Seasonal weather sensitivity, temperature thresholds, and climate change impacts for park visitation

Hewer, Micah J.; Scott, Daniel; Fenech, Adam

doi:10.1080/14616688.2016.1172662

Cited by 63 publications

(42 citation statements)

References 33 publications

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“…This finding has important implications for previous studies that combined many months or even multiple seasons into one season for analysis, especially modeling-based studies that defined weather sensitivity and held that statistical relationship constant within their predictive models. For example, Jones and Scott [14,15] modeled the peak and shoulder seasons for park visitation separately, which was good, but the shoulder season was likely too large and needed to be separated to include an off season, as tourism participation does not respond in the same way to weather and climate variability in the spring as it does in the winter [23,33]. Furthermore, Hewer and Gough [5,6] modeled zoo attendance using an off-season and shoulder-season and peak-season model, which was an improvement, but both this study and the analogue study of Hewer and Gough [9] demonstrate that tourism participation does not respond in the same way to weather and climate variability in the spring as it does in the autumn, thus requiring the shoulder seasons to be modeled/analyzed separately.…”

Section: Discussionmentioning

confidence: 99%

“…With only seven studies to date, zoos and aquariums have only begun to be studied in the context of tourism climatology. Despite findings suggesting that zoo and aquarium attendance is highly sensitive to weather and climate variability, other activities, such as visiting parks and protected areas, have received much more attention internationally within the tourism climatology literature [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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Determining the Effect of Extreme Weather Events on Human Participation in Recreation and Tourism: A Case Study of the Toronto Zoo

Hewer

2020

Atmosphere

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This study devises a novel approach for defining extreme weather events and assessing their effects on human participation in recreation and tourism, based on a case study of attendance at the Toronto Zoo (Toronto, ON, Canada). Daily zoo attendance data from 1999 to 2018 was obtained and analyzed in connection with daily weather data from local weather stations for the maximum temperature, minimum temperature, total precipitation, and maximum wind speed. The “climatic distance” method, used for evaluating representative weather stations for case studies in applied climatology, was employed to rank and select surrounding weather stations that most accurately captured daily weather observations recorded at the Toronto Zoo from 1990 to 1992. Extreme weather events can be defined as lying in the outermost (most unusual) 10 percent of a place’s history. Using this definition as the foundation, a percentile approach was developed to identify and assess the effects of extreme weather events across the following thresholds: the 99th percentile, the 95th percentile, and the 90th percentile, as well as less than the 1st percentile, less than the 5th percentile, and less than the 10th percentile. Additionally, revealed, theoretical, and binary thresholds were also assessed to verify their merit and determine their effects, and were compared to the extreme weather events defined by the percentiles approach. Overall, extreme daily weather events had statistically significant negative effects on zoo attendance in Toronto, apart from a few cases, such as the positive effect of usually warm daytime temperatures in the winter and usually cool nighttime temperatures in the summer. The most influential weather event across all seasons was extremely hot temperatures, which has important implications for climate change impact assessments.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determining the Effect of Extreme Weather Events on Human Participation in Recreation and Tourism: A Case Study of the Toronto Zoo

Hewer

2020

Atmosphere

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“…In the last ten years, research has increasingly aimed at identifying the ideal or preferred weather conditions for different tourist activities, such as visiting the zoo [21][22][23]; travelling to ski and mountain environments [24][25][26]; camping [12,27]; visiting parks [28]; and tourism in urban destinations [29]. The relationship between climate and tourism is particularly close in the case of beach tourism, where climate has repeatedly been identified as a critical pull factor [30][31][32].…”

Section: Tourism Climate Weather and Seasonalitymentioning

confidence: 99%

Influence of Weather on the Behaviour of Tourists in a Beach Destination

2020

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In sun-and-beach destinations, weather has a decisive influence on the variability of the daily flow of tourists. Uncertainty in demand flows directly affects businesses and employment. This work aims to improve understanding of the behaviour of tourists in response to changes in weather conditions. The analysis is carried out in the Rías Baixas, a sun-and-beach destination in north-west Spain. The paper analyses the relationship of weather conditions with daily flows during the high season at the main tourist beaches in the area, also considering two beach typologies. The density of beach use is measured three times a day through the analysis of webcam images in combination with real-time weather, and an online survey is conducted among tourists who have visited these beaches. The results show that the hours of sunshine are the most influential weather factor. Weather forecast greatly or totally influenced the decision to go to the beach for almost 70% of respondents and about 80% of the respondents checked on the weather before visiting a beach.

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“…Since 2000, Amelung et al (2007), and Kubokawa et al (2014) have used the tourism climate index to predict changes in climate attractiveness. Hewer et al (2016) and Jedd et al (2018) tried to construct a correlation model between climate and tourist flows, and analyzed the impact of temperature changes on the scale of tourism flows. In the past few decades, many quantitative studies have attempted to evaluate the impact of climate change on tourism from the single-factor constructed climate comfort level assessment model, and divided the climate suitability of different types of tourist destinations (Liu et al, 2007;Liu et al, 2014), wherein the index used includes temperature-humidity index (THI), wind-chill index (WCI), and index of clothing (ICL).…”

Section: Introductionmentioning

confidence: 99%

Impact of climate change on Tibet tourism based on tourism climate index

Zhong

Zeng

2019

J. Geogr. Sci.

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Climate change is an important factor affecting the sustainable development of tourist destinations. Based on the monthly observation data of the main meteorological stations on the ground in Tibet from 1960 to 2015, this paper constructs a tourism climate index model. This index is used to quantitatively evaluate the tourism climate changes in Tibet, and investigate the impact of climate change on tourism. The results show that from 1960 to 2015, the temperature in Tibet increased by 1.35°C, and the tourism climate index changed significantly, especially in the regions of Changtang, Ngari and Kunlun Mountain. The fluctuation of temperature-humidity index, wind-chill index and index of clothing of these areas was larger than that of other regions. The changes of each index in different months are different, where spring observes larger changes while summer observes smaller changes. The tourism climate index in northwestern Tibet has increased, and the climate comfort period is expanding. In southeastern Tibet, the comfort level has declined and the comfort level in the central part has been slowly increasing. The comfort index in the southeastern part of Tibet has gradually declined, and the comfort index in central Tibet has slowly increased. According to the comprehensive assessment method including temperature and humidity index, wind-chill index, index of clothing and altitude adaptability index, the types of tourism climate index in Tibet can be divided into reduced, low-speed growth, medium-speed growth and rapid growth. Different regions should adopt alternative tourism products, strengthen energy conservation and emission reduction technology applications and green infrastructure construction, and appropriately control the scale of tourism activities so as to adapt to and mitigate the impact of climate change on tourist destinations.

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Seasonal weather sensitivity, temperature thresholds, and climate change impacts for park visitation

Cited by 63 publications

References 33 publications

Determining the Effect of Extreme Weather Events on Human Participation in Recreation and Tourism: A Case Study of the Toronto Zoo

Determining the Effect of Extreme Weather Events on Human Participation in Recreation and Tourism: A Case Study of the Toronto Zoo

Influence of Weather on the Behaviour of Tourists in a Beach Destination

Impact of climate change on Tibet tourism based on tourism climate index

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