Calibration of backward-in-time model using drifting buoys in the East China Sea

• Autorzy: Yu F. , Li J. , Zhao Y. , Li Q. , Chen G.

Identyfikatory

DOI

10.1016/j.oceano.2017.01.003

• Języki publikacji: EN

Abstrakty

EN

In the process of oil exploitation and transportation, large amounts of crude oil are often spilled, resulting in serious pollution of the marine environment. Forecasting oil spill reverse trajectories to determine the exact oil spill sources is crucial for taking proactive and effective emergency measures. In this study, the backward-in-time model (BTM) is proposed for identifying sources of oil spills in the East China Sea. The wind, current and random walk are three major factors in the simulation of oil spill sources. The wind drag coefficient varies along with the uncertainty of the wind field, and the random walk is sensitive to various traits of different regions, these factors are taken as constants in most of the state-of-the-art studies. In this paper, a self-adaptive modification mechanism for drift factors is proposed, which depends on a data set derived from the drifter buoys deployed over the East China Sea shelf. It can be well adapted to the regional characteristics of different sea areas. The correlation factor between predicted positions and actual locations of the drifters is used to estimate optimal coefficients of the BTM. A comparison between the BTM and the traditional method is also made in this study. The results presented in this paper indicate that our method can be used to predict the actual specific spillage locations.

Słowa kluczowe

EN

wind drag coefficient; random walk; drifter buoys; oil spill reverse; oil spill model

• Wydawca: Polish Academy of Sciences, Institute of Oceanology ; Elsevier
• Czasopismo: Oceanologia
• Rocznik: 2017
• Tom: No. 59 (3)
• Strony: 238--247
• Opis fizyczny: Bibliogr. 34 poz., mapy, tab., wykr.

Twórcy

autor

Yu F.

• College of Information Science and Engineering, Ocean University of China, Qingdao, PR China
• Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, PR China

autor

Li J.

• College of Information Science and Engineering, Ocean University of China, Qingdao, PR China

autor

Zhao Y.

• College of Liberal Arts, Journalism and Communication, Ocean University of China, Qingdao, PR China
• Research Institute of Marine Development of China, Shandong Qingdao, PR China

autor

Li Q.

• College of Information Science and Engineering, Ocean University of China, Qingdao, PR China

autor

Chen G.

• College of Information Science and Engineering, Ocean University of China, Qingdao, PR China
• Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, PR China

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).