Effect of tropical Indian Ocean thermal condition during preceding winter on summer high temperature anomalies over the southern Yangtze River valley

2016 ◽  
Vol 37 (8) ◽  
pp. 3478-3490 ◽  
Author(s):  
Ge Liu ◽  
Renguang Wu ◽  
Huimei Wang ◽  
Liren Ji
Keyword(s):  
High Temperature ◽  
Indian Ocean ◽  
Yangtze River ◽  
Thermal Condition ◽  
Tropical Indian Ocean ◽  
Yangtze River Valley ◽  
River Valley ◽  
Temperature Anomalies ◽  
Preceding Winter

scholarly journals New Predictors and a Statistical Forecast Model for Mei-Yu Onset Date in the Middle and Lower Reaches of the Yangtze River Valley

2014 ◽  
Vol 29 (3) ◽  
pp. 654-665 ◽  
Author(s):  
Yijia Hu ◽  
Yimin Zhu ◽  
Zhong Zhong ◽  
Yao Ha
Keyword(s):  
Yangtze River ◽  
Asian Summer Monsoon ◽  
East Asian ◽  
Forecast Model ◽  
Yangtze River Valley ◽  
River Valley ◽  
Onset Date ◽  
The Yangtze River ◽  
Tropical Ocean ◽  
Preceding Winter

Abstract The prediction of mei-yu onset date (MOD) in the middle and lower reaches of the Yangtze River valley (MLYRV) is an important and challenging task for those making seasonal climate predictions in China. In this paper, the atmospheric and oceanic conditions in the preceding winter and spring related to MOD are analyzed. It is found that the MOD is associated with the intensity of the Ural high and the East Asian trough in high latitudes, with the intensity of the upper-level westerly jet in middle latitudes, and with the contrast of land–sea temperature and pressure in the preceding winter and spring, which are proxies for the intensity of the East Asian winter monsoon (EAWM). It is suggested that the intensity of the EAWM is the most crucial factor affecting the MOD. Years with an early MOD usually correspond to strong EAWMs in the preceding winter, and vice versa. The EAWM can affect the MOD by influencing the East Asian summer monsoon (EASM) through tropical ocean–atmosphere and tropical–extratropical interactions. Based on the above analysis, a physics-based statistical forecast model is established using multivariable linear regression techniques. The hindcast of MOD during the 13 yr from 1998 to 2010 is carried out to evaluate the performance of this forecast model. The MOD can be predicted successfully in 8 out of the 13 yr. The forecast model predicts the MOD in the years with strong mei-yu intensity more accurately than in those with weak mei-yu intensity, especially for cases of extreme flooding. This is useful in the prevention of flooding disasters.

scholarly journals Swarms of brown planthopper migrate into the lower Yangtze River Valley under strong western Pacific subtropical highs

Ecosphere ◽  
2017 ◽  
Vol 8 (10) ◽  
pp. e01967 ◽  
Author(s):  
Ming-Hong Lu ◽  
Xiao Chen ◽  
Wan-Cai Liu ◽  
Feng Zhu ◽  
Ka-Sing Lim ◽  
...  
Keyword(s):  
Yangtze River ◽  
Brown Planthopper ◽  
Yangtze River Valley ◽  
River Valley ◽  
Western Pacific ◽  
Subtropical Highs ◽  
Lower Yangtze

scholarly journals Vulnerability of rice production to temperature extremes during rice reproductive stage in Yangtze River Valley, China

2021 ◽  
Vol 33 (8) ◽  
pp. 101599
Author(s):  
Muhammad Ishaq Asif Rehmani ◽  
Chengqiang Ding ◽  
Ganghua Li ◽  
Syed Tahir Ata-Ul-Karim ◽  
Adel Hadifa ◽  
...  
Keyword(s):  
Yangtze River ◽  
Yangtze River Valley ◽  
River Valley ◽  
Rice Production ◽  
Reproductive Stage ◽  
Temperature Extremes

scholarly journals Skillful seasonal prediction of Yangtze river valley summer rainfall

2016 ◽  
Vol 11 (9) ◽  
pp. 094002 ◽  
Author(s):  
Chaofan Li ◽  
Adam A Scaife ◽  
Riyu Lu ◽  
Alberto Arribas ◽  
Anca Brookshaw ◽  
...  
Keyword(s):  
Yangtze River ◽  
Summer Rainfall ◽  
Seasonal Prediction ◽  
Yangtze River Valley ◽  
River Valley
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