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Under the background of intensifying global change, the frequent occurrence of agrometeorological disasters has an adverse impact on the social economy. Low-temperature weather in spring is one of the main agrometeorological disasters in Xinjiang. Studying the spatial and temporal characteristics of low temperatures in spring in Xinjiang is of great significance. However, research on the spatiotemporal variation of spring frost in arid areas is currently lacking, which limits our understanding of the occurrence and development mechanism of typical disastrous weather events in arid areas. Therefore, on the basis of the daily meteorological data of 40 meteorological stations in the Xinjiang Province of China from 1971 to 2020, we studied the spatiotemporal heterogeneity of spring frost in Xinjiang through trend analysis, the Mann–Kendall test, Kriging interpolation, and wavelet analysis. Results showed that the frequency of spring frost had the spatial trend from Northern Xinjiang to Southern Xinjiang. The occurrence frequency of spring frost in the entire and northern region of Xinjiang had an upward trend, whereas that in Southern Xinjiang showed a downward trend. Severe and moderate spring frost events mainly occurred in Xinjiang. The duration of spring frost had the characteristics of Northern Xinjiang to Southern Xinjiang. The spring frost in Northern Xinjiang mainly occurred in April, and that of Southern Xinjiang was in March. Obvious 15-, 10-, and 20-year oscillation cycles were observed in the occurrence frequency of spring frost in the entire, southern, and northern regions of Xinjiang, respectively. This study can provide a useful reference for the prediction and research corresponding to the occurrence mechanism of spring frost in arid areas. [ABSTRACT FROM AUTHOR]

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China's summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer. [ABSTRACT FROM AUTHOR]