scholarly journals Impact of the Westerly Jet on Rainfall/Runoff in the Source Region of the Yangtze River during the Flood Season

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xin Lai ◽  
Yuanfa Gong ◽  
Sixian Cen ◽  
Hui Tian ◽  
Heng Zhang

Based on runoff data collected at the Zhimenda station, reanalysis data from the National Centers of Environmental Prediction/National Centers of Atmospheric Research (NCEP/NCAR), and observation data from ground stations in China, this study analyzes the characteristics of changes in runoff in the source region of the Yangtze River (SRYR) during the flood season (from July to September), the relationship between runoff and antecedent rainfall, and the impact of the westerly jet (WJ) on rainfall in the coastal zone of the SRYR. The results show the following. The runoff in the SRYR displays a significant interannual and interdecadal variability. The runoff in the SRYR during the flood season is most closely related to 15-day (June 16 to September 15) antecedent rainfall in the coastal zone of the SRYR. In turn, the antecedent rainfall in the coastal zone of the SRYR is mainly affected by the intensity of the simultaneous WJ over a key region (55–85°E, 45–55°N). When the intensity of the WJ over the key region is greater (less) than normal, the jet position moves northward (southward), and the easterly (westerly) wind anomalies over the region to the west of the SRYR become unfavorable (favorable) to the transport of water vapor from high-latitude regions to the SRYR. In addition, the southerly wind over the equatorial region cannot (can) easily advance northward, which is unfavorable (favorable) to the northward transport of water vapor from the low-latitude ocean. Hence, these conditions result in a decrease (increase) in the water vapor content in the SRYR. Furthermore, the convergence (divergence) anomalies in the upper level and the divergence (convergence) anomalies in the lower level result in the descending (ascending) motion over the SRYR. These factors decrease (increase) the rainfall, thereby decreasing (increasing) the runoff in the SRYR during the flood season.

2009 ◽  
Vol 55 (190) ◽  
pp. 353-362 ◽  
Author(s):  
Liu Shiyin ◽  
Zhang Yong ◽  
Zhang Yingsong ◽  
Ding Yongjian

AbstractGlacier runoff from the Yangtze River source region (YRSR), China, is estimated for the period 1961–2000 using a degree-day approach. In the investigation area, glacier runoff accounts for 11.0% of the total river runoff during the period 1961–2000. In the 1990s its contribution to river runoff rises to 17.0%. Due to the current rate of glacier decline, the impact of glacier runoff on river runoff has recently increased in the source region. Based on two different climate-change scenarios derived from ECHAM5/MPI-OM, future glacier runoff is assessed for the period 2001–50. In all climate-change scenarios, annual glacier runoff shows a significant increase due to intensified ice melting. There is an increase in glacier runoff during spring and early summer, yet a significant decrease in late summer. This study highlights the current and future impact of glacier runoff on river runoff in the YRSR.


2021 ◽  
Vol 9 ◽  
Author(s):  
Yicong Xia ◽  
Qian Huang ◽  
Suxiang Yao ◽  
Tianle Sun

Based on observation data supplied by the Chinese Meteorological Administration (CMA) and reanalysis datasets provided by the ECMWF, the multiscale causes of persistent heavy rainfall events (PHREs) that occurred from 1979 to 2018 during Meiyu periods over the middle and lower reaches of the Yangtze River (MLYR) are investigated. During Meiyu periods, precipitation shows obvious interannual variabilities. In PHRE years, the contribution rate of persistent heavy rainfall to the total precipitation is approximately 57%. Precipitation also shows significant synoptic-scale (less than 10 days) characteristics. Through the quantitative diagnosis of interactions among background-scale (greater than 30 days), quasi-biweekly-scale (10–30-days), and synoptic-scale variables, the possible causes of PHREs are explored. The results reveal that the difference in precipitation intensity between PHRE years and non-PHRE years is determined by the background water vapor, background wind and synoptic-scale wind conditions. In PHRE years, the prevailing background southwesterly winds from lower latitudes provide more background water vapor, and more mean kinetic energy is converted to perturbation energy. Moreover, the active synoptic-scale oscillations from higher latitudes and the convergence of Rossby wave disturbance energy over the MLYR could also cause the occurrence and maintenance of PHREs during Meiyu periods. The multiscale causes and corresponding circulation patterns in 2020 PHREs are similar to PHREs years.


2014 ◽  
Vol 6 (2) ◽  
pp. 124 ◽  
Author(s):  
Chongyi E ◽  
Hongchang Hu ◽  
Hong Xie ◽  
Yongjuan Sun

The study of temperature change and its elevation dependency in the source region of the Yangtze River and Yellow River have been insufficient owing to the lack of adequate observation stations and long-term climatic data. In this study five temperature indices of 32 stations from 1961 to 2007 in and near the source region are used. The 32 stations all have experienced significant warming; the warming amplitudes are higher than the mean warming amplitude of the Qinghai-Tibetan plateau. The warming amplitudes and the numbers of stations showing significant warming trends in mean minimum temperature and extreme minimum temperature are higher than that of the mean maximum temperature and extreme maximum temperature. The elevation dependency of climatic warming and the amount of significant warming stations are not obvious; the influence of human activity and urbanization may be higher. The warming amplitudes of 26 stations above 3000 m tend to be uniform, and there is no significant law at 6 stations below 3000 m. On the contrary, the ratio of stations showing significant warming in minimum temperature above 4000 m is far less than that of the stations below 4000 m.


2021 ◽  
Vol 35 (4) ◽  
pp. 557-570
Author(s):  
Licheng Wang ◽  
Xuguang Sun ◽  
Xiuqun Yang ◽  
Lingfeng Tao ◽  
Zhiqi Zhang

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