Spatial and Temporal Patterns of the Extreme Precipitation across the Tibetan Plateau (1986–2015)

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. and snowstorms caused by extreme precipitation events, have an adversely effect on ecosystems, agriculture, industry, and socioeconomic development [2,3]. Thus, the occurrences of extreme climate events and their trends have become the focus of most climate change studies. In the global, extreme precipitation probability have shown an increasing trend, and the total amount of extreme precipitation has increased significantly, and also the tropic region has the most extreme precipitation events [4,5]. Additionally, they have more areas with significant increasing trends in extreme precipitation amounts, intensity, and frequency than areas with decreasing trends ...

Concurrent and Lagged Effects of Extreme Drought Induce Net Reduction in Vegetation Carbon Uptake on Tibetan Plateau

“…Encompassing approximately 25% of China's mainland, the TP primarily includes the regions of north-western Sichuan, Qinghai, and Tibet. As 'Asia's water tower' [41], the Plateau possesses a typical thermal/moisture gradient from the southeast to northwest due to the elevation and monsoonal winds, and it includes a range of climate-sensitive vegetation along the climate change characteristics, from subtropical and tropical forests to alpine deserts. Specifically, the annual mean total precipitation increases from 16 mm in the northwest to 1764 mm in the southeast, as observed during the period of 1981-2011, with a corresponding variation gradient in the annual mean air temperature increasing from −5.0 • C in the northwest to 15.5 • C in the southeast [42].…”

A Study of Precipitation Patterns through Stochastic Ordering

“…The understanding of the spatial and temporal patterns of precipitation change is very important to a country, such as China, where the available water per person is only one-third of the world average [4]. Spatial and temporal changes in precipitation have been studied for different regions in China, for example, Southwestern China [5], Northwestern China [6], the Yangtze River Delta [7], the Zhujiang River Basin [8], and other specific regions [9][10][11][12][13][14][15][16]. These results agree with the literature in that the observed changes in precipitation extremes are much less spatially coherent and statistically significant compared to observed changes in temperature extremes [17,18].…”

Observed Changes in Temperature and Precipitation Extremes Over the Yarlung Tsangpo River Basin during 1970–2017

“…Previous studies reported that the Asian summer monsoon affects precipitation in southern regions of the TP [29,53]. As shown in Table 8, the South Asian summer monsoon index (SASMI) has a positive correlation with PRCPTOT and R10 mm, indicating that the South Asian summer monsoon has considerable influence on precipitation variation.…”

“…China China Previous studies have indicated that the annual total precipitation is well correlated with extreme precipitation [29,32,34,53]. Figure 13b indicates a strong correlation between total precipitation and each of the precipitation indices (except CDD), of which R95p, R10mm, and R20mm showed the best correlation with total precipitation with a correlation coefficient of >0.70 (p < 0.01).…”