scholarly journals An estimate of the cross-frontal transport at the shelf break of the East China Sea with the Finite Volume Coastal Ocean Model

2006 ◽  
Vol 111 (C3) ◽  
Author(s):  
Atsuhiko Isobe ◽  
Robert C. Beardsley
Keyword(s):  
East China Sea ◽  
Finite Volume ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Shelf Break ◽  
East China ◽  
The East China Sea ◽  
China Sea ◽  
The Cross ◽  
Coastal Ocean Model

scholarly journals Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea

2021 ◽  
Vol 9 (3) ◽  
pp. 279
Author(s):  
Zhehao Yang ◽  
Weizeng Shao ◽  
Yuyi Hu ◽  
Qiyan Ji ◽  
Huan Li ◽  
...  
Keyword(s):  
East China Sea ◽  
Oil Spill ◽  
Oil Spills ◽  
Ocean Model ◽  
Sea Surface ◽  
East China ◽  
The East China Sea ◽  
Sar Images ◽  
China Sea ◽  
Spatial Coverage

Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China Sea was hindcast simulated using the oil particle-tracing method. Sea-surface winds from the European Centre for Medium-Range Weather Forecasts (ECMWF), currents simulated from the Finite-Volume Community Ocean Model (FVCOM), and waves simulated from the Simulating WAves Nearshore (SWAN) were employed as background marine dynamics fields. In particular, the oil spill simulation was compared with the detection from Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) images. The validation of the SWAN-simulated significant wave height (SWH) against measurements from the Jason-2 altimeter showed a 0.58 m root mean square error (RMSE) with a 0.93 correlation (COR). Further, the sea-surface current was compared with that from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2), yielding a 0.08 m/s RMSE and a 0.71 COR. Under these circumstances, we think the model-simulated sea-surface currents and waves are reliable for this work. A hindcast simulation of the tracks of oil slicks spilled from the Sanchi shipwreck was conducted during the period of 14–17 January 2018. It was found that the general track of the simulated oil slicks was consistent with the observations from the collected GF-3 SAR images. However, the details from the GF-3 SAR images were more obvious. The spatial coverage of oil slicks between the SAR-detected and simulated results was about 1 km2. In summary, we conclude that combining numerical simulation and SAR remote sensing is a promising technique for real-time oil spill monitoring and the prediction of oil spreading.

Sedimentary responses to the cross-shelf transport of terrigenous material on the East China Sea continental shelf

2019 ◽  
Vol 384 ◽  
pp. 50-59 ◽  
Author(s):  
Kaidi Zhang ◽  
Anchun Li ◽  
Peng Huang ◽  
Jian Lu ◽  
Xiting Liu ◽  
...  
Keyword(s):  
Continental Shelf ◽  
East China Sea ◽  
East China ◽  
Terrigenous Material ◽  
The East China Sea ◽  
China Sea ◽  
The Cross

scholarly journals Retrieving monthly and interannual total-scale pH (pH<sub>T</sub>) on the East China Sea shelf using an artificial neural network: ANN-pH<sub>T</sub>-v1

2020 ◽  
Vol 13 (10) ◽  
pp. 5103-5117
Author(s):  
Xiaoshuang Li ◽  
Richard Garth James Bellerby ◽  
Jianzhong Ge ◽  
Philip Wallhead ◽  
Jing Liu ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
East China Sea ◽  
Ocean Model ◽  
East China ◽  
Ann Model ◽  
The East China Sea ◽  
China Sea ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Abstract. While our understanding of pH dynamics has strongly progressed for open-ocean regions, for marginal seas such as the East China Sea (ECS) shelf progress has been constrained by limited observations and complex interactions between biological, physical and chemical processes. Seawater pH is a very valuable oceanographic variable but not always measured using high-quality instrumentation and according to standard practices. In order to predict total-scale pH (pHT) and enhance our understanding of the seasonal variability of pHT on the ECS shelf, an artificial neural network (ANN) model was developed using 11 cruise datasets from 2013 to 2017 with coincident observations of pHT, temperature (T), salinity (S), dissolved oxygen (DO), nitrate (N), phosphate (P) and silicate (Si) together with sampling position and time. The reliability of the ANN model was evaluated using independent observations from three cruises in 2018, and it showed a root mean square error accuracy of 0.04. The ANN model responded to T and DO errors in a positive way and S errors in a negative way, and the ANN model was most sensitive to S errors, followed by DO and T errors. Monthly water column pHT for the period 2000–2016 was retrieved using T, S, DO, N, P and Si from the Changjiang biology Finite-Volume Coastal Ocean Model (FVCOM). The agreement is good here in winter, while the reduced performance in summer can be attributed in large part to limitations of the Changjiang biology FVCOM in simulating summertime input variables.

Vertical mixing in the bottom mixed layer near the continental shelf break in the East China Sea

1994 ◽  
Vol 50 (4) ◽  
pp. 437-448 ◽  
Author(s):  
Takeshi Matsuno ◽  
Seiichi Kanari ◽  
Chikashi Kobayashi ◽  
Toshiyuki Hibiya
Keyword(s):  
Continental Shelf ◽  
East China Sea ◽  
Mixed Layer ◽  
Vertical Mixing ◽  
Shelf Break ◽  
East China ◽  
The East China Sea ◽  
China Sea ◽  
Continental Shelf Break

scholarly journals Influence of Tropical Cyclone Intensity and Size on Storm Surge in the Northern East China Sea

2019 ◽  
Vol 11 (24) ◽  
pp. 3033 ◽  
Author(s):  
Jian Li ◽  
Yijun Hou ◽  
Dongxue Mo ◽  
Qingrong Liu ◽  
Yuanzhi Zhang
Keyword(s):  
Tropical Cyclone ◽  
Storm Surge ◽  
East China Sea ◽  
Ocean Model ◽  
Economic Effects ◽  
East China ◽  
Cyclone Intensity ◽  
China Sea ◽  
Coastal Ocean Model ◽  
The Impact

Typhoon storm surge research has always been very important and worthy of attention. Less is studied about the impact of tropical cyclone size (TC size) on storm surge, especially in semi-enclosed areas such as the northern East China Sea (NECS). Observational data for Typhoon Winnie (TY9711) and Typhoon Damrey (TY1210) from satellite and tide stations, as well as simulation results from a finite-volume coastal ocean model (FVCOM), were developed to study the effect of TC size on storm surge. Using the maximum wind speed (MXW) to represent the intensity of the tropical cyclone and seven-level wind circle range (R7) to represent the size of the tropical cyclone, an ideal simulation test was conducted. The results indicate that the highest storm surge occurs when the MXW is 40–45 m/s, that storm surge does not undergo significant change with the RWM except for the area near the center of typhoon and that the peak surge values are approximately a linear function of R7. Therefore, the TC size should be considered when estimating storm surge, particularly when predicting marine-economic effects and assessing the risk.

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