Reanalyzing the Trend of Long-term Spatial Changes in the Minimum Temperature of Iran

Document Type : Research Paper

Authors

1 Department of Physical Geography, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran

2 Corresponding Author, Department of Physical Geography, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran

Abstract

Today, climate change has become a major challenge for human societies. The widespread concern of environmental scientists and researchers about global warming has prompted them to study the time series of climatic parameters, especially temperature to reveal the trends of these parameters over the past few decades. Due to the importance of this issue, the present study was conducted to investigate the trend of spatial changes in the minimum temperature of Iran. In this regard, V20CR networked minimum temperature data with daily time resolution and 1 in 1 degree spatial resolution during the period 2019-1836 have been used. First, the trend of minimum temperature changes was calculated using Mann-Kendall test. Then, using spatial statistical methods such as global and local Moran index and hot spot analysis, the patterns governing Iran's minimum temperature and their dispersion were identified. The results of this study showed that in the cold months of the year the zone is trendless, while the decreasing trend is dominant in Iran in the warm months of the zone. An increasing trend has been observed in the southern regions and to some extent in the southeast of Iran. A declining trend occurred in northwestern Iran in January and is gradually spreading throughout Iran in other months. In May, it reaches its maximum expansion in Iran. According to the World Moran Index, the minimum temperature in Iran has a pleasant pattern. The local Moran index also showed that the northwest of Iran follows the pattern of low cluster and the southern regions of Iran follow the pattern of high cluster. The findings from hot spots indicate that the northwestern regions have cold-temperature spots (negative spatial autocorrelation) and the southern regions have hot-temperature spots (positive spatial autocorrelation).
Extended Abstract
1-Introduction
Climate change and temperature fluctuation are among the most important issues in human life. By examining the trend of the changes in the average air temperature, it is possible to trace the climatic changes of a region. Temperature is an indicator of heat intensity and an important climatic element. Significant changes in temperature or global warming have been considered as the most important manifestations of climate change in the present century (Alijani and Ghavidel, 2005). Air temperature at the surface and different layers of the atmosphere are important climatic parameters that affect other parameters such as humidity and evaporation. Therefore, changes in the amount or pattern of temperature at different time intervals are of great importance. The rate of surface temperature increase and different layers of the atmosphere is different in different regions. The results of studies conducted in Iran also point to an increase in temperature. The results of extensive studies conducted at the national, regional, and global levels indicate an increase in temperature in many parts of the world and generally an increase in average air temperature.
2-Materials and Methods
In this study, the minimum gridded temperature data of V20CR, whose temporal resolution is daily and its spatial resolution is 1 in 1 degree for the whole planet, were used during the statistical period 1836-2019. First, the trend of the studied data was calculated by Mann-Kendall test. Then, we used spatial statistics methods including spatial autocorrelation of local and global Moran’s index and hot spot analysis. The Moran’s index is the most common index used to measure spatial autocorrelation between phenomena and events. If the value of the index is +1 or close to +1, the studied variable has autocorrelation and a cluster pattern. If the value of the index is -1 or close to -1, the data are discrete and have a scattered pattern. In addition, if the value of the index is zero, the data have a random pattern.
3- Results and Discussion
The trend of Iran minimum temperature during the study period was calculated to reanalyze the changes. Increasing trends have occurred mainly in the southern regions as well as parts of central Iran. Decreasing trends have also been observed in the northwestern, central, western and eastern regions of Iran. During the cold months of the year, the trendless zone is more prominent in the country and the size of the decreasing and increasing trend zones has been reduced. In March, April, May, June and July, most of Iran is covered by a declining trend. The graphic output from the global Moran’s index showed that the minimum temperature in Iran in all months has a cluster pattern. According to the results of the local Moran’s index, in almost all months, there is a zone without a significant pattern throughout the central regions of Iran. The northwestern corner of Iran has a low cluster pattern in all months and the southern and southeastern parts of Iran have a high cluster pattern. In March, April and May, in addition to the southern parts of the country, a high cluster pattern has been observed in parts of eastern Iran located in the south of South Khorasan province and northeast of Kerman province. In May, June, July, August, September and October, a high cluster pattern can be seen even in small part of the west of the country located in the west of Khuzestan province. Hot spot analysis showed that there are cold spots in northwestern Iran in all months and its significance decreases as it progresses towards the center of Iran. Hot spots are also observed in the southern regions of Iran, located on the shores of the Persian Gulf and the Oman Sea, and by moving towards the center of Iran, their level of significance decreases. Central regions of Iran also lack a significant pattern.
4- Conclusion
In the present study, for the first time, the trend of temporal-spatial changes in the minimum temperature of Iran during the long-term period of 1836-2019 has been reanalyzed. Therefore, spatial statistics methods including global and local Moran and hot spot analysis have been used. The results of trend analysis using Mann-Kendall test showed that in September, October, November, December and January, the trend-free zone is dominant in Iran. A decreasing trend was observed in western Iran in January and it gradually spread throughout the country in other months and reached its maximum expansion in May, covering 90.22% of Iran's area. An increasing trend has also occurred in the southern regions and parts of southeastern and eastern Iran. The results of the global Moran’s index showed that the minimum temperature of Iran in all months follows the cluster pattern. According to the results of the local Moran’s index, northwestern Iran follows the low cluster pattern in all months and the southern regions of Iran follow the high cluster pattern in all months. It should be noted that the high cluster pattern has been observed in some parts of eastern and central Iran in some months. According to the results of hot spot analysis, cold temperature spots have occurred in all months in northwestern Iran. So that in East and West Azarbaijan provinces, cold temperature spots are observed at a significance level of 99% and its significance level decreases as we move towards the central regions of Iran. Warm temperature spots at the level of 99% significance are also observed in the southern regions of Iran in all months and by moving towards the central regions of Iran, its significance level decreases. In some parts of eastern Iran, hot temperature spots have been observed at a significance level of 90%.

Keywords


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