A Quantitative Analysis of the Influence of Temperature Change on the Extreme Precipitation

As an essential part of the hydrological cycle, precipitation is usually associated with floods and droughts increasingly being paid attention to in context global warming. Analyzing change trends correlation temperature extreme indicators can effectively identify natural disasters. This study aimed detect Inner Mongolia from 1960 2019. Panel vector autoregression (PVAR) models based on Stata software were used between at 35 climatological stations throughout Mongolia. The indicator analyzed using Mann–Kendall test Sen’s slope method. spatial distribution characteristics annual rainfall intensity more significant southeast minor northwest, while increase wet days was noticeable northeast. Granger cause tests showed a each significance level 1%. positively correlated only negatively correlating remaining indicators. There no doubt that trend analysis increasing all stations, which means increased risk events. By contrast, decreasing trends, concentrated, it easier form provide basis for decision-making water resources drought/flood management Mongolia, China.