Abstract

Extreme climate index is one of the useful tools to monitor and detect climate change. The primary objective of this study is to provide more comprehensively the changes in precipitation and temperature extremes for the period of 1959–2015 in the Jing-Jin-Ji metropolitan region of China, including Beijing city, Tianjin city and Hebei province, which will hopefully provide scientific understanding of the precipitation and temperature-related natural hazards such as flood, drought and heat wave. Daily precipitation and temperature from 26 surface meteorological stations over the study area were used to calculate 14 extreme precipitation indices (EPIs) and 17 extreme temperature indices (ETIs) generated by the joint World Meteorological Organization Commission for Climatology (CCI)/World Climate Research Programme (WCRP) project on Climate Variability and Predictability (CLIVAR) Expect Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). The EPIs and ETIs were generated using the RClimRex software, and the trends were analyzed using the Mann-Kendall non-parametric test and the Thiel-Sen’s slope estimator. The results showed the following: (1) The spatiotemporal variability for daily climate extremes varied for both the EPIs and ETIs between 1959 and 2015. In the case of the EPIs, most of the indices were negative trend-dominated, and for the ETIs, 13 ETIs were positive trend-dominated, and six ETIs were negative trend-dominated. (2) Six types of precipitation intensity EPIs including the R10mm–R250mm were especially defined to detect impacts of climate change on the precipitation events. The results showed that the spatial distributions of increasing trends for these EPIs were similar, mainly located at the south of the Hebei province. (3) In general, the trend magnitudes of fixed-threshold extreme indices were smaller than those of station-related thresholds and non-threshold extreme indices for both the EPIs and ETIs. (4) The spatial distributions of positive and negative trends for both the EPIs and ETIs were scattered. For several indices such as the ID0, SU25, WSDI and TX90p, stations that had statistically significant increasing/decreasing trends at 5% significance level were detected mainly located at the north of the Jing-Jin-Ji metropolitan region. More works on the physical mechanisms behind the varied changes and scattered spatial distributions of trends in the Jing-Jin-Ji metropolitan region are recommended as an extension of this study.

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