Abstract

Exploration of the temporal and spatial evolutionary trends of future extreme precipitation under different emission scenarios is of considerable importance for promoting active response to climate change. Based on the output of CMIP6 global climate models (GCMs) with four Shared Socioeconomic Pathways (SSPs), precipitation data for the Jialing River Basin (China) were obtained through CMhyd downscaling and correction. A relative threshold of 95 percentile of each year was used to extract extreme precipitation in the basin, and historical observational data were used to verify the capability of the GCMs to simulate extreme precipitation. Based on Extreme-point Symmetric Mode Decomposition, the trends and periodic characteristics of future extreme precipitation in the Jialing River Basin under four different emission scenarios (SSP2.6, SSP4.5, SSP7.0, and SSP8.5) were simulated and analyzed. The future temporal and spatial distributions of extreme precipitation frequency and intensity in different periods were described. The results revealed the following. (1) Future extreme precipitation in the Jialing River Basin is likely to increase with rates of 21.8 mm/10a, 11.4 mm/10a, 8.7 mm/10a, and 8.3 mm/10a for SSP8.5, SSP 7.0, SSP4.5, and SSP2.6, respectively. (2) The frequency of extreme precipitation decreased in the whole basin with a 1-day decrease of 3.88 % (SSP8.5), 7.11 % (SSP7.0), 5.66 % (SSP4.5), and 2.40 % (SSP2.6) from historical levels. (3) The intensity of extreme precipitation increased with a 1-day increase of 11.18 % (SSP8.5), 6.80 % (SSP7.0), 5.04 % (SSP4.5), and 4.57 % (SSP2.6) from historical levels. Over time, the change of extreme precipitation showed strong periodic characteristics with three periodic components of 2–3, 4–6, and 9–12 years. In terms of spatial distribution, the frequency (intensity) center of extreme precipitation in the next 80 years will be distributed in the south (southeast) of the basin. Compared with historical observations, the area of extreme precipitation intensity in the future accounted for a larger proportion, while the area of extreme precipitation frequency accounted for a smaller proportion. In terms of increased emission levels, the extreme precipitation frequency would decrease and the intensity would increase. The conclusions of this study could provide a reference for disaster prevention and mitigation of the effects of extreme precipitation under future climate change.

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