A comprehensive analysis of physiologically equivalent temperature changes of Iranian selected stations for the last half century

Abstract

As a preliminary and major step for land use planning of the coming years, the study of variability of the past decades' climatic conditions with comprehensive indicators is of high importance. Given the fact that one of the affected areas by climatic change includes variability of thermal comfort, this study uses the physiologically equivalent temperature (PET) to identify and evaluate bioclimatic conditions of 40 meteorological stations in Iran. In this study, PET changes for the period of 1960 to 2010 are analyzed, with the use of Mann-Kendall non-parametric test and Pearson parametric method. The study focuses particularly on the diversity in spatio-temporal distribution of Iran's bioclimatic conditions. The findings show that the mean frequency percentage of days with comfort is 12.9 % according to the total number of selected stations. The maximum and minimum frequency percentage with values of 17.4 and 10.3 belong to Kerman and Chabahar stations, respectively. The findings of long-term trend analysis for the period of 1960-2010 show that 55 % of the stations have significant increasing trend in terms of thermal comfort class based on the Pearson method, while it is 40 % based on Mann-Kendall test. The results indicate that the highest frequency of days with thermal comfort in the southern coasts of Iran relates to the end of autumn and winter, nevertheless, such ideal conditions for the coastal cities of Caspian Sea and even central stations of Iran relate to midspring and mid-autumn. Late summer and early autumn along with late spring can be identified as the most ideal times in the west and northwest part of Iran. In addition, the most important inhibiting factors of thermal comfort prove to be different across the regions of Iran. For instance, in the southern coasts, warm to very hot bioclimatic events and in the west and northwest regions, cold to very cold conditions turn out to be the most important inhibiting factors. When considering the variations across the studied period, an increase in the frequency of thermal comfort condition is observed in almost half of the stations. Moreover, based on Pearson and Mann-Kendall methods, the trend of changes in monthly averages of PET has decreased in most stations and months, which can lead to different consequences in each month and station. Thus, it is expected that due to PET changes in recent decades and to the intensified global warming conditions, Iran's bioclimatic conditions change in a way that transfers the days with comfort to early spring and late autumn.

Climatic clustering analysis for novel atlas mapping and bioclimatic design recommendations

“…The results showed that the highest frequency of occurrence of days with comfort is in the Persian Gulf Coastline. Similar findings are found in similar studies, 29,53,54 and were observed by Daneshvar et al 55 and Roshan et al 56 These studies showed that the maximum occurrence of days with comfort during the cold period of the year are in the Iran's Southern Coastal Strip. For the Shores of the Sea of Oman and Persian Gulf, the combination of these bioclimatic strategies with Conventional Dehumidification is the most influential in 24% of study stations in providing comfort inside buildings.…”

Thermal discomfort analysis using UTCI and MEMI (PET and PMV) in outdoor environments: case study of two climates in Iran (Arak & Bandar Abbas)

“…Previous studies have applied the PET index to locations in Iran (Daneshvar et al ., ; Roshan et al ., ). In the study by Daneshvar et al .…”

“…at both Arak and Bandar Abbas. The years included in the analyses differ (1961–2010 for Roshan et al ., and 2000–2014 for the present study), which may explain this disagreement (Roshan et al ., ). Hadianpour et al .…”

Investigating the Behaviour of Human Thermal Indices under Divergent Atmospheric Conditions: A Sensitivity Analysis Approach

“…In addition, and while critical studies pertaining to climatic indices were disseminated before the turn of the century [1][2][3][4][5][6][7][8][9][10][11][12][13], since the ingress into the twenty-first century (and arguably further instigated by the arrival of the climate change adaptation agenda), the importance and development of climatic indices have increased. In accordance with the rational presented by Potchter et al [14], the associated research complexity intrinsic to climatic models can be seen under two prisms, the: (i) overall review, cataloguing, structuring, and fragmentation of index typologies based upon their equational suitability and methodical pertinence [15][16][17][18][19][20]; and, (ii) the pursuit and testing of the most suitable index to estimate thermal comfort thresholds within a specific outdoor and climatic setting [21][22][23][24][25][26][27][28]. Both of these perspectives indicate the significance and opportunities regarding the correct approach to human thermal comfort thresholds within urban environments.…”