Evaluation of outdoor thermal comfort conditions in northern Russia over 30-year period: Arkhangelsk region

The aim of the current paper is to evaluate spatial and temporal characteristics of the distribution of bioclimatic comfort within the Arkhangelsk region (Russian Federation) with two modern indices of thermal comfort: PET and UTCI. Its average values calculated for the modern climatic period (1981-...

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Bibliographic Details
Published in:Geographica Pannonica
Main Authors: Konstantinov Pavel, Shartova Natalia, Varentsov Mikhail, Revich Boris
Format: Article in Journal/Newspaper
Language:English
Published: University of Novi Sad, Department of Geography, Tourism and Hotel Management 2020
Subjects:
pet
geo
Online Access:https://doi.org/10.5937/gp24-24738
https://scindeks-clanci.ceon.rs/data/pdf/0354-8724/2020/0354-87242004252K.pdf
https://doaj.org/article/6490fcbbfe3e479c8378ec3c9847e1ed
Description
Summary:The aim of the current paper is to evaluate spatial and temporal characteristics of the distribution of bioclimatic comfort within the Arkhangelsk region (Russian Federation) with two modern indices of thermal comfort: PET and UTCI. Its average values calculated for the modern climatic period (1981-2010) in the monthly mean give a clear picture of spatial heterogeneity for the warmest month (July) and for the coldest one (January). The spatial picture of both indices in July allows us to distinguish three large internal regions: the Arkhangelsk province, the continental part of the Nenets Autonomous Okrug (NAO) and Novaya Zemlya islands (NZ). Winter distribution of thermal discomfort is fundamentally different: the coldest regions (with extreme cold stress) are equally NZ and the Eastern half of NAO; intermediate position is occupied by the West of the NAO and the extreme northeast of the Arkhangelsk region, the highest winter UTCI values are observed in the rest of the region. In Archangelsk-city extreme cold stress in January has repeatability 6.7%, in February-4%, in December-2.2%, respectively. The average number of time points during the year at which thermal stress is not observed is only 19%. Obtained results will be the basis for planning relevant health measures and providing reliable forecasts of the effects of climate change in the Arctic region.