Document Type : Research Paper
Authors
1 Associate professor in Climatalogy , Department of Geography, Yazd University
2 PhD student of Climatology, Yazd University, Yazd, Iran
Abstract
Extended Abstract
Introduction:
Time series analysis is a suitable tool that is used in mathematical modeling, predicting future events, revealing trends, investigating diffraction in climate data, as well as reconstructing incomplete data, and expanding information. Climatic changes are mainly caused by fluctuations, fluctuations, or changes in climatic elements, especially temperature and precipitation. These developments leave undeniable effects on local phenomena, hence the evidence of the past climate can be traced in all wet and dry, hot and cold environments, and biological areas (Ghayour, 2006:85). The temperature of the earth's surface is an important parameter for evaluating the energy budget of the earth's surface (Trigo et al, 2008:1). With the change in climate (temperature and rainfall), many changes are made on the surface of the earth, including vegetation. In fact, with the increase in temperature and decrease in rainfall, vegetation in the region decreases. Considering the importance of the issue and the relationship between climatic indicators and vegetation, by determining the relationship between them, one can predict the changes based on the other, which leads to an increase in the speed and accuracy of the work. Therefore, it seems important to use satellite images and extract and investigate the relationship between temperature and rainfall factors as well as vegetation in different areas, especially watersheds (Zhu et al, 2016:792). With the expansion of satellite technology, satellite images have widely provided access to information on land resources, and remote sensing tools have taken an important role in obtaining information about climate phenomena, because multi-spectral satellite images have important advantages, including They have the availability and ability of digital interpretation (Lillesand and Kiefer, 1994:750).
Materials & Methods:
In this research, using monthly rainfall data from a CHIRPS sensor with a spatial resolution of five kilometers, NDVI vegetation index from a MODIS sensor for 16 days, with a resolution of 250 meters, and day and night surface temperature of 8 days from a MODIS sensor with a resolution of one kilometer, to analyze the changes in surface temperature and its relationship with climatic factors in Kerman province during a statistical period of 22 years (2001-2022) were studied. In the investigation of the annual precipitation fluctuations of Kerman province, standardized values of Z have been used, and these values have varied between -1.5 and +1.5. After receiving the data, first the CHIRPS images, then the NDVI and LST images were processed in the ArcGIS software environment and the values were extracted for Kerman province and then analyzed in the Excel software environment.
Results & Discussion:
According to SPI results, drought is observed in 2010, 2016, 2018, and 2021, and drought in 2004, 2009, 2017, 2019 and 2020. In the rest of the years, the SPI index has been normal. Also, the seasonal rainfall showed that the highest rainfall was in the winters of 2005, 2017, and 2019 with an amount of 90 mm and more and the lowest rainfall was in the summer of 2019 with an amount of less than 1.04 mm. The value of the vegetation cover index (NDVI) is also in the spring season with a value of 1.05, which has an increasing trend, and the lowest value of the vegetation cover index (NDVI) in the autumn and winter seasons, whose lowest value is 0.35 and 0.42 on December 19 and November 17 with a trend A decrease is shown. The seasonal vegetation also shows that as we move from the west of the region to the east, the amount of vegetation decreases. The seasonal changes in the temperature of the surface of the earth during the day in Kerman province show that the hottest seasons are summer and spring and the coldest season is winter. The seasonal changes in the earth's surface temperature at night also show that the highest surface temperature is related to summer and spring, and the lowest is in autumn and winter.
Conclusion:
In general, the results show that according to temperature fluctuations, there is a positive and significant relationship between the temperature of the earth's surface and vegetation (P-value at the 0.01 level). And there is a negative and significant relationship between the temperature of the earth's surface and precipitation. So precipitation has the greatest effect on the variability of the earth's surface temperature and vegetation has the least effect on the surface temperature changes. The increase in day and night temperatures in the spring and summer seasons causes an increase in evaporation and a subsequent decrease in water resources throughout the province and pressure on underground water. On the other hand, with the increase in temperature, the amount of evaporation and transpiration (plants' water needs) will also increase and will lead to a potential decrease in water resources, especially in the eastern regions of the province, but the presence of vegetation can almost reduce the temperature of the earth's surface. In the autumn and winter seasons, during the last decades, with the increase in temperature, the amount of precipitation and vegetation has decreased. Also, an increase in temperature can increase the water demand, which in turn leads to more extraction of surface and underground water resources. This means that the surface temperature has increased significantly in the mentioned statistical period. Also, the different conditions of each region are important factors in determining the type of relationship between temperature, vegetation, and precipitation. The results of this research on the relationship between the earth's surface temperature and climatic factors with the research of Mianabadi et al (2023), and Mazidi et al (2023) based on the method of the experimental relationship between surface temperature and other factors are consistent. According to the findings, the temperature trend in Kerman province is significant and the possibility of heat stress will increase in the future.
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Main Subjects
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