Spatial characteristics of extreme rainfall over China with hourly through 24-hour accumulation periods based on national-level hourly rain gauge data

Abstract

Hourly rainfall measurements of 1919 national-level meteorological stations from 1981 through 2012 are used to document, for the first time, the climatology of extreme rainfall in hourly through 24-h accumulation periods in China. Rainfall amounts for 3-, 6-, 12-and 24-h periods at each station are constructed through running accumulation from hourly rainfall data that have been screened by proper quality control procedures. For each station and for each accumulation period, the historical maximum is found, and the corresponding 50-year return values are estimated using generalized extreme value theory. Based on the percentiles of the two types of extreme rainfall values among all the stations, standard thresholds separating Grade I, Grade II and Grade III extreme rainfall are established, which roughly correspond to the 70th and 90th percentiles for each of the accumulation periods. The spatial characteristics of the two types of extreme rainfall are then examined for different accumulation periods. The spatial distributions of extreme rainfall in hourly through 6-h periods are more similar than those of 12-and 24-h periods. Grade III rainfall is mostly found over South China, the western Sichuan Basin, along the southern and eastern coastlines, and in the large river basins and plains. There are similar numbers of stations with Grade III extreme hourly rainfall north and south of 30 • N, but the percentage increases to about 70% south of 30 • N as the accumulation period increases to 24 hours, reflecting richer moisture and more prolonged rain events in southern China. Potential applications of the extreme rainfall climatology and classification standards are suggested at the end.

Storm impacts on phytoplankton community dynamics in lakes

“…Extreme weather events (EWEs) are ranked as the highest global risk in terms of likelihood of occurrence and third highest in impact, ranking behind only weapons of mass destruction and failure to mitigate and adapt to climate change (World Economic Forum, 2019). The transient and lasting effects of EWEs (including droughts, heat waves, and storms) on ecosystems are undeniable (Coumou & Rahmstorf, 2012; Knapp et al, 2002; Nielsen & Ball, 2015; Thibault & Brown, 2008; Zheng, Xue, Li, Chen, & Tao, 2016), but are much less understood than the effects of longer‐term changes in average environmental conditions (Carvalho et al, 2012; Jentsch, Kreyling, & Beierkuhnlein, 2007; Jeppesen et al, 2005; Parmesan, Root, & Willig, 2000; Walther et al, 2002). EWEs and changes in their frequency, intensity, and duration may be just as important as these longer‐term changes for ecological and evolutionary processes (Jentsch et al, 2007; Lawson, Vindenes, Bailey, & van de Pol, 2015; Vasseur et al, 2014), encompassing levels of organization from genes to ecosystems (Ehrlich et al, 1980; Gutschick & BassiriRad, 2003; Knapp et al, 2015).…”

What Is the Main Cause of Diurnal Variation and Nocturnal Peak of Summer Precipitation in Sichuan Basin, China? The Key Role of Boundary Layer Low‐Level Jet Inertial Oscillations

“…Sichuan Basin (SB) is located immediately east of the Tibetan Plateau (TP) in southwestern China (Figure ). It is one of the warm season precipitation maximum centers in China (J. Lin & Yang, ; Yu et al, ; Zheng et al, ). Heavy rainfall can cause river, urban and rural area flooding, mountain flash floods and landslides, and interrupt transportations, farming, and industrial activities and lead to great economic losses (D.‐Q.…”

“…Studies have shown that precipitation in SB has strong diurnal variations. Nocturnal precipitation has been found to account for up to 70% of the total precipitation in SB (Zheng et al, ), which is usually called “Bashan Yeyu” (nocturnal precipitation in Bashan Mountains; Lv, ). Both rain gauge and satellite observations reveal that, from pre‐Meiyu season to midsummer, precipitation peak usually occurs at night and early morning in SB (Bao et al, ; G. Chen et al, ; Qian et al, ; Shen & Zhang, ; Xu & Zipser, ; Yin et al, ; Yu, Xu, et al, ; Yu, Zhou, et al, ; Yuan et al, ).…”

Performance of multi-level association rule mining for the relationship between causal factor patterns and flash flood magnitudes in a humid area

“…Causal factors of flash flood hazards are various because of the specific hydrological and environmental characteristics of each location. After carefully reviewing the literatures and field survey in the study area (Zhang et al 2010;Zheng et al 2016), total 24-h rainfall (TR), elevation (DE), slope degree (SD), vegetation cover (VC), soil type (ST), drainage density (DD), and SM are selected as risk factors of flash flood hazards in Upper Hanjiang River. In this research, 31 flash flood events in the study area over the period of 2011, 2012, and 2013 have been considered.…”