Feng Shang Li

Dr. Feng Shang Li


Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

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

Representative Publications

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19 December 2012 in Advances in Atmospheric Sciences
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YLYi Lian
Yi Lian
BSBaizhu Shen
Baizhu Shen
FLFeng Shang Li
Feng Shang Li
BZBin Zhao
Bin Zhao
ZGZongting Gao
Zongting Gao
LCLing Cao
Ling Cao

1 August 2016 in Journal of Meteorological Research
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FLFeng Shang Li
Feng Shang Li
DJDabang Jiang
Dabang Jiang
YLYi Lian
Yi Lian
YYYaoxian Yao
Yaoxian Yao
Based on the daily mean temperature data of CN05.2 from 1961 to 2012, cold events (CEs) are first divided into two categories according to their duration: strong cold events (SCEs) and weak cold events (WCEs). Then, the characteristics of CEs, SCEs, and WCEs during springtime are investigated. The results indicate that in the pre-1990s epoch, ENSO and Arctic Oscillation events in the previous winter are closely related to SCEs in the following spring. The multidecadal variations of CEs, SCEs, and WCEs are obvious. The intensity trend for SCEs is significantly negative, but it seems less apparent for WCEs. Further analysis reveals that when both SCEs and WCEs occur, a typical East Asian trough in the 850- hPa wind field, whose northwesterly wind component invades Northeast China (NEC) and causes freezing days, can be found in every decade. For the SCEs, a cold vortex, with its center located over Okhotsk and northeasterly current affecting NEC, is found as an additional feature. For the WCEs, the cold vortex is located in Karafuto and its northwesterly airflow intrudes into NEC. As for the difference between SCEs and WCEs, the northwestern flow is weaker while the northeastern counterpart is stronger during the SCEs, in all decades. In the Takaya–Nakamura flux and divergence fields, for the SCEs, a divergence center exists over NEC; and over its downstream regions, a stronger divergence center appears, not like a wave train. However, the opposite is the case for the WCEs; moreover, the wave train appears clearly during the WCEs, which means that the wave energy can propagate and dissipate more easily during WCEs.

16 January 2023 in Atmosphere
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CSChen Shi
Chen Shi
ZLZhongda LIN
Zhongda LIN
YLYi Lian
Yi Lian
FLFeng Shang Li
Feng Shang Li
XYXu Yang
Xu Yang
GLGang Liu
Gang Liu
Summer in the East Asian monsoon region is characterized by heavy rainfall and high temperature. Its onset, depicted by monsoon rainfall and/or airflow as well as surface air temperature, has been well documented. However, the onset of summer season is rarely addressed in northern East Asia (NEA) around the northern edge of the East Asian summer monsoon. This study investigates the feature, mechanism, and variability of the summer onset in NEA based on the ERA-5 reanalysis dataset for 1979–2020. Results show that, in climatology, the onset of summer in NEA occurs in pentad 31 when the spring-to-summer warming process is decelerated at the highest rate. The change in the warming rate is mainly attributed to a decrease in the diabatic heat, mostly surface sensible heat, and temperature advection plays a small role. After the onset of summer, regional low-level northwesterly winds are weakened, and a local NEA cyclonic low forms. The latter, coupled with monsoon southerly airflow to the south, advects more moisture into NEA and increases regional rainfall. Furthermore, a temperature threshold of 17 °C, the climatological regional mean surface air temperature in pentad 31, was proposed to depict summer onset in NEA. Based on the temperature threshold, the year-to-year variability of summer onset timing in NEA is revealed, ranging from pentad 29 (late May) to 34 (middle June), with the standard deviation of 1.2 pentads. It advanced by 0.6 pentads, on average, after the late 1990s. This study provides a new method to objectively quantify the timing of summer onset in East Asia, which is thermodynamically explainable and may help us to depict and monitor summer onset in different latitudes and topography.

28 November 2025 in Water
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YWYao Wang
Yao Wang
CWChongchang Wang
Chongchang Wang
QYQian Yang
Qian Yang
FLFeng Shang Li
Feng Shang Li
Yingxin ShangYingxin Shang
Yingxin Shang
XZXuetong Zhang
Xuetong Zhang
Snow disasters are severe natural hazards in Jilin Province, China. This research formulated a holistic risk assessment framework which integrates the factors of hazardousness, sensitivity, vulnerability, and disaster prevention and mitigation capacity. Using multi-source data and Geographic Information System (GIS), we evaluated snow disaster risks through 15 selected indicators weighted by the entropy method. Results show high-risk areas primarily concentrated in southeastern mountainous regions, including Jingyu, Fusong, Changbai, and Linjiang. Disaster sensitivity decreases from southeast to northwest, while high-vulnerability zones appear in central urban areas like Changchun. The comprehensive risk generally declines from the southeastern mountains to the northwestern plains. This assessment model effectively reflects snow disaster formation mechanisms and spatial patterns, providing scientific support for disaster prevention and emergency management in Jilin Province.