Spatial-Temporal Characteristics of Arctic Summer Climate Comfort Level in the Context of Regional Tourism Resources from 1979 to 2019

Huang, Yutao; Zhang, Xuezhen; Zhang, Dan; Zhang, Lijuan; Zhang, Wenshuai; Ren, Chong; Pan, Tao; Chen, Zheng; Chen, Yuying

doi:10.3390/su132313056

Cited by 8 publications

(5 citation statements)

References 45 publications

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“…Similarly, research by Mohammed in North Africa and the Middle East found UTCI values ranging from 0 • C to 32 • C, with an increasing trend of 0.1 • C to 0.7 • C decade −1 [28]. In the Arctic, the average UTCI was found to be 0.025 • C, and it has shown a significant increase at a rate of 0.457 • C decade −1 during the summer [29]. In Russia, thermal stress ranges from extreme cold stress to moderate heat stress in summer, and the distribution and trend of thermal stress are primarily related to air temperature.…”

Section: Introductionmentioning

confidence: 79%

Spatial–Temporal Characteristics of Human Thermal Comfort in Xinjiang: Based on the Universal Thermal Climate Index from 1981 to 2019

Qi,

Yang,

Han

et al. 2023

Land

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Xinjiang is one of the world’s most sensitive and vulnerable regions to climate change. However, little is known about the current status and changes in thermal comfort conditions in this area. Using the Universal Thermal Climate Index (UTCI) derived from the newly available high-resolution dataset HiTiSEA, the spatial–temporal pattern and changes thereof over annual and seasonal scales across Xinjiang from 1981 to 2019 were evaluated. The results reveal that the distribution and change of thermal comfort in Xinjiang have apparent regional heterogeneity and seasonal characteristics. Across all scales, 7 of 10 UTCI thermal stress categories were observed, from slight cold stress to strong heat stress. Annually, the mean UTCI is 3 °C and has significantly increased at 0.37 °C decade−1. The mean number of comfortable days (CDs) is 114 days, with a range from 0 to 189 days. On the space scale, the Tarim Basin experiences the highest UTCI value, while the Ili River Valley, the north side of the Tianshan Mountains, and the peripheral areas of the Tarim Basin have a higher number of CDs. Seasonally, summer has the highest UTCI value, while winter is the lowest. The trend for all seasons is upward, and spring increases fastest. Results also indicate that air temperature has a positive correlation with climate comfort, and the influence of air temperature on climate comfort is most significant. Further research indicates that the range and intensity of population exposure to uncomfortable climates in Xinjiang have increased. The distribution and expansion of population exposure are similar to the population density. These findings contribute to a systematic understanding of the local climate environment and can be helpful for the assessment of the impact of climate change and optimize tourism development.

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Section: Introductionmentioning

confidence: 79%

Spatial–Temporal Characteristics of Human Thermal Comfort in Xinjiang: Based on the Universal Thermal Climate Index from 1981 to 2019

Qi,

Yang,

Han

et al. 2023

Land

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“…In order to explore the linear trends of Tmax and HWEs, linear regression was carried out. It has been a common method to determine the long-term linear trend of a certain meteorological variable [47,48]:…”

Section: Regression Analysismentioning

confidence: 99%

High-Resolution Regional Climate Modeling and Projection of Heatwave Events over the Yangtze River Basin

Gao

Yan

2022

Sustainability

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Heatwave events (HWEs) have strong impacts on human health, ecosystems, and sustainable social development. Using a gridded observation dataset and a high-resolution regional climate model (RCM), this study analyzed the characteristics of HWEs over the Yangtze River Basin (YRB) in eastern China during the historical period and projected the changes in HWEs over the YRB in the future. The daily maximum temperature (Tmax), long-lived (≥6 days) HWEs, and total (≥3 days) HWEs in the YRB all showed an obvious upward trend from 1981 to 2018, while the increase in short-lived (≥3 days and <6 days) HWEs was relatively moderate overall. The RCM of the Weather Research and Forecasting (WRF) model can simulate the characteristics of Tmax and HWEs in the historical period very well, and the projection results showed that Tmax, total HWEs, and long-lived HWEs will all increase obviously in both the SSP245 and SSP585 scenarios. Short-lived HWEs will also increase rapidly under SSP585, but they will rise slowly overall under SSP245. The changes in HWEs had distinct regional differences, and the intensity and coverage area of HWEs were greater under SSP585 overall. In the future, the increase in HWEs over the YRB region is likely to be associated with the enhancement of the western-Pacific subtropical high (WPSH) and South-Asian high (SAH), and this enhancement was also greater under SSP585. The results from the high-resolution simulation of the RCM can provide an important reference for disaster prevention and mitigation in the future.

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“…The UTCI has many advantages and shortcomings (Błażejczyk et al 2012 ; Błażejczyk and Kuchcik 2021 ). Among other considerations, the UTCI has important advantages: (i) it is expressed in °C—a unit of measurement that is understandable not only to specialists, but also to the broader public; and (ii) it can be used in a huge temperature range from below −50°C and up to higher than +50°C (Błażejczyk et al 2012 ; de Freitas and Grigorieva 2017 ; Błażejczyk and Kuchcik 2021 ) and applied around the world, enabling direct comparisons of results for different areas: in Europe (Antonescu et al 2021 ), in the Caribbean (Di Napoli et al 2022 ), in the Arctic (Mölders 2019 ; Shartova et al 2019 ; Huang et al 2021 ), China (Mi et al 2020 ; An et al 2021 ; Wang and Yi 2021 ; Liu et al 2022 ), Japan (Ohashi et al 2018 ), Russia (Shartova et al 2019 ; Konstantinov et al 2020 ; Vinogradova 2021 ). The UTCI has been used in a variety of applications (Krüger 2021 ), including medical science (Shartova et al 2019 ; Urban et al 2021 ; Romaszko et al 2022 ), tourism (Huang et al 2021 ), and in urban planning (Krüger 2021 ).…”

Section: Introductionmentioning

confidence: 99%

“…Vinogradova ( 2021 ) evaluated climatological and extreme values of the UTCI for a network of surface stations in Russia, but temporal variations and trends were not considered. Huang et al ( 2021 ) documented Arctic-averaged variations of the UTCI computed from the ERA5 reanalysis, but study area was limited to 65–90°N, and most of results were presented as averages over all or parts of the land areas north of 65° N.…”

Section: Introductionmentioning

confidence: 99%

“…Climate warming can seriously change bioclimate, potentially decreasing the period with exceptionally low temperatures on one hand, but improving the intervals with comfortable conditions, which are very important for both inhabitants (Mölders 2019;Konstantinov et al 2020) and tourists traveling to the Arctic (Huang et al 2021). This change in bioclimate is very important, especially given the growing demand for tourism development in the Arctic, and in particular in Alaska and Chukotka.…”

Section: Introductionmentioning

confidence: 99%

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Universal thermal climate index in the Arctic in an era of climate change: Alaska and Chukotka as a case study

Grigorieva,

Alexeev,

Walsh

2023

Int J Biometeorol

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The modern unambiguous climate change reveals in a rapid increase of air temperature, which is more distinctly expressed in the Arctic than in any other part of the world, affecting people health and well-being. The main objective of the current research is to explore the inter- and intra-annual changes in thermal stress for people in the Arctic, specifically for two parts of Beringia: Alaska, USA, and Chukotka, Russia, using climatology of the universal thermal climate index (UTCI). Data for 39 locations are taken from the ERA5-HEAT reanalysis for the period 1979–2020. Climatologically, the study area is divided into four subregions in Alaska: North, Interior, West and South, and two in Chukotka: Interior and Coast. The extreme coldest UTCI categories (1 and 2) are most common in coastal locations of northern Alaska and Chukotka, where strong winds exacerbate the low temperatures during winter. The results show that the frequency of category 1 (UTCI<−40°C) varies spatially from a quarter of all hours annually in Alaska North to almost zero in Alaska South. On the other hand, the warmest categories are rarely reached almost everywhere in Alaska and Chukotka, and even categories 7 and 8 (UTCI between +26 and +38°C) are found occasionally only at interior locations. Category 6 with no thermal stress (UTCI between +9 and+26°C) has frequencies up to 3% and 25% in Alaska North and Interior, respectively. The extremely cold thermal stress frequencies have substantially decreased over the 1979–2020 period, especially in Alaska North and Chukotka Coast. At the same time, the number of hours with UTCI in the comfortable category of thermal perception has increased depending on subregion, from 25 to 203 h/year. Overall, a decrease in the UTCI categories of extremely cold stress is coupled with an increase in the comfortable range in both Alaska and Chukotka. The salient conclusion is that, from the point of view of comfort and safety, global warming has a positive impact on the climatology of thermal stress in the Arctic, providing advantages for the development of tourism and recreation.

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Spatial-Temporal Characteristics of Arctic Summer Climate Comfort Level in the Context of Regional Tourism Resources from 1979 to 2019

Cited by 8 publications

References 45 publications

Spatial–Temporal Characteristics of Human Thermal Comfort in Xinjiang: Based on the Universal Thermal Climate Index from 1981 to 2019

Spatial–Temporal Characteristics of Human Thermal Comfort in Xinjiang: Based on the Universal Thermal Climate Index from 1981 to 2019

High-Resolution Regional Climate Modeling and Projection of Heatwave Events over the Yangtze River Basin

Universal thermal climate index in the Arctic in an era of climate change: Alaska and Chukotka as a case study

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