Abstract
Climate is an important tourism resource and a vital component of the attractiveness of a destination. Climate has a strong impact on supply and demand in the tourism industry. Most studies concerning the distribution of tourism climate resources are based on point measurements from meteorological stations. Tourism climate distribution maps with high resolution are required. In this paper, the tourism climate index (TCI) and spatial interpolation based on polynomial regression are used to analyze the distribution of summer tourism climate resources in China. The results indicate that there exists an obvious positive linear relationship between the TCI and latitude and a quadratic relationship between the TCI and elevation. The tourism climate is unfavorable in 8% of the study area, acceptable in 34% of the study area, good and very good in 36% of the study area, and excellent in 22% of the study area. From the perspective of climate, the places comfortable for summer tourism are mainly concentrated to the north of 35°N, on the second elevation step, and in the temperate continental climate zone. The tourism climate information provided is accurate at the 90% level for most areas.
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References
Amelung B, Nicholls S (2014) Implications of climate change for tourism in Australia. Tour Manag 41:228–244. https://doi.org/10.1016/j.tourman.2013.10.002
Amelung B, Viner D (2006) Mediterranean tourism: exploring the future with the tourism climatic index. J Sustain Tour 14:349–366. https://doi.org/10.2167/jost549.0
Becken S (2012) Measuring the effect of weather on tourism. J Travel Res 52:156–167. https://doi.org/10.1177/0047287512461569
Becken S, Wilson J (2013) The impacts of weather on tourist travel. Tour Geogr 15:620–639. https://doi.org/10.1080/14616688.2012.762541
Bujosa A, Riera A, Torres CM (2015) Valuing tourism demand attributes to guide climate change adaptation measures efficiently: the case of the Spanish domestic travel market. Tour Manag 47:233–239. https://doi.org/10.1016/j.tourman.2014.09.023
Cao Y, Gao L, Wang X (2016) Climate comfort regional characteristics in summer in Liaoning during past 30 years. Sci Geogr Sin 36:1205–1211. https://doi.org/10.13249/j.cnki.sgs.2016.08.011
Carod-Artal FJ (2014) High-altitude headache and acute mountain sickness. Neurología 29:533–540. https://doi.org/10.1016/j.nrleng.2012.04.021
China National Tourism Adminstration (2016) The year book of China tourism statistics 2016. China Travel and Tourism Press, Beijing
Davis NE (1968) An optimum summer weather index. Weather 23:305–317. https://doi.org/10.1002/j.1477-8696.1968.tb07379.x
Deng W, Cheng G, Wen A (2008) The conception of mountain science development in China. Bull Chin Acad Sci 23:156–161. https://doi.org/10.16418/j.issn.1000-3045.2008.02.001
Dylla L et al (2017) Along the Colorado Trail: assessing the average hikers’ knowledge of altitude sickness. Am J Emerg Med. https://doi.org/10.1016/j.ajem.2017.10.011
Eugenio-Martin JL, Campos-Soria JA (2010) Climate in the region of origin and destination choice in outbound tourism demand. Tour Manag 31:744–753. https://doi.org/10.1016/j.tourman.2009.07.015
Fang Y, Yin J (2015) National assessment of climate resources for tourism seasonality in China using the tourism climate index. Atmosphere 6:183–194. https://doi.org/10.3390/atmos6020183
Fitchett JM, Robinson D, Hoogendoorn G (2017) Climate suitability for tourism in South Africa. J Sustain Tour 25:851–867. https://doi.org/10.1080/09669582.2016.1251933
de Freitas CR (2003) Tourism climatology: evaluating environmental information for decision making and business planning in the recreation and tourism sector. Int J Biometeorol 48:45–54. https://doi.org/10.1007/s00484-003-0177-z
de Freitas CR, Grigorieva EA (2015) A comprehensive catalogue and classification of human thermal climate indices. Int J Biometeorol 59:109–120. https://doi.org/10.1007/s00484-014-0819-3
de Freitas CR, Scott D, McBoyle G (2008) A second generation climate index for tourism (CIT): specification and verification. Int J Biometeorol 52:399–407. https://doi.org/10.1007/s00484-007-0134-3
Ge Q, Kong Q, Xi J, Zheng J (2016) Application of UTCI in China from tourism perspective. Theo Appl Climatol 128:551–561. https://doi.org/10.1007/s00704-016-1731-z
Goh C (2012) Exploring impact of climate on tourism demand. Ann Tour Res 39:1859–1883. https://doi.org/10.1016/j.annals.2012.05.027
Gonggalanzi et al (2016) Acute mountain sickness among tourists visiting the high-altitude city of Lhasa at 3658 m above sea level: a cross-sectional study. Arch Public Health 74:23. https://doi.org/10.1186/s13690-016-0134-z
Gu S, Huang C, Bai L, Chu C, Liu Q (2016) Heat-related illness in China, summer of 2013. Int J Biometeorol 60:131–137. https://doi.org/10.1007/s00484-015-1011-0
Hoppe PR (1993) Heat balance modeling. Experienti 49:741–746. https://doi.org/10.1007/bf01923542
Hu L, Huang G, Qu X (2016) Spatial and temporal features of summer extreme temperature over China during 1960–2013. Theo Appl Climatol 128:821–833. https://doi.org/10.1007/s00704-016-1741-x
Jendritzky G, de Dear R, Havenith G (2012) UTCI—why another thermal index? Int J Biometeorol 56:421–428. https://doi.org/10.1007/s00484-011-0513-7
Ketterer C, Matzarakis A (2016) Mapping the physiologically equivalent temperature in urban areas using artificial neural network. Landsca Urban Plan 150:1–9. https://doi.org/10.1016/j.landurbplan.2016.02.010
Koberl J, Prettenthaler F, Bird DN (2016) Modelling climate change impacts on tourism demand: a comparative study from Sardinia (Italy) and Cap Bon (Tunisia). Sci Total Environ 543:1039–1053. https://doi.org/10.1016/j.scitotenv.2015.03.099
Li H, Song H, Li L (2017) A dynamic panel data analysis of climate and tourism demand. J Travel Res 56:158–171. https://doi.org/10.1177/0047287515626304
Lu R, Chen R (2016) A review of recent studies on extreme heat in China. Atm Oceanic Sci Lett 9:114–121. https://doi.org/10.1080/16742834.2016.1133071
Luber G, McGeehin M (2008) Climate change and extreme heat events. Am J Prev Med 35:429–435. https://doi.org/10.1016/j.amepre.2008.08.021
Martín G, Belén M (2005) Weather, climate and tourism a geographical perspective. Ann Tourism Res 32:571–591. https://doi.org/10.1016/j.annals.2004.08.004
Matzarakis A, Rammelberg J, Junk J (2013) Assessment of thermal bioclimate and tourism climate potential for Central Europe—the example of Luxembourg. Theo Appl Climatol 114:193–202. https://doi.org/10.1007/s00704-013-0835-y
Michailidou AV, Vlachokostas C, Moussiopoulos Ν (2016) Interactions between climate change and the tourism sector: multiple-criteria decision analysis to assess mitigation and adaptation options in tourism areas. Tour Manag 55:1–12. https://doi.org/10.1016/j.tourman.2016.01.010
Mieczkowski Z (1985) The tourism climate index: a method of evaluating world climates for tourism. Can Geogr 29:220–233. https://doi.org/10.1111/j.1541-0064.1985.tb00365.x
Morgan R, Gatell E, Junyent R, Micallef A, Özhan E, Williams AT (2000) An improved user based beach climate index. J Coast Conserv 6:41–50. https://doi.org/10.1007/bf02730466
Olya HGT, Alipour H (2015) Risk assessment of precipitation and the tourism climate index. Tour Manag 50:73–80. https://doi.org/10.1016/j.tourman.2015.01.010
Peng J (2014) An investigation of the formation of the heat wave in southern China in summer 2013 and the relevant abnormal subtropical high activities. Atm Oceanic Sci Lett 7:286–290. https://doi.org/10.3878/j.issn.1674-2834.13.0097
Perch-Nielsen SL, Amelung B, Knutti R (2010) Future climate resources for tourism in Europe based on the daily tourism climatic index. Clim Chang 103:363–381. https://doi.org/10.1007/s10584-009-9772-2
Ren Y, Fu Z, Shen W, Jiang P, He Y, Peng S, Wu Z, Cui B (2010) Incidence of high altitude illnesses among unacclimatized persons who acutely ascended to Tibet. High Alt Med Biol 11:39–42. https://doi.org/10.1089/ham.2009.1049
Rosselló-Nadal J (2014) How to evaluate the effects of climate change on tourism. Tour Manag 42:334–340. https://doi.org/10.1016/j.tourman.2013.11.006
Sánchez-Mascuñano A, Masuet-Aumatell C, Morchón-Ramos S, Ramon JM (2017) Relationship of altitude mountain sickness and smoking: a Catalan traveller’s cohort study. BMJ Open 7:e017058. https://doi.org/10.1136/bmjopen-2017-017058
Scott D, Lemieux C (2010) Weather and climate information for tourism. Procedia Environ Sci 1:146–183. https://doi.org/10.1016/j.proenv.2010.09.011
Scott D, McBoyle G, Schwartzentruber M (2004) Climate change and the distribution of climatic resources for tourism in North America. Clim Res 27:105–117. https://doi.org/10.3354/cr027105
Scott D, Rutty M, Amelung B, Tang M (2016) An inter-comparison of the holiday climate index (HCI) and the tourism climate index (TCI) in Europe. Atmosphere 7:80. https://doi.org/10.3390/atmos7060080
Textbook (2013) Eight grade geography book (volume one). People’s education press, Beijing
Tibet Autonomous Region Bureau of Statistics (2016) Tibet statistical yearbook 2016. China Statistics Press, Beijing
UNWTO (2016) UNWTO annual report 2015. UNWTO, Madrid
UNWTO (2017) UNWTO annual report 2016. UNWTO, Madrid
Wang W, Zhou W, Wang X, Fong SK, Leong KC (2013) Summer high temperature extremes in Southeast China associated with the east Asian jet stream and circumglobal teleconnection. J Geophs Res: Atm 118:8306–8319. https://doi.org/10.1002/jgrd.50633
Wu TY, Ding SQ, Liu JL, Yu MT, Jia JH, Duan JQ, Chai ZC, Dai RC, Zhang SL, Liang BZ, Zhao JZ, Qi DT, Sun YF, Kayser B (2009) Reduced incidence and severity of acute mountain sickness in Qinghai-Tibet railroad construction workers after repeated 7-month exposures despite 5-month low altitude periods. High Alt Med Biol 10:221–232. https://doi.org/10.1089/ham.2009.1012
Yang J, Zhang Y, Xi J (2016) The comprehensive evaluation of suitability of summer tourism base in China. Resour Sci 38:11–16. https://doi.org/10.18402/resci.2016.12.02
Yu G, Schwartz Z, Walsh JE (2009) A weather-resolving index for assessing the impact of climate change on tourism related climate resources. Clim Chang 95:551–573. https://doi.org/10.1007/s10584-009-9565-7
Yu Z, Sun G, Luo Z, Feng Q (2015) An analysis of climate comfort degree and tourism potential power of cities in northern China in summer to the north of 40°N. J Nat Resour 30:327–339. https://doi.org/10.11849/zrzyxb.2015.02.015
Zaninovic K, Matzarakis A (2009) The bioclimatological leaflet as a means conveying climatological information to tourists and the tourism industry. Int J Biometeorol 53:369–374. https://doi.org/10.1007/s00484-009-0219-2
Zhao J et al (1995) Chinese physical geography. Higher education press, Beijing
Acknowledgements
We would like to thank Hongfei Du of the University of Electronic Science and Technology of China for his advice on the TCI model. We wish to acknowledge valuable discussions on the spatialization of the TCI model with Jing Li of the Northwest Institute of Eco-Environment and Resources, CAS, and Junli Xu of Yancheng Teachers University. We also thank Changjuan He of the Institute of Mountain Hazards and Environment, CAS, for digitizing relief boundaries and climate zone boundaries. The authors acknowledge anonymous reviewers and editors for improving the manuscript. Climate data were provided by the China Meteorological Data Service Center. The DEM was provided by the CGIAR Consortium for Spatial Information.
Funding
This work was supported by the National Natural Science Foundation of China (Grant Nos. 41201603 and 41071091), Youth Science Foundation of Centre of Mountain Development, IMHE, CAS (2018).
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Huang, J., Li, L., Tan, C. et al. Mapping summer tourism climate resources in China. Theor Appl Climatol 137, 2289–2302 (2019). https://doi.org/10.1007/s00704-018-2740-x
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DOI: https://doi.org/10.1007/s00704-018-2740-x