Abstract

This work analyses the temporal and spatial characteristics of bioclimatic conditions in the Lower Silesia region. The daily time values (12UTC) of meteorological variables in the period 1966–2017 from seven synoptic stations of the Institute of Meteorology and Water Management (IMGW) (Jelenia Góra, Kłodzko, Legnica, Leszno, Wrocław, Opole, Śnieżka) were used as the basic data to assess the thermal stress index UTCI (Universal Thermal Climate Index). The UTCI can be interpreted by ten different thermal classes, representing the bulk of these bioclimatic conditions. Stochastic autoregressive moving-average modelling (ARMA) was used for the statistical analysis and modelling of the UTCI as well as separately for all meteorological components. This made it possible to test differences in predicting UTCI as a full index or reconstructing it from single meteorological variables. The results show an annual and seasonal variability of UTCI for the Lower Silesia region. Strong significant spatial correlations in UTCI were also found in all stations of the region. “No thermal stress” is the most commonly occurring thermal class in this region (about 38%). Thermal conditions related to cold stress classes occurred more frequently (all cold classes at about 47%) than those of heat stress classes (all heat classes at about 15%). Over the available 52-year period, the occurrence of “extreme heat stress” conditions was not detected. Autoregressive analysis, although successful in predicting UTCI, was nonetheless unsuccessful in reconstructing the wind speed, which showed a persistent temporal correlation possibly due to its vectorial origin. We conclude thereby that reconstructing UTCI using linear autoregressive methods is more suitable when working directly on the UTCI as a whole rather than reconstructing it from single variables.

Highlights

  • Bioclimatology finds applications in many fields such as climate change (Wu et al 2019), health research (Brode et al 2018), epidemiology (Di Napoli et al 2018), military (Galan and Guedes 2019), and urban planning or even to determine the attractiveness of tourist places such as coastal towns or health resorts (Błazejczyk and Kunert 2011b; Ge et al 2017)

  • The Lower Silesia region accounts for about 20% of all health resorts in Poland to which tourists and the sick go in order to recover or improve their health conditions

  • We show how statistics of biometeorological conditions are related to the available synoptic stations in the Lower Silesia region

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Summary

Introduction

Bioclimatology finds applications in many fields such as climate change (Wu et al 2019), health research (Brode et al 2018), epidemiology (Di Napoli et al 2018), military (Galan and Guedes 2019), and urban planning or even to determine the attractiveness of tourist places such as coastal towns or health resorts (Błazejczyk and Kunert 2011b; Ge et al 2017). There are still many locations that do not possess historical records of meteorological measurements. Forecast for these regions, often including cities or attractive areas, relies purely on extrapolation from the modelled data. Despite the fact that only a few of those health resorts have historical records of meteorological measurements, all resorts are required to periodically report on the biometeorological conditions in the region so as to obtain standard certifications

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