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• W4221062008 abstract "Abstract Since climate change has altered extreme precipitation and temperature patterns, further study of these patterns is essential. The examination of precipitation and temperature patterns is of great significance to water engineers, water resources management, and hydrological studies. Accordingly, this study explored the nonlinear dynamic patterns and their sources governing extreme precipitation and temperatures using multifractal, shuffling, surrogating techniques, and extreme climate indices. The temperature and precipitation data regarding central England (1931–2019) were collected and used for analysis. The results of extreme climate indices demonstrated climate change in the study area. Besides, the multifractal analysis indicated that all indices’ time series were characterized by multifractality. Despite the fact that multifractality of the maximum 1-day precipitation, minimum of maximum temperature, and maximum of maximum temperature was predominantly produced by correlation properties (long-range correlations between small and large local fluctuations), the multifractal characteristics of the warm nights were due to a probability density function (PDF) predominance. Moreover, multifractal properties of the diurnal temperature range, maximum 5-day precipitation, maximum of minimum temperature, minimum of minimum temperature, cool nights, and cool and warm days were produced by the identical extent of correlation properties and the PDF." @default.
• W4221062008 created "2022-04-03" @default.
• W4221062008 creator A5067681804 @default.
• W4221062008 creator A5075107690 @default.
• W4221062008 date "2022-03-28" @default.
• W4221062008 modified "2023-10-11" @default.
• W4221062008 title "Evaluation of nonlinear dynamic patterns of extreme precipitation and temperatures in central England during 1931–2019" @default.
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• W4221062008 doi "https://doi.org/10.2166/wcc.2022.451" @default.
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