Coupling relationship between meteorological factors and precipitation: an empirical study from Xinjiang Province, China
2022
Zhang, Yuhu | Xie, Pei | Pu, Yanru | Wang, Peng
The present study examines the spatio–temporal trend analysis of rainfall and temperature over time (annual, warm season, and cold season) from 1981 to 2010 in Xinjiang Province, China. The Mann–Kendall test, least square linear regression, and Spearman rank correlation were used to detect the direction and magnitude of change in rainfall and temperature. A panel data set of 8 meteorological factors during 1981–2010 was used to detect the statistical relationship between rainfall and other meteorological factors in Sect. 4.4. The results showed that annual rainfall and seasonal rainfall increased steadily, and the increasing rainfall trend during the cold season was more significant compared to the warm season. For temperature, average, high, and low temperatures increased on the annual and seasonal scales. Spatially, the northern parts of Xinjiang received more rainfall and showed higher variability. Based on the rainfall trend, the province was clustered into three parts using the K–means method. Based on this clustering, the statistical relationships between rainfall and other meteorological factors were investigated. The results showed that temperature and relative humidity were significantly correlated with rainfall in the three clusters, whereas sunshine, wind speed, and cloud cover had small influences on rainfall.
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