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滑雪气候指数(SCI):土耳其的模糊化及区域气候建模应用

The Ski Climate Index (SCI): fuzzification and a regional climate modeling application for Turkey.

作者信息

Demiroglu Osman Cenk, Turp Mustafa Tufan, Kurnaz Mehmet Levent, Abegg Bruno

机构信息

Department of Geography and Arctic Research Centre (ARCUM), Umeå University, 901 87, Umeå, Sweden.

Center for Climate Change and Policy Studies, Bogazici University, 34342, Istanbul, Turkey.

出版信息

Int J Biometeorol. 2021 May;65(5):763-777. doi: 10.1007/s00484-020-01991-0. Epub 2020 Aug 26.

Abstract

Climatology has increasingly become an important discipline for understanding tourism and recreation, especially in the era of contemporary climate change. Climate indices, in this respect, have been useful tools to yield the climatic attractiveness of tourism destinations as well as in understanding their altering suitability to various tourism types along with the changing climates. In this study, a major gap for a comprehensive climate index tailored for ski tourism is aimed to be fulfilled. For this purpose, initially the Ski Climate Index (SCI) is specified, based on fuzzy logic and as informed by literature and through extensive co-creation with the ski tourism industry experts, and applied to an emerging destination, Turkey, based on regional climate modeling projections. The index is designed as a combination of snow reliability and aesthetics and comfort facets, the latter of which includes sunshine, wind, and thermal comfort conditions. Results show that the Eastern Anatolia region is climatically the most suitable area for future development, taking account of the overriding effects of natural and technical snow reliability. Future research suggestions include the incorporation of more components into the index as well as technical recommendations to improve its application and validation.

摘要

气候学日益成为理解旅游和休闲的重要学科,尤其是在当代气候变化的时代。在这方面,气候指数一直是评估旅游目的地气候吸引力以及了解随着气候的变化其对各种旅游类型适宜性变化的有用工具。在本研究中,旨在填补为滑雪旅游量身定制的综合气候指数方面的一个主要空白。为此,首先基于模糊逻辑、参考文献并通过与滑雪旅游业专家广泛共同创建,确定了滑雪气候指数(SCI),并基于区域气候模型预测将其应用于新兴目的地土耳其。该指数被设计为雪的可靠性与美学和舒适度方面的组合,后者包括日照、风以及热舒适条件。结果表明,考虑到自然和技术雪可靠性的首要影响,东安纳托利亚地区在气候上是未来发展最合适的地区。未来的研究建议包括将更多要素纳入该指数,以及提出改进其应用和验证的技术建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f966/8116266/17b5a27ba403/484_2020_1991_Fig1_HTML.jpg

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