Recent Trends of Extreme Precipitation and Their Teleconnection with Atmospheric Circulation in the Beijing-Tianjin Sand Source Region, China, 1960–2014

Abstract

Based on the daily precipitation data from 53 meteorological stations, 11 extreme precipitation indices were selected, categorized and calculated; the temporal and spatial patterns in these indices and their teleconnections with the large-scale circulations were analyzed by the non-parametric Mann-Kendall test; and Sen's slope estimator and linear regression for the period of 1960-2014 were calculated. The results indicated that all extreme precipitation indices had spatial patterns decreasing from the southeastern to the northwestern parts of the Beijing-Tianjin Sand Source Region (BTSSR), except for the consecutive dry days (CDD), which exhibited a reverse spatial pattern. At the whole-region scale, most extreme precipitation indices showed an insignificant decreasing trend, with exceptions in the intensity indices (RX1day and RX5day) with a statistical significance at the 90% confidence level. The total annual precipitation showed a general shift towards a drier climate in the study area. Spatially, all indices for extreme precipitation showed decreasing trends at most stations, except for simple daily intensity index (SDII) and heavy precipitation days (R10). The change in extreme precipitation may be affected by the El Niño-Southern Oscillation (ENSO), East Asian Summer Monsoon (EASM) and Pacific Decadal Oscillation (PDO). Better understanding of extreme precipitation for the BTSSR may be useful in the regional planning for ecological restoration and water management.

Analysis of Precipitation Extremes in the Qinghai-Tibetan Plateau, China: Spatio-Temporal Characteristics and Topography Effects

“…A great many statistical methods have been developed to detect the trend in long-time series of hydro-meteorological variables, including parametric and non-parametric methods [43][44][45]. The non-parametric Mann-Kendall (MK) test [46,47] is a valid tool for assessing the significance of monotonic trends in hydro-meteorological time series; it is suitable for non-normally distributed data, including missing values, and it is less influenced by the presence of outliers in the data [48]).…”

Temporal Trends and Spatial Patterns of Temperature and Its Extremes over the Beijing-Tianjin Sand Source Region (1960–2014), China

“…However, increasing trends can also increase regional evapotranspiration [26] which, in conjunction with a decreasing trend in precipitation in the BTSSR [77], will increase the risk of drought [78]. The tradeoff of change trends of these meteorological factors is currently unclear.…”

“…However, in water-limited areas of the BTSSR, increasing temperature in the growing season may exacerbate rain-fed plant stress due to high temperatures combined with decreasing precipitation [77,91], especially for vegetation planted (shrubs or trees) as part of the degraded land restoration project in the BTSSR.…”

Trend and spatial variability of 1-day extreme rainfall from 1980 - 2015: study at the adminisitrative area of UPT PSDA Pasuruan

“…Penelitian terkait kecenderungan telah banyak dilakukan dengan tujuan untuk mengetahui, membandingkan metode ataupun untuk mengetahui kecenderungan beberapa unsur iklim seperti curah hujan, temperatur dan evaporasi (Subarna, 2014). Analisis kecenderungan hujan (tahunan, ekstrim, dan bulanan) di beberapa negara, sudah umum dilakukan, misalnya di India (Kumar et al, 2010), di China (Jun et al, 2012;Wei et al, 2017), di Australia (Hajani et al, 2014); dan Malaysia (Zin et al, 2010;Faizah et al, 2016). Di Indonesia, Komalasari (2017) melakukan analisis karakteristik curah hujan ekstrim untuk pulau Jawa dan proyeksinya di masa depan.…”