Ying Xu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Ying Xu has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Abhishek
Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India
1 shared publication - Biao Long
Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences Lanzhou University Lanzhou China
1 shared publication - Chuanqiao Zhou
Graduate School of Informatics, Kyoto University, Kyoto, Japan
1 shared publication - Jian Zhang
College of Hydraulic Science and Engineering Yangzhou University Yangzhou China
1 shared publication - Jingwen Hu
College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China
1 shared publication - Shuoyuan Liang
School of Environment and Society, Institute of Science Tokyo, Yokohama 226-8503, Japan
1 shared publication
Latest Publications
- Open Access
Spatiotemporal Patterns and Atmospheric Drivers of Anomalous Precipitation in the Taihu Basin, Eastern China
This study investigates anomalous precipitation patterns in the Taihu Basin, located in the Yangtze River Delta of eastern China, using high-resolution daily data from 1960 to 2019. Leveraging a deep learning autoencoder and self-organizing map, three spatially distinct types are identified—north type (72%), south type (19.7%), and center type (8.3%). The north type exhibits a pronounced upward trend (+0.11 days/year, p < 0.05), indicating intensifying extreme rainfall under climate warming, while the south type displays a bimodal temporal structure, peaking in early summer and autumn. Composite analyses reveal that these patterns are closely associated with the westward extension of the Western North Pacific Subtropical High (WNPSH), meridional shifts of the East Asian Westerly Jet (EAJ), low-level moisture convergence, and SST–OLR anomalies. For instance, north-type events often coincide with strong anticyclonic anomalies and enhanced moisture transport from the Northwest Pacific and South China Sea, forming favorable convergence zones over the basin. For flood management in the Taihu Basin, the identified spatial patterns, particularly the bimodal south type, have clear implications. Their strong link to specific circulation features enables certain flood-prone scenarios to be anticipated 1–2 seasons in advance, supporting proactive measures such as reservoir scheduling. Overall, this classification framework deepens the understanding of atmospheric patterns associated with flood risk and provides practical guidance for storm design and adaptive flood risk management under a changing climate.
Open AccessSpatiotemporal Patterns and Atmospheric Drivers of Anomalous Precipitation in the Taihu Basin, Eastern China
This study investigates anomalous precipitation patterns in the Taihu Basin, located in the Yangtze River Delta of eastern China, using high-resolution daily data from 1960 to 2019. Leveraging a deep learning autoencoder and self-organizing map, three spatially distinct types are identified—north type (72%), south type (19.7%), and center type (8.3%). The north type exhibits a pronounced upward trend (+0.11 days/year, p < 0.05), indicating intensifying extreme rainfall under climate warming, while the south type displays a bimodal temporal structure, peaking in early summer and autumn. Composite analyses reveal that these patterns are closely associated with the westward extension of the Western North Pacific Subtropical High (WNPSH), meridional shifts of the East Asian Westerly Jet (EAJ), low-level moisture convergence, and SST–OLR anomalies. For instance, north-type events often coincide with strong anticyclonic anomalies and enhanced moisture transport from the Northwest Pacific and South China Sea, forming favorable convergence zones over the basin. For flood management in the Taihu Basin, the identified spatial patterns, particularly the bimodal south type, have clear implications. Their strong link to specific circulation features enables certain flood-prone scenarios to be anticipated 1–2 seasons in advance, supporting proactive measures such as reservoir scheduling. Overall, this classification framework deepens the understanding of atmospheric patterns associated with flood risk and provides practical guidance for storm design and adaptive flood risk management under a changing climate.