Projecting changes in the thermal comfort of coastal tourists in Hormozgan province

Document Type : Full length article


Geographical Sciences Department, University of Hormozgan, Bandar Abbas, Iran



Weather conditions have a significant impact on the tourism sector, especially coastal tourism. Variations in the climate elements brought on by global warming may present challenges for this sector of tourism. This study aims to evaluate variations of climate elements in coastal regions of Hormozgan Province using the outputs of Global Climate Models (GCMs) and to identify how these differences affect the thermal comfort of coastal visitors to this area. Daily and monthly data of eight synoptic stations were used for the base period 1990–2019, along with the outputs of five GCMs for the near- and the far-future time periods of 2020–2050 and 2050–2100, respectively, based on tow Representative Concentration Pathways (RCP 4.5 and RCP 8.5. scenarios). The PMV index was then extracted to evaluate travelers' thermal comfort. The research findings showed that January, February, and December were regarded as thermally stress-free or neutral for coastal tourism during the base period in all the analyzed stations. While April through October were hot and very hot, March and November were just moderately warm. Only The Minab station experienced intolerable conditios in July and August. Both scenarios projected monthly shifts in thermal comfort for visitors in the near and far future. Neutral thermal conditions will restricted to January and February, while months with no heat stress to moderate warm will change to warm and humid months and intolerable circumstances will worsen everywhere
Extended Abstract
As a result of the increase in greenhouse gases, it has recently been estimated that temperatures will rise between 0.4 and 2.6 degrees Celsius by the middle of the century and between 0.3 and 4.8 degrees Celsius by the end of the century (IPCC AR5, 2014). These changes will undoubtedly have an impact on the number of tourists and the best time to travel.
According to ASHRAE (1972), thermal comfort is the state in which the brain is content with the environment's temperature. Thermally neutral conditions are another name for this circumstance (Fanger, 1970). According to Mieczkowski (1985), there are six factors that influence the degree of thermal comfort: two human factors, such as physical activity and clothing thermal resistance, and four environmental factors, such as air temperature, air vapor pressure, average radiant temperature, and wind speed. The degree of human thermal comfort in various Environments and conditions has been measured using various combinations of these parameters in various indices (more than 100 indices). The Predicted Mean Vote (PMV) stands out among thermal comfort indices because of its strong theoretical foundations, simplicity in computation, wide applicability, experimental evaluation, and consideration of all factors affecting the tourism climate (De Freitas et al., 2008).
Due to the year-round thermal comfort (Khorasani et al., 2015); specific geomorphological phenomena, such as marine terraces, diverse types of wind erosion, and distinctive landscapes; Beautiful islands and historical and cultural landmarks the coastlines of the Hormozgan Province have a great deal of tourism potential. Although earlier studies have noted an increase in temperature and a decrease in precipitation for these regions (Sharaf and Mir Karim, 2020; Ghasemi 2015), and projections have also confirmed the strengthening of these conditions until the end of this century (Mansouri Daneshvar et al. 2019; Parandin et al. 2019, Khoorani and Monjazeb Marvdashti, 2014), there has been very little research into changes in thermal comfort and tourism climate in the study area under climate change conditions. Valizadeh and Khoorani, 2022 projected a decrease in OTCI values for the future (until the end of this century) based on four large-scale climate models and two scenarios in Hormozgan province (including coastal and non-coastal areas). Based on the output of the HADCM3 model and two scenarios, Khoorani and Manjzeb Marvdashti, 2012, have predicted seasonal changes in the number of visitors for Hengam Island until the end of the 21st century (including an increase in summer and autumn and a decrease in spring and summer). Using the tourism climate information plan, Karimi et al. (2014) revealed comparable seasonal changes in the aesthetic, thermal, and physical components of the tourism climate along the Persian Gulf and Sea of Oman beaches from 1979 to 2008. The aim of this study is to use PMV thermal index to anticipate how climate change may affect the tourism climate along Iran's southern coast in the province of Hormozgan. Monthly climate data of minimum and maximum temperature, sunshine hours and precipitation from 8 weather stations from 1990 to 2019 (for Gheshm station from 1996 to 2019) was downloaded from Iran Meteorological Organization.The data are projected for 2 time periods (near period 2020-2050 and far period 2050-2100) up to the end of the 21st century using an ensemble of 5 GCMs under 2 Representative Concentration Pathways (RCP2.6 and RCP8.5). The LARSWG-6 stochastic weather generator was used to downscale GCM outputs, and the PMV index was calculated for the Historic period (1990-2019), Near period (2020-2050), and Far future (2050-2100).
Results and Discussion
According to the PMV index for 1990-2019, the Bandar Abbas, Jask, Siri, Bandarlange, and Kish Island stations had good travel conditions in December, February, and January, as well as the Abu Musi Station in January and February, the Minab Station in February, and the Qeshm Island Station in December, March, and February.
The overall evaluation shows that, from May to October, the majority of the year is marked by varied degrees of heat stress. Only a few months, from December to March, make up the ideal thermal season. December and February are usually considered as favorable months by stations.
According to the RCP4.5 scenario for the near future (2020-2050), the PMV index of the Bandar Abbas, Bandar Jask, Qeshm, Siri, Abu Musi, Bandar Lange, and Kish stations in February and January, as well as the Minab station in January, indicates a favorable situation.
According to the RCP4.5 scenario, there will be an increase in the severity of heat stress in the far future (2100-2050) with August and July becoming unbearably hot. This increase will be greater than that in the past and the near future.
According to RCP8.5, Bandar Abbas, Bandar Jask, and Qeshm stations in December, February, and January; Siri station in February and January; and Abu Musa, Bandarlange, Minab, and Kish stations in January will be in good condition in the near future (2020-2050).
The intensity of heat stress would increase in the far future (2050-2100) compared to past periods, according to the RCP8.5 scenario. During the months of September, August, July, and June, the degrees of this increase will range from very hot to uncomfortable at most sites.
As a result of the changes in temperature and precipitation in the future periods, the suitable time period for travel and beach activities in Hormozgan province has shifted to January, February, and December, and due to the increase in temperature, the months with Low thermal tension will no longer have suitable conditions for beach activities and travel, and their condition will change to acceptable. These factors will cause seasonal shifts and diminish the optimal tourism climate conditions on Hormozgan's coastlines. It is suggested that future research develop a climate calendar for tourists visiting Hormozan province's coastal areas, taking into account the importance of climatic factors. It is also advised to use the projections from the outputs of Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs in the future studies.
There is no funding support.
Authors’ Contribution
All of the authors approved the content of the manuscript and agreed on all aspects of the work.
Conflict of Interest
Authors declared no conflict of interest.
We are grateful to all the scientific consultants of this paper.


Main Subjects

  1. Aboubakri, O., Khanjani, N., & Jahani, Y. (2020). Thermal comfort and mortality in a dry region of Iran, Kerman; a 12-year time series analysis. Theor Appl Climatol, 139, 403–413.
  2. Alizadeh, M., Rahimi, M., Nickbakht, R., & Sedigh bazkia, M. (2019). Evaluation of tourism climate conditions of selected cities of Isfahan province based on tourism climate indices. Geography (Regional Planning)8(33), 43-55. Doi:1001.1.22286462.1397. [In Persian].
  3. Amengual, A., Homar, V., Romero, R., Alonso, S. and Ramis, C. (2012). Projections of the climate potential for tourism at local scales: application to Platja de Palma, Spain. J. Climatol, 32(14), 2095-2107.
  4. Asghari M., Teimori GH., Abbasinia M., Shakeri F., Tajik R., Ghannadzadeh M. J., Ghalhari GH., F. (2019). Thermal discomfort analysis using UTCI and MEMI (PET and PMV) in outdoor environments: case study of two climates in Iran (Arak & Bandar Abbas). Weather, 74(S1), S57-S64.
  5. (1972). Handbook of fundamentals. American Society of Heating, Refrigerating and Air-Conditioning Engineers, New York.
  6. Bazrafshan, J., Khalili, A., Hoorfar, A., Torabi, S., Hajjam,S. 2009. Comparison of the Performance of ClimGem and LARS-WG Models in Simulating the Weather Factors for Diverse Climates of Iran. Journal Iran-Water Resources Research, 5 (13), 44-57. (In Persian).
  7. Berrittella, M., Bigano, A., Roson, R., & Tol, R. (2006). A general equilibrium analysis of climate Change impacts on tourism. Tourism Management, 27, 913–924.
  8. Broday E. E., Moreto J. A., Xavier A. A. P., & Oliveira R. (2018). The approximation between thermal sensation votes (TSV) and predicted mean vote (PMV): A comparative analysis, International Journal of Industrial Ergonomics, 69, 1-8.
  9. Critchefied, j.H. (1983). General climatology. prentice Hall Inc.USA.
  10. De Freitas, C. R., Scott, D., & McBoyle, G. (2004). A new generation climate index for tourism. Advances in tourism climatology. Reports Meteorology Institute, University of Freiburg, 12, 19-26.
  11. De Freitas, C.R., Scott D., & Geoff M. (2008). A second generation climate index for tourism (CIT): specification and verification. Int J Biometeorol, 52, 399–407.
  12. Fanger, P., O. (1970). Thermal Comfort. Copenhagen: Danish Tehchnical Press.
  13. Ghalhari GH. F., Dehghan S. F., Shakeri F., Abbasinia M., Asghari M. (2019). Thermal comfort and heat stress indices for outdoor occupations over 15 years: a case study from Iran. Weather, 74(S1), S40-S45.
  14. Ghasemi AR (2015) Changes and trends in maximum, minimum and mean temperature series in Iran. Atmos Sci Let, 16, 366–372.
  15. Ghorbannia Kheybari, V., azimi, E., & armin, M. (2022). Calculation of RayMan model tourism climate indices in Yasuj city and study of their trend. Journal of Geography and Environmental Studies11(41), 107-122. Doi: 1001.1.20087845.1401. [In Persian].
  16. Habibi, K., Hoseini, S.M., Dehshti, M., Khanian, M., & Mosavi, A. (2020). The Impact of Natural Elements on Environmental Comfort in the Iranian-Islamic Historical City of Isfahan. J. Environ. Res. Public Health, 17(16), 5776.
  17. Hamze Nejad, M., Fadaee, F., & Ildarabadi, P. (2020). Evaluation of comfort and thermal comfort (PMV and PPD) according to daylight and home orientation in Yazd traditional houses (Case study: Malekzade home in Yazd city). Journal of Architecture in Hot and Dry Climate8(11), 151-182. doi: 10.29252/ahdc.2020.1984. [In Persian].
  18. (2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (Eds.)]. IPCC, Geneva, Switzerland, 151.
  19. Karimi, Z., Nazaripour, H., & Khosravi, M. (2017). Potential Impacts of Climate Change on Tourism in South Beaches of Iran based on Climate Tourism Information Scheme. Geography and Environmental Planning28(1), 21-34. doi: 10.22108/gep.2017.97874 [In Persian].
  20. Kashki, A., hosseini, S. M., & hardani, A. (2019). Climatic Comfort Analysis and Its Relation to Human Physiological Indices (Case: Sistan and Baluchestan Province). Journal of Environmental Science Studies4(1), 929-944. [In Persian].
  21. Khaledi, S., karimi, Y., ebdali, H., & Mohammadi, G. (2020). Analyze of Comfort Climate Indexes and its relation to tourism in Tabriz. Sustainable Development & Geographic Environment1(1), 73-81. doi: 10.52547/sdge.1.1.73 [In Persian].
  22. Khoorani, A., & Monjazeb Marvdashti, S. (2014). Investigating the Effects of Climate Change on the Number of Visitors in Hengam Island. Physical Geography Research Quarterly46(1), 109-122. doi: 10.22059/jphgr.2014.50622 [In Persian].
  23. Khorasani, H., Khoorani, A., & Zolfaghrai, H. (2016). Hourly Evaluation of Climate Comfort of Queshm Island for Different Nature-based Tourism Activities. Journal of Tourism Planning and Development5(16), 209-229. [In Persian].
  24. Lemesios, G., Papadaskalopoulou, C., Moustakas, K., Malamis, D., & Ioannou, Maria. K. (2016). Future heat-related impact assessment of tourism industry to climate change in Cyprus. Reg Environ Change, 16, 1915–1927.
  25. Lin, T. P., & Matzarakis, A. (2008). Tourism climate and thermal comfort in Sun Moon Lake, Taiwan. International Journal of Biometeorology, 52(4), 281-290. https:// org/10.30892/gtg.25218-376
  26. Mahmoud, D., Gamal, G., & Abou El Seoud, T. (2019). The potential impact of climate change on Hurghada city, Egypt using tourism climate index. GeoJournal of Tourism and Geosites, 25(2), 496–508.
  27. Majidi, F. A., Heidari, S., Ghalehnoee, M., & Ghasemi Cichani, M. (2020). Assessment and Analysis of the Thermal Comfort Conditions in Open Spaces of Residential Neighborhoods Using Thermal Indicators (Case Study: Neighborhoods of Isfahan City). Journal of Iranian Architecture & Urbanism(JIAU)10(2), 113-126. doi: 10.30475/isau.2020.103467 [In Persian].
  28. Mansouri Daneshvar, MR., Ebrahimi, M., Nejadsoleymani, H. (2019). An overview of climate change in Iran: facts and statistics. Environ Syst Res, 8(7), 1-10.
  29. Matzarakis, A. (2001). Assessing climate for tourism purposes: Existing methods and tools for the thermal complex. In Proceedings of the first international workshop on climate, tourism and recreation, ed. by A. Matzarakis and CR de Freitas. International Society of Biometeorology, Commission on Climate Tourism and Recreation, 101-112.
  30. Matzarakis, A. (2007). Climate, thermal comfort and tourism (in:) Amelung, B., Blazejczyk, K., Matzarakis, A. Climate Change and Tourism-Assesment and Coping Strategies. Maastricht – Warsaw – Freiburg, 139-154
  31. Matzarakis, A., Mayer, H., & Iziomon, M. G. (1999). Application of a Universal Thermal Index: Physiological Equivalent Temperature. Biometorology. 43(43), 78-84. DOI:10.1007/s004840050119
  32. Mazidi, A., Omidvar, K., Malek Ahmadi, A., & Hosseini, S. S. (2021). Evaluation of bioclimatic indicators affecting human comfort (Case study: Urmia). Geography and Human Relationships4(2), 155-175. doi: 10.22034/gahr.2021.286618.1560 [In Persian].
  33. Mieczkowski, Z. (1985). The tourism climatic index: a method of evaluating world climates for tourism. Can Geogr, 29(3), 220–233.
  34. Mohammadi, K., mohammadi, D., & kolivand, T. (2019). The Simulation of Microclimatic Conditions and Thermal Comfort in Main Streets of Kermanshah City. Geography and Territorial Spatial Arrangement9(30), 77-94. doi: 10.22111/gaij.2019.4446 [In Persian].
  35. Morabito, M., Crisci, A., Barcaioli, G., & Maracchi, G. (2004). Climate change: The impact on tourism comfort at three Italian tourist sites (in:) Matzarakis A., de Freitas C. R., Scott D. (eds.) Advances in Tourism Climatol., Ber. Meteor. Inst. Univ. Freiburg (Germany), 12, 56–65.
  36. Nazaripour, H., & Tavosi, T. (2021). Thermal Comfort Evaluation in Urban Open Public Space with Emphasis on Strengthening Social Relations (Case Study: Quds Neighborhood, Zahedan). Journal of Urban Social Geography8(1), 287-306. doi:10.22103/JUSG.2021.2043. [In Persian].
  37. Panagiotis, T. N, & Matzarakis, A. (2019). Present and Future Climate—Tourism Conditions in Milos Island, Greece. Atmosphere, 10(3), 145.
  38. Parandin, F., Khoorani, A., Bazrafshan, O. (2019). The impacts of climate change on maximum daily discharge in the Payab Jamash Watershed. Iran. Open Geosci, (11),1035–1045. 1515/geo-2019-0080
  39. Rao, J., & Garfinkel, C. I. (2021). CMIP5/6 models project little change in the statistical characteristics of sudden stratospheric warmings in the 21st century. Res. Lett.16, 034024. DOI 10.1088/1748-9326/abd4fe
  40. Rasco, P., Szeidl, L., & Semenov, M.A. (1991). A serial approach to local stochastic models. Ecological Modeling, 57, 27-41.
  41. Scott, D., Dawson, J., and Jones, B. (2008). Climate change vulnerability of the US Northeast winter recreation–tourism sector. Mitig Adapt Strateg Glob Change, 13, 577–596.
  42. Scott, D., McBoyle, G., and Schwartzentruber, (2004). Climate change and the distribution of climatic resources for tourism in North America. Climate research, 27(2), 105-117. doi:10.3354/cr027105
  43. Semenov, M.A., & Barrow E.M. (1997). Use of a stochastic weather generator in the development of climate change scenarios. Climatic Change, 35, 397-414.
  44. Sharaf, S., Mir Karim, N. (2020). Investigating trend changes of annual mean temperature and precipitation in Iran. Arab J Geosci, 13,759.
  45. Sobhani, P., & Danehkar, A. (2023). Investigating tourism climate conditions in Iran's mangrove forests using Tourism Comfort Climate Index (TCI) and Holiday Climate Index (HCI). Journal of Natural Environment, 75(Special Issue Coastal and Marine Environment), 29-45. doi: 10.22059/jne.2022.351668.2494 [In Persian].
  46. Valizadeh, M., & Khoorani, A. (2022). The impact of climate change on the outdoor tourism with a focus on the outdoor tourism climate index (OTCI) in Hormozgan province, Iran. Theor Appl Climatol,150, 1605–1612.
  47. Walls, W., Parker, N., & Walliss, J. (2015). Designing with thermal comfort indices in outdoor sites. Living and learning: research for a better built environment, Australia, Univ Melbourne, Melbourne Sch Design, Fac Architecture Bldg & Planning, Melbourne, 1117-1128.
  48. Wilby, R., & Harris, I. (2006). A frame work for assessing uncertainties in climate change impacts: low flow scenarios for the River Thames, UK. Water Resources Research, 42(2), W02419.
  49. Yu, , Schwartz, Z., & EWalsh J. (2009). A weather-resolving index for assessing the impact of climate change on tourism related climate resources. Climatic Change, 95, 551–573.
  50. Zamani, M., & Akbari, A. (2022). The effect of Sarakhs plain climate on the formation of Robat Sharaf anatomy to achieve thermal comfort. Iranian Civilization Research3(2), 1-12. [In Persian].