Yuqing Zhang

Dr. Yuqing Zhang

School of Urban and Environmental Sciences, Huaiyin Normal University, Huai’an 223300, China
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 March 2023 in Science of The Total Environment
Verified
Journal Article
Closed access
Yuqing ZhangYuqing Zhang
Yuqing Zhang
QYQinglong You
Qinglong You
SUSafi Ullah
Safi Ullah
CCChangchun Chen
Changchun Chen
LSLiucheng Shen
Liucheng Shen
ZLZhu Liu
Zhu Liu

18 January 2018 in Journal of Climate
Verified
Journal Article
Open access
Yuqing ZhangYuqing Zhang
Yuqing Zhang
QYQinglong You
Qinglong You
CCChangchun Chen
Changchun Chen
JGJing Ge
Jing Ge
MAMuhammad Adnan
Muhammad Adnan
Compared to traditional drought events, flash droughts evolve rapidly during short-term extreme atmospheric conditions, with a lasting period of one pentad to several weeks. There are two main categories of flash droughts: the heat wave flash drought (HWFD), which is mainly caused by persistent high temperatures (heat waves), and the precipitation deficit flash drought (PDFD), which is mainly triggered by precipitation deficits. The authors’ previous research focused on the characteristics and causes of flash drought based on meteorological observations and Variable Infiltration Capacity (VIC) model simulations in a humid subtropical basin (Gan River basin, China). In this study, the authors evaluated the downscaled phase 5 of the Coupled Model Intercomparison Project (CMIP5) models’ simulations, coupled with the VIC model (CMIP5–VIC) in reproducing flash droughts in a humid subtropical basin in China. Most downscaled CMIP5–VIC simulations can reproduce the spatial patterns of flash droughts with respect to the benchmarks. The coupled models fail to readily replicate interannual variation (interannual pentad change), but most models can reflect the interannual variability (temporal standard deviation) and long-term average pentads of flash droughts. It is difficult to simultaneously depict both the spatial and temporal features of flash droughts within only one coupled model. The climatological patterns of the best multimodel ensemble mean are close to those of the all-model ensemble mean, but the best multimodel ensemble mean has a minimal bias range and relatively low computational burden.

1 June 2021 in Weather and Climate Extremes
Verified
Journal Article
Open access
Yuqing ZhangYuqing Zhang
Yuqing Zhang
XSXiubao Sun
Xiubao Sun
CCChangchun Chen
Changchun Chen

14 August 2018 in Climate Dynamics
Verified
Journal Article
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PDF file
Yuqing ZhangYuqing Zhang
Yuqing Zhang
QYQinglong You
Qinglong You
GMGuangxiong Mao
Guangxiong Mao
CCChangchun Chen
Changchun Chen
ZYZhengwei Ye
Zhengwei Ye

3 May 2021 in Atmospheric Science Letters
Verified
Journal Article
Open access
PDF file
LSLiucheng Shen
Liucheng Shen
Yuqing ZhangYuqing Zhang
Yuqing Zhang
SUSafi Ullah
Safi Ullah
NPNick Pepin
Nick Pepin
QMQianrong Ma
Qianrong Ma
Snow plays an essential role in regulating climate change, the hydrological cycle, and various biological processes. Passive microwave snow depth data and gridded data from the Climate Research Unit (CRU_TS4.04) are utilized in this study to investigate spatiotemporal variations of snow depth over the Tibetan Plateau (TP), with special focus on the vertical dimension. The response of snow to elevation‐dependent warming (EDW) is determined accordingly. High mountains experience more rapid warming than lower elevations. During 1980–2014, the total snow depth over the TP decreased; areas with the most significant decreasing trends are mainly concentrated in the northwestern and southwestern parts of the TP. The plateau‐wide decrease in snow depth (−0.24 cm/decade) is mainly affected by increasing temperature (0.30°C/decade). The reduction in snow depth trend intensifies as sub‐regional mean elevation increases from 3,332 m (IID2) to 5,074 m (ID1). A stronger snow depth decrease in high‐elevation sub‐regions generally corresponds to higher warming rates, which demonstrates EDW. The most pronounced correlation between snow depth decrease rate and elevation occurs in the southeastern TP, which covers the largest elevation range on the plateau (from 2,000 to 6,000 m).

1 October 2020 in Sustainable Cities and Society
Verified
Journal Article
Closed access
Yuqing ZhangYuqing Zhang
Yuqing Zhang
GMGuangxiong Mao
Guangxiong Mao
CCChangchun Chen
Changchun Chen
ZLZhonghui Lu
Zhonghui Lu
LZluo zhen
luo zhen
WZWenting Zhou
Wenting Zhou