Development and Validation of an Operational Search and Rescue Modeling System for the Yellow Sea and the East and South China Seas
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Title
- Development and Validation of an Operational Search and Rescue Modeling System for the Yellow Sea and the East and South China Seas
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Author(s)
- Cho, Kyoung-Ho; Li, Yan; Wang, Hui; Park, Kwang-Soon; Choi, Jin-Yong; Shin, Kwang-Il; Kwon, Jae-Il
- KIOST Author(s)
- Choi, Jin Yong(최진용); Kwon, Jae Il(권재일)
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Alternative Author(s)
- 조경호; 박광순; 최진용; 권재일
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Publication Year
- 2014-01
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Abstract
- An operational search and rescue (SAR) modeling system was developed to forecast the tracks of victims or debris from marine accidents in the marginal seas of the northwestern Pacific Ocean. The system is directly linked to a real-time operational forecasting system that provides wind and surface current forecasts for the Yellow Sea and the East and South China Seas and is thus capable of immediately predicting the tracks and area to be searched for up to 72 h in the future. A stochastic trajectory model using a Monte Carlo ensemble technique is employed within the system to estimate the trajectories of drifting objects. It is able to consider leeway drift and to deal with uncertainties in the forcing fields obtained from the operational forecasting system. A circle assessment method was applied to evaluate the performance of the SAR model using comparisons in buoy and ship trajectories obtained from field drifter experiments. The method effectively analyzed the effects of the forcing fields and diagnosed the model's performance. Results showed that accurate wind and current forcing fields play a significant role in improving the behavior of the SAR model. Operationally, the SAR modeling system is used to support the Korea Coast Guard during marine emergencies. Additionally, some sensitivity tests for model parameters and wave effect on the SAR model prediction are discussed.
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ISSN
- 0739-0572
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/2918
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DOI
- 10.1175/JTECH-D-13-00097.1
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Bibliographic Citation
- JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, v.31, no.1, pp.197 - 215, 2014
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Publisher
- AMER METEOROLOGICAL SOC
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Subject
- HYPER-ENSEMBLE STATISTICS; SURFACE DRIFT PREDICTION; CURRENTS; OCEAN; OBJECTS
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Keywords
- Operational forecasting; Model evaluation; performance; Emergency response; Field experiments
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Type
- Article
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Language
- English
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Document Type
- Article
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