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Bingchen Liang

Researcher at Ocean University of China

Publications -  97
Citations -  878

Bingchen Liang is an academic researcher from Ocean University of China. The author has contributed to research in topics: Geology & Significant wave height. The author has an hindex of 14, co-authored 69 publications receiving 602 citations.

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Blended wind fields for wave modeling of tropical cyclones in the South China Sea and East China Sea

TL;DR: Wang et al. as mentioned in this paper proposed a blended TC wind model combining two datasets, which shows good capacity of the TC wind simulation, and applied the blended wind model is applied in TC wave simulations in the South China Sea and East China Sea (ECS) of 4 years (2011-2014).
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Modeling wave effects on storm surge and coastal inundation

TL;DR: In this article, a parametric study of surface wave effects on storm surge and coastal inundation is presented, showing that the presence of waves can increase the maximum storm surge heights significantly through wave setup, and the contribution of waves varies considerably depending on the storm characteristics.
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Numerical modelling of the nearshore wave energy resources of Shandong peninsula, China

TL;DR: In this article, the third generation wave model SWAN was used to simulate wave parameters of the Shandong peninsula in China for 16 years (1996-2011) and the wind parameters were obtained by the Weather Research & Forecasting Model (WRF).
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22-Year wave energy hindcast for the China East Adjacent Seas

TL;DR: In this article, the third generation wave model SWAN was used to simulate wave parameters of the China East Adjacent Seas (CEAS) including Bohai, Yellow and East China Sea for the 22 years period ranging from 1990.12.1 to 2011.
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An automated threshold selection method based on the characteristic of extrapolated significant wave heights

TL;DR: In this paper, a threshold selection method based on the characteristic of extrapolated significant wave heights (ATSME) is proposed to determine the suitable threshold within the stable threshold range, which exhibits a high probability of containing a suitable threshold.