat stress was rare, and in winter nearly the whole country experienced severe cold stress. Multidirectional changes in bioclimatic conditions were observed in Russia against the general background of climate warming. The European part of the country was most susceptible to climate change because it experiences significant changes both in summer and winter thermal stress repeatability. Intense Arctic warming was not reflected in significant changes in thermal stress repeatability.

Corresponding author: Natalia Shartova, shartova@yandex.ru
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