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

doi:10.1007/s11442-019-1706-y

Abstract

Abstract:

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.

Key words: climate change, tourism climate index, adaptation countermeasures, Tibet

ZHONG Linsheng, YU Hu, ZENG Yuxi. Impact of climate change on Tibet tourism based on tourism climate index[J].Journal of Geographical Sciences, 2019, 29(12): 2085-2100.

Figures/Tables 8

Figure 1

Table 1

Figure 2

Figure 3

Table 2

Figure 4

Figure 5

Figure 6

References 26

1	Amelung B, Nicholls S, Viner D , 2007. Implication of global climate change for tourism flows and seasonality. Journal of Travel Research, 45(5):285-296. doi: 10.1177/0047287506295937
2	Christopher A C, Song F , 2018. A temporal and spatial analysis of climate change, weather events, and tourism businesses. Tourism Management, 67(2):351-361. doi: 10.1016/j.tourman.2018.02.013
3	Defreitas C R , 1979. Human climates of northern China. Atmospheric Environment, 13(1):71-77. doi: 10.1016/0004-6981(79)90246-4 pmid: 420731
4	Du J, Ma P F, Pan D , 2016. Spatial-temporal change of air temperature at 02, 08, 14 and 20 Beijing time over Tibet during 1981-2014. Acta Geographica Sinica, 71(3):422-432. (in Chinese) doi: 10.11821/dlxb201603006
5	Dube K, Nhamo G , 2018. Climate variability, change and potential impacts on tourism: Evidence from the Zambian side of the Victoria Falls. Environmental Science & Policy, 84(3):113-123. doi: 10.1016/j.watres.2019.115345 pmid: 31805498
6	Gonzalez R, Nishi Y, Gagge A , 1974. Experimental evaluation of standard effective temperature: A new biometeorological index of man’s thermal discomfort. International Journal of Biometeorology, 18(1):1-15. doi: 10.1007/bf01450660 pmid: 4845140
7	Gŏssling S, Hall C M , 2005. Tourism and Global Environmental Change: Ecological, Social, Economic and Political Interrelationships. London:Routledge.
8	Hewer M, Scott D, Fenech A , 2016. Seasonal weather sensitivity, temperature thresholds, and climate change impacts for park visitation. Tourism Geographies, 18(3):297-321. doi: 10.1080/14616688.2016.1172662
9	Jaume R N , 2014. How to evaluate the effects of climate change on tourism. Tourism Management, 42:334-340. doi: 10.1016/j.tourman.2013.11.006
10	Jedd T M, Michael J, Carrillo C M et al., 2018. Measuring park visitation vulnerability to climate extremes in U.S. Rockies national parks tourism. Tourism Geographies, 20(2):224-249. doi: 10.1080/14616688.2017.1377283
11	Kubokawa H, Inoue T, Satoh M , 2014. Evaluation of the tourism climate index over Japan in a future climate using a statistical downscaling method. Journal of the Meteorological Society of Japan, 92(1):37-54. doi: 10.2151/jmsj.2014-103
12	Liu Q C, Wang Z, Xu S Y , 2007. Climate suitability index for city tourism in China. Resources Science, 29(1):133-141. (in Chinese)
13	Liu S J, Zhang J H, Wu S A et al., 2014. Possible impact of global climate changes on climate comfort degree and tourist flows in Hainan Island. Journal of Tropical Meteorology, 30(5):977-982. (in Chinese)
14	Ma L J, Sun G N, Li F F et al., 2008. Correlative analysis of climate comfort and monthly variation of tourists in Haikou city. Resources Science, 30(11):1754-1759. (in Chinese)
15	Ma L J, Sun G N, Xie Y F et al., 2010. A study on variations of the tourism climate comfort degree in five typical cities in eastern China during the last 50 years. Resources Science, 32(10):1963-1970. (in Chinese)
16	Matzarakis A , 2014. Transfer of climate data for tourism applications: The Climate-Tourism/Transfer- Information-Scheme. Sustainable Environment Research, 24:273-280.
17	Mieczkowski Z , 1985. The tourism climatic index: A method of evaluating world climates for tourism. The Canadian Geographer, 29:220-233. doi: 10.1111/cag.1985.29.issue-3
18	Pan B T, Li J J , 1997. Qinghai-Tibetan Plateau: A driver and amplifier of the global climate change: The effects of the uplift of Qinghai-Tibetan Plateau on climatic changes. Journal of Lanzhou University (Natural Sciences), 32(1):108-115. (in Chinese)
19	Perry J , 2011. World heritage hot spots: A global model identifies the 16 natural heritage properties on the world heritage list most at risk from climate change. International Journal of Heritage Studies, 17(5):426-441. doi: 10.1080/13527258.2011.568064
20	Scott D, Jones B, Konopek J , 2007. Implications of climate and environmental change for nature-based tourism in the Canadian Rocky Mountains: A case study of Waterton lakes national park. Tourism Management, 28(2):570-579. doi: 10.1016/j.tourman.2006.04.020
21	Scott D, Mcboyle G, Schwartzentruber M , 2004. Climate change and the distribution of climatic resources for tourism in North America. Climate Research, 27(2):105-117. doi: 10.3354/cr027105
22	Susann B, Christian Z, Jordy H , 2015. Developing climate change maps for tourism: essential information or awareness raising? Journal of Travel Research, 54(4):430-441. doi: 10.2196/15000 pmid: 31793889
23	Thom E C , 1959. The discomfort index. Weatherwise, 12(2):57-60. doi: 10.1111/jdv.16131 pmid: 31804196
24	Uhlmann B, Goyette S, Beniston M , 2009. Sensitivity analysis of snow patterns in Swiss ski resorts to shifts in temperature, precipitation and humidity under conditions of climate change. International Journal of Climatology, 29(8):1048-1055. doi: 10.1002/joc.v29:8
25	Yu Z K, Sun G N, Feng Q et al., 2014. Tourism climate comfort and risk for the Qinghai-Tibet Plateau. Resources Science, 36(11):2327-2336. (in Chinese) pmid: 7558729
26	Zhong L S, Tang C C, Cheng S K , 2011. The impact of global climate change on tourism industry in China and adaptive strategies. China Soft Science, ( 2):34-41. (in Chinese)

Temperature-humidity index (THI)		Wind-chill index (WCI)		Index of clothing (ICL)		Altitude adaptation index (AAI)
Classification	Human body sensation	Classification	Human body sensation	Classification	Suitable clothing	Oxygen content of air	Human body sensation
< 40	Extremely cold and uncomfortable	≤ -1000	Extremely cold wind	>2.5	Down coat or fur coat	0 m, 100%	Very comfortable
40-45	Cold and uncomfortable	-800 to -1000	Cold wind	1.8-2.5	Casual clothing plus coat	100 m, 99.2%	Comfortable
45-55	Slightly cold and uncomfortable	-600 to -800	Slightly cold wind	1.5-1.8	Casual winter clothing	1000 m, 92.4%	Quite comfortable
55-60	Cool and comfortable	-300 to -600	Cool wind	1.3-1.5	Casual spring and autumn clothing	2000 m, 84.7%	Generally comfortable
60-65	Cool and very comfortable	-200 to -300	Comfortable wind	0.7-1.3	Shirt and casual clothing	3000 m, 77.1%	Un-comfortable
65-70	Warm and comfortable	-50 to 200	Warm wind	0.5-0.7	Light summer clothing	4000 m, 69.5%	Very un- comfortable
70-75	Rather warm and comfortable	+80 to -50	No sensible wind	0.3-0.5	Short sleeve and open collar shirt	5000 m, 61.8%	Extremely un-comfortable
75-80	Sultry and uncomfortable	+160 to +80	Hot wind	0.1-0.3	Tropical light clothing
> 80	Extremely sultry and uncomfortable	≥ +160	Uncomfortable wind	< 0.1	Extremely light clothing

Year	1960	1965	1970	1975	1980	1985	1990	1995	2000	2005	2010	2015
THI	45.99	44.79	46.09	45.96	45.68	46.29	46.06	46.79	46.30	47.26	48.77	48.13
-WCI	633.35	751.62	806.65	701.05	652.10	645.99	632.68	595.30	582.87	752.03	537.01	591.61
ICL	1.95	2.03	1.96	1.98	1.96	1.93	1.93	1.87	1.88	1.87	1.79	1.78
Month	Dec	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sept	Oct	Nov
THI	36.51	35.57	38.41	42.24	46.29	51.2	55.95	57.32	56.28	53.26	46.73	40.59
-WCI	795.89	878.68	886.00	811.52	705.67	595.93	486.41	438.17	442.7	492.16	618.46	719.59
ICL	2.51	2.62	2.47	2.20	1.92	1.60	1.33	1.25	1.30	1.45	1.83	2.24

[1]	Martha Elizabeth APPLE, Macy Kara RICKETTS, Alice Caroline MARTIN. Plant functional traits and microbes vary with position on striped periglacial patterned ground at Glacier National Park, Montana [J]. Journal of Geographical Sciences, 2019, 29(7): 1127-1141.
[2]	Yuan ZHANG, Shuying ZANG, Li SUN, Binghe YAN, Tianpeng YANG, Wenjia YAN, E Michael MEADOWS, Cuizhen WANG, Jiaguo QI. Characterizing the changing environment of cropland in the Songnen Plain, Northeast China, from 1990 to 2015 [J]. Journal of Geographical Sciences, 2019, 29(5): 658-674.
[3]	Yujie LIU, Ya QIN, Quansheng GE. Spatiotemporal differentiation of changes in maize phenology in China from 1981 to 2010 [J]. Journal of Geographical Sciences, 2019, 29(3): 351-362.
[4]	CHEN Qiong, LIU Fenggui, CHEN Ruijie, ZHAO Zhilong, ZHANG Yili, CUI Peng, ZHENG Du. Trends and risk evolution of drought disasters in Tibet Region, China [J]. Journal of Geographical Sciences, 2019, 29(11): 1859-1875.
[5]	TIAN Yuan, YU Chengqun, ZHA Xinjie, GAO Xing, DAI Erfu. Hydrochemical characteristics and controlling factors of natural water in the border areas of the Qinghai-Tibet Plateau [J]. Journal of Geographical Sciences, 2019, 29(11): 1876-1894.
[6]	WANG Yunsheng, ZHENG Mianping, YAN Lijuan, BU Lingzhong, QI Wen. Influence of the regional climate variations on lake changes of Zabuye, Dangqiong Co and Bankog Co salt lakes in Tibet [J]. Journal of Geographical Sciences, 2019, 29(11): 1895-1907.
[7]	Danyang MA, Haoyu DENG, Yunhe YIN, Shaohong WU, Du ZHENG. Sensitivity of arid/humid patterns in China to future climate change under a high-emissions scenario [J]. Journal of Geographical Sciences, 2019, 29(1): 29-48.
[8]	Man ZHANG, Yaning CHEN, Yanjun SHEN, Baofu LI. Tracking climate change in Central Asia through temperature and precipitation extremes [J]. Journal of Geographical Sciences, 2019, 29(1): 3-28.
[9]	Jing ZHANG, Yanjun SHEN. Spatio-temporal variations in extreme drought in China during 1961-2015 [J]. Journal of Geographical Sciences, 2019, 29(1): 67-83.
[10]	Haijun DENG, Yaning CHEN, Yang LI. Glacier and snow variations and their impacts on regional water resources in mountains [J]. Journal of Geographical Sciences, 2019, 29(1): 84-100.
[11]	Weijie HU, Hailong LIU, Anming BAO, M. El-Tantawi Attia. Influences of environmental changes on water storage variations in Central Asia [J]. Journal of Geographical Sciences, 2018, 28(7): 985-1000.
[12]	Yichun XIE, Yang ZHANG, Hai LAN, Lishen MAO, Shi ZENG, Yulu CHEN. Investigating long-term trends of climate change and their spatial variations caused by regional and local environments through data mining [J]. Journal of Geographical Sciences, 2018, 28(6): 802-818.
[13]	Wenxia ZHANG, , Qingrong FENG, Tianguang WANG, Tianqiang WANG. The spatiotemporal responses of Populus euphratica to global warming in Chinese oases between 1960 and 2015 [J]. Journal of Geographical Sciences, 2018, 28(5): 579-594.
[14]	Xiaojun YAO, Meiping SUN, Peng GONG, Baokang LIU, Xiaofeng LI, Lina AN, Luxia YAN. Overflow probability of the Salt Lake in Hoh Xil Region [J]. Journal of Geographical Sciences, 2018, 28(5): 647-655.
[15]	Yang FU, Hui CHEN, Huihui NIU, Siqi ZHANG, Yi YANG. Spatial and temporal variation of vegetation phenology and its response to climate changes in Qaidam Basin from 2000 to 2015 [J]. Journal of Geographical Sciences, 2018, 28(4): 400-414.