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利用天气综合类型预测亚特兰大和印第安纳波利斯动物园的游客人数。

Using synoptic weather types to predict visitor attendance at Atlanta and Indianapolis zoological parks.

机构信息

George Mason University Center for Climate Change Communication, Fairfax, VA, USA.

出版信息

Int J Biometeorol. 2018 Jan;62(1):127-137. doi: 10.1007/s00484-016-1142-y. Epub 2016 Feb 23.

Abstract

Defining an ideal "tourism climate" has been an often-visited research topic where explanations have evolved from global- to location-specific indices tailored to tourists' recreational behavior. Unfortunately, as indices become increasingly specific, they are less translatable across geographies because they may only apply to specific activities, locales, climates, or populations. A key need in the future development of weather and climate indices for tourism has been a translatable, meteorologically based index capturing the generalized ambient atmospheric conditions yet considering local climatology. To address this need, this paper tests the applicability of the spatial synoptic classification (SSC) as a tool to predict visitor attendance response in the tourism, recreation, and leisure (TRL) sector across different climate regimes. Daily attendance data is paired with the prevailing synoptic weather condition at Atlanta and Indianapolis zoological parks from September 2001 to June 2011, to review potential impacts ambient atmospheric conditions may have on visitor attendances. Results indicate that "dry moderate" conditions are most associated with high levels of attendance and "moist polar" synoptic conditions are most associated with low levels of attendance at both zoological parks. Comparing visitor response at these zoo locations, visitors in Indianapolis showed lower levels of tolerance to synoptic conditions which were not "ideal." Visitors in Indianapolis also displayed more aversion to "polar" synoptic regimes while visitors in Atlanta displayed more tolerance to "moist tropical" synoptic regimes. Using a comprehensive atmospheric measure such as the SSC may be a key to broadening application when assessing tourism climates across diverse geographies.

摘要

定义理想的“旅游气候”一直是一个经常被探讨的研究课题,其解释已经从全球到针对游客娱乐行为的特定地点的指数演变而来。不幸的是,随着指数变得越来越具体,它们在地域上的可翻译性就越低,因为它们可能只适用于特定的活动、地点、气候或人群。未来旅游天气和气候指数的一个关键需求是一个可翻译的、基于气象的指数,该指数既能捕捉广义的环境大气条件,又能考虑当地气候学。为了满足这一需求,本文测试了空间天气分类(SSC)作为一种工具的适用性,该工具可预测不同气候条件下旅游、娱乐和休闲(TRL)部门的游客出勤率。将每天的出勤数据与 2001 年 9 月至 2011 年 6 月亚特兰大和印第安纳波利斯动物园的盛行天气条件进行配对,以审查环境大气条件对游客出勤人数可能产生的潜在影响。结果表明,“干燥适中”的条件与高出勤率最相关,而“湿润极地”的天气条件与两个动物园的低出勤率最相关。比较这些动物园的游客反应,印第安纳波利斯的游客对不理想的天气条件的容忍度较低。印第安纳波利斯的游客对极地天气模式表现出更多的反感,而亚特兰大的游客对潮湿热带天气模式表现出更多的容忍。使用综合大气测量方法,如 SSC,可能是在评估不同地理位置的旅游气候时扩大应用的关键。

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