Spatial and Temporal Changes of Tourism Climate in Ardabil Province using Physiological Equivalent Temperature (PET) and its Prediction Using Multivariable Regression Equation
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Climate is one of the environmental factors that plays a seminal role in human activities including tourism. In this research, the human-biometeorological climatic conditions of Ardabil province have been investigated using physiological equivalent temperature (PET) based on body-atmosphere energy balance and multivariate regression. The data was collected from the National Meteorological Organization for 8 synoptic stations over 30 years (1991 to 2020). The results suggest that out of 9 climate classes of PET index, only 5 classes of “very cold, cold, relatively cool, cool and comfortable” can be found in this region and 4 classes of “relatively hot, hot, hot and very hot” do not exist in this province. In this regard, it turned out that very cold conditions prevail over the entire province in 5 months of the cold season, i.e., January, February, March, November and December, and the spatial distribution of these conditions is fully homogenous. This is relatively heterogeneous in the summer and the climatic conditions of this area are more variable in the hot season of the year. In general, in June, July and August, ideal conditions prevail in parts of this province. As such, the it was found that the major controlling factor of comfortable climatic conditions among longitude, latitude and altitude was altitude, so that there is a strong inverse relationship between altitude and PET index in 12 months of the year at a significant level of α=0.05 and α=0.01. The multivariate regression relationship of longitude, latitude and altitude with the PET indicate that Adj.R2 value of PET from January to December for the reference period is 0.713, 0.820, 0.783, 0.807, 0.807, 0.559, 0.841, 0.693, 0.745, 0.731, 0.824 and 0.662. The highest variations in the dependent variable were observed in the regression model. In this model, altitude has an inverse relationship with PET so that its value declines as altitude increases. This is true for two variables of latitude and longitude, but the effect of longitude is less substantial than that of latitude, both of which are eclipsed by altitude.
Keywords:
Language:
Persian
Published:
Journal Of Geography and Regional Development Reseach Journal, Volume:22 Issue: 1, 2024
Pages:
253 to 284
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