Shuwen Zhang

Dr. Shuwen Zhang

orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

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

Representative Publications

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4 July 2019 in Remote Sensing
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Journal Article
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RDRuijun Dang
Ruijun Dang
YYYi Yang
Yi Yang
XHXiao-Ming Hu
Xiao-Ming Hu
ZWZhiting Wang
Zhiting Wang
SZShuwen Zhang
Shuwen Zhang
The height of the atmospheric boundary layer (ABLH) or the mixing layer height (MLH) is a key parameter characterizing the planetary boundary layer, and the accurate estimation of that is critically important for boundary layer related studies, which include air quality forecasts and numerical weather prediction. Aerosol lidar is a powerful remote sensing instrument frequently used to retrieve the ABLH through detecting the vertical distributions of aerosol concentration. Presently available methods for ABLH determination from aerosol lidar are summarized in this review, including a lot of classical methodologies as well as some improved versions of them. Some new recently developed methods applying advanced techniques such as image edge detection, as well as some new methods based on multi-wavelength lidar systems, are also summarized. Although a lot of techniques have been proposed and have already given reasonable results in several studies, it is impossible to recommend a technique which is suitable in all atmospheric scenarios. More accurate instantaneous ABLH from robust techniques is required, which can be used to estimate or improve the boundary layer parameterization in the numerical model, or maybe possible to be assimilated into the weather and environment models to improve the simulation or forecast of weather and air quality in the future.

1 November 2005 in Advances in Atmospheric Sciences
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Journal Article
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SZShuwen Zhang
Shuwen Zhang
LHLi Haorui
Li Haorui
ZWZhang Weidong
Zhang Weidong
QCQiu Chongjian
Qiu Chongjian
LXLi Xin
Li Xin

24 July 2021 in Atmosphere
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Journal Article
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Lili YangLili Yang
Lili Yang
SZShuwen Zhang
Shuwen Zhang
Zhongwei HuangZhongwei Huang
Zhongwei Huang
YYYanping Yang
Yanping Yang
LWLina Wang
Lina Wang
XLXiaoyun Li
Xiaoyun Li
As the main source of dust in Asia, China often suffers from dust events. The temporal and spatial characteristics of dust events change with the variations of geography, climate and human activities. Based on the criteria of selecting dust events proposed recently by the China Environmental Monitoring Station, the hourly concentration of PM10 and PM2.5 of 336 cities in China from 2015 to 2020 were used to study the temporal and spatial characteristics of dust events more accurately and objectively. The results showed that all of the dust events in China clearly decreased, but the strong dust events did not decrease. There were 334 cities that had dust events except Shenzhen and Dongguan, 299 cities were seriously polluted due to dust events, 134 cities encountered dust level III and 56 cities encountered dust level IV. The high frequencies of dust events were mainly distributed in Northern China, especially in Northwest China. The dust contribution of PM10 to the cities in Northwest China was more than 10% and about 5–10% for PM2.5. The most likely month for dust was May. The starting time of dust was bimodally distributed, and the most common starting time was 10:00–11:00 BJT, followed by 22:00–23:00 BJT. According to the PSCF (Potential Source Contribution Function) results, the dust potential source contribution of different cities mainly came from the northwest, and was mainly affected by Mongolia in addition to the local dust in China. In addition, Beijing was obviously affected by dust recirculation. This study is of great significance to the improvement of the forecast of dust weather and the warning of heavy pollution caused by dust events.

1 August 2018 in Journal of Meteorological Research
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HZHaibo Zou
Haibo Zou
SZShuwen Zhang
Shuwen Zhang
XLXudong Liang
Xudong Liang
XYXueting Yi
Xueting Yi
Using China New Generation Weather Radar (CINRAD) level-II data, the original algorithms for removing isolated non-meteorological echoes and ground clutters in radar data, which have been applied to Weather Surveillance Radar-1988 Doppler (WSR-88D) in the USA and Severe Weather Automatic Nowcast (SWAN) system in China, are modified and improved. To remove isolated non-meteorological echoes, the new algorithm introduces a constraint parameter (Po) to distinguish whether a window of 5 × 5 points is isolated as external echoes. A statistical analysis of 150 radar scans (5 cases, with each case comprising 30 scans) under three different echo types (small-scale convection, typhoon, and large-scale synoptic system) shows that the constraint parameter Po ⩽ 0.167 is suitable for removing isolated non-meteorological echoes while preserving the edge of meteorological echoes. A new parameter, NDZ, which promotes the ability of the algorithm to identify the ground clutters appearing at two adjacent elevation angles, is constructed based on the vertical continuity of reflectivity. These improved algorithms are tested for four cases (three cases of isolated non-meteorological echoes and one case of ground clutters). Based on the statistics of 232 volume scans of radar data (on a temporal resolution of 1 h) measured at Nanchang station from 0000 UTC 5 to 1600 UTC 14 March 2015, it is found that the improved algorithms not only eliminate most (over 95% under clear-sky conditions) of the isolated non-meteorological echoes and ground clutters (including those appearing at two adjacent elevation angles), but also well preserve the structure of meteorological echoes (storms). Key words: radar, isolated non-meteorological echoes, ground clutter, quality control

1 June 2020 in Journal of Meteorological Research
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HZHaibo Zou
Haibo Zou
SZShuwen Zhang
Shuwen Zhang
YLYanan Liu
Yanan Liu
WZWeidong Zhang
Weidong Zhang
XYXixi Yang
Xixi Yang

30 December 2010 in Advances in Atmospheric Sciences
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SZShuwen Zhang
Shuwen Zhang
DLDeqin Li
Deqin Li
CQChongjian Qiu
Chongjian Qiu