Abstract
The Tibetan Plateau is one of the most vulnerable areas to extreme precipitation. In recent decades, water cycles have accelerated, and the temporal and spatial characteristics of extreme precipitation have undergone dramatic changes across the Tibetan Plateau, especially in its various ecosystems. However, there are few studies that considered the variation of extreme precipitation in various ecosystems, and the impact of El Niño-Southern Oscillation (ENSO), and few researchers have made a quantitative analysis between them. In this study, we analyzed the spatial and temporal pattern of 10 extreme precipitation indices across the Tibetan Plateau (including its four main ecosystems: Forest, alpine meadow, alpine steppe, and desert steppe) based on daily precipitation from 76 meteorological stations over the past 30 years. We used the linear least squares method and Pearson correlation coefficient to examine variation magnitudes of 10 extreme precipitation indices and correlation. Temporal pattern indicated that consecutive wet days (CWD) had a slightly decreasing trend (slope = −0.006), consecutive dry days (CDD), simple daily intensity (SDII), and extreme wet day precipitation (R99) displayed significant increasing trends, while the trends of other indices were not significant. For spatial patterns, the increasing trends of nine extreme precipitation indices (excluding CDD) occurred in the southwestern, middle and northern regions of the Tibetan Plateau; decreasing trends were distributed in the southeastern region, while the spatial pattern of CDD showed the opposite distribution. As to the four different ecosystems, the number of moderate precipitation days (R10mm), number of heavy precipitation days (R20mm), wet day precipitation (PRCPTOT), and very wet day precipitation (R95) in forest ecosystems showed decreasing trends, but CDD exhibited a significant increasing trend (slope = 0.625, P < 0.05). In the other three ecosystems, all extreme precipitation indices generally exhibited increasing trends, except for CWD in alpine meadow (slope = −0.001) and desert steppe (slope = −0.005). Furthermore, the crossover wavelet transform indicated that the ENSO had a 4-year resonance cycle with R95, SDII, R20mm, and CWD. These results provided additional evidence that ENSO play an important remote driver for extreme precipitation variation in the Tibetan Plateau.
Highlights
The spatial and temporal patterns of extreme climatic events become more capricious due to accelerated water cycles over the past several decades [1]
This study had two objectives: (1) Through the Pearson correlation coefficient and linear regression, we analyzed the temporal variation of extreme precipitation across the Tibetan Plateau and in its four different ecosystems, and we explored the spatial pattern of extreme precipitation by spatial analysis method in ArcGIS10.5; and (2) we measured the correlation between the El Niño-Southern Oscillation (ENSO)
The most extreme precipitation indices showed increasing trends in the Tibetan Plateau from 1986 to 2015, and consecutive dry days (CDD), simple daily intensity (SDII), and R99 passed 0.05 statistically significance. These results were consistent with previous studies in China, Xinjiang Province and the southwest China (Table 7) [57,58,59], which showed similar variations on smaller regional scales. These results indicate that extreme precipitation events were more frequent across the Tibetan Plateau
Summary
The spatial and temporal patterns of extreme climatic events become more capricious due to accelerated water cycles over the past several decades [1]. Extreme precipitation probability have shown an increasing trend, and the total amount of extreme precipitation has increased significantly, and the tropic region has the most extreme precipitation events [4,5]. They have more areas with significant increasing trends in extreme precipitation amounts, intensity, and frequency than areas with decreasing trends [6]. As the same trend of global change, the frequency and intensity of extreme precipitation events tend to increase in China.
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