Spatiotemporal changes in precipitation extremes over Yangtze River basin, China, considering the rainfall shift in the late 1970s

2016 ◽  
Vol 147 ◽  
pp. 106-124 ◽  
Author(s):  
Tao Gao ◽  
Lian Xie
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Precipitation Extremes ◽  
Spatiotemporal Changes

Precipitation extremes in the Yangtze River Basin, China: regional frequency and spatial–temporal patterns

2013 ◽  
Vol 116 (3-4) ◽  
pp. 447-461 ◽  
Author(s):  
Yongqin David Chen ◽  
Qiang Zhang ◽  
Mingzhong Xiao ◽  
Vijay P. Singh ◽  
Yee Leung ◽  
...  
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Temporal Patterns ◽  
Precipitation Extremes ◽  
The Yangtze River ◽  
The Yangtze River Basin ◽  
Regional Frequency

Weakening Influence of Spring Soil Moisture over the Indo-China Peninsula on the Following Summer Mei-Yu Front and Precipitation Extremes over the Yangtze River Basin

2020 ◽  
Vol 33 (23) ◽  
pp. 10055-10072
Author(s):  
Chujie Gao ◽  
Gen Li ◽  
Bei Xu
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Summer Monsoon ◽  
Yangtze River ◽  
Large Scale ◽  
Asian Summer Monsoon ◽  
Yangtze River Basin ◽  
Precipitation Extremes ◽  
The Yangtze River ◽  
The Yangtze River Basin

AbstractThe seasonal prediction of precipitation extremes over the Yangtze River basin (YRB) has always been a great challenge. This study investigated the effects of spring soil moisture over the Indo-China Peninsula (ICP) on the following summer mei-yu front and YRB precipitation extremes during 1961–2010. The results indicated that the frequency of summer YRB precipitation extremes was closely associated with the mei-yu front intensity, which exhibited a strong negative correlation with the preceding spring ICP soil moisture. However, the lingering climate influence of the ICP soil moisture was unstable, with an obvious weakening since the early 1990s. Due to its strong memory, an abnormally lower spring soil moisture over the ICP would increase local temperature until the summer by inducing less evapotranspiration. Before the early 1990s, the geopotential height elevation associated with the ICP heating affected the western Pacific subtropical high (WPSH), strengthening the southwesterly summer monsoon. Consequently, the mei-yu front was intensified as more warm, wet air was transported to the YRB, and local precipitation extremes also occurred more frequently associated with abnormal ascending motion mainly maintained by the warm temperature advection. In the early 1990s, the Asian summer monsoon underwent an abrupt shift, with the changing climatological states of the large-scale circulations. Therefore, the similar ICP heating induced by the anomalous soil moisture had different effects on the monsoonal circulation, resulting in weakened responses of the mei-yu front and YRB precipitation extremes since the early 1990s.

scholarly journals Anthropogenic Influences on 2019 July Precipitation Extremes Over the Mid–Lower Reaches of the Yangtze River

2020 ◽  
Vol 8 ◽  
Author(s):  
Nergui Nanding ◽  
Yang Chen ◽  
Huan Wu ◽  
Buwen Dong ◽  
Fangxing Tian ◽  
...  
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Heavy Precipitation ◽  
Precipitation Extremes ◽  
Mitigation Measures ◽  
Anthropogenic Influences ◽  
The Yangtze River ◽  
Major Floods ◽  
Industrial Needs

Understanding the driving factors for precipitation extremes matters for adaptation and mitigation measures against the changing hydrometeorological hazards in Yangtze River basin, a habitable area that provides water resources for domestic, farming, and industrial needs. However, the region is naturally subject to major floods linked to monsoonal heavy precipitation during May–September. This study aims to quantify anthropogenic influences on the changing risk of 2-week-long precipitation extremes such as the July 2019 extreme cases, as well as events of shorter durations, over the middle and lower reaches of Yangtze River basin (MLYRB). Precipitation extremes with different durations ranging from 1-day to 14-days maximum precipitation accumulations are investigated. Gridded daily precipitations based on nearly 2,400 meteorological stations across China are used to define maximum accumulated precipitation extremes over the MLYRB in July during 1961–2019. Attribution analysis is conducted by using the Met Office HadGEM3-GA6 modeling system, which comprises two sets of 525-member ensembles for 2019. One is forced with observed sea-surface temperatures (SSTs), sea-ice and all forcings, and the other is forced with preindustrialized SSTs and natural forcings only. The risk ratio between the exceedance probabilities estimated from all-forcing and natural-forcing simulations is calculated to quantify the anthropogenic contribution to the changing risks of the July 2019–like precipitation extremes. The results reveal that anthropogenic warming has reduced the likelihood of 2019-like 14-days heavy precipitation over the mid–lower reaches of the Yangtze River by 20%, but increased that of 2-days extremes by 30%.

scholarly journals Multivariate Regression Analysis and Statistical Modeling for Summer Extreme Precipitation over the Yangtze River Basin, China

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Tao Gao ◽  
Lian Xie
Keyword(s):  
Heat Flux ◽  
Prediction Model ◽  
River Basin ◽  
Extreme Precipitation ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Precipitation Extremes ◽  
Statistical Prediction ◽  
Global Ocean ◽  
The Impact

Extreme precipitation is likely to be one of the most severe meteorological disasters in China; however, studies on the physical factors affecting precipitation extremes and corresponding prediction models are not accurately available. From a new point of view, the sensible heat flux (SHF) and latent heat flux (LHF), which have significant impacts on summer extreme rainfall in Yangtze River basin (YRB), have been quantified and then selections of the impact factors are conducted. Firstly, a regional extreme precipitation index was applied to determine Regions of Significant Correlation (RSC) by analyzing spatial distribution of correlation coefficients between this index and SHF, LHF, and sea surface temperature (SST) on global ocean scale; then the time series of SHF, LHF, and SST in RSCs during 1967–2010 were selected. Furthermore, other factors that significantly affect variations in precipitation extremes over YRB were also selected. The methods of multiple stepwise regression and leave-one-out cross-validation (LOOCV) were utilized to analyze and test influencing factors and statistical prediction model. The correlation coefficient between observed regional extreme index and model simulation result is 0.85, with significant level at 99%. This suggested that the forecast skill was acceptable although many aspects of the prediction model should be improved.

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