Spatiotemporal relationship of temperature and precipitation over southern coasts of the Caspian Sea based on quantile regression methods

Temperature and precipitation are significant environmental variables that can lead to catastrophic climatic disasters. The intensity of precipitation increases with increasing temperature under humid conditions. As a result, investigating the trend and relationship between precipitation and temperature is important in a wide range of industries such as trade, agriculture, and ecological analysis. Quantile regression techniques were used in this study to determine the effect of temperature variables on different amounts of precipitation during a 36-year duration (1984-2019) in Mazandaran Province of Iran. According to the findings, heavy rainfall increased significantly in February and April while decreasing in May, June, and September. All minimum and maximum temperature measurements, however, increased significantly. Moreover, the positive and negative effects of temperature variables were higher in the upper quantiles of precipitation, so the most negative effect of the minimum temperature were identified in the northwestern regions and in the warm and cold months of the year, but the most positive effect were detected in the north. In contrast, it was revealed that the north and northwest regions, respectively, were most negatively impacted by maximum temperature and most positively impacted by heavy rainfall. Finally, in a long period, high temperatures have not shown a positive effect on precipitation, and it is different according to spatial and temporal changes.