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28 August 2019 Accuracy Improvement of Particle Tracking Model Using 2-D Current Measurement (HF-Radar) Data
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Abstract

Choi, J.W.; Song, K.M., and Choi, J.Y., 2019. Accuracy improvement of particle tracking model using 2-D current measurement (HF-Radar) data. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 251-255. Coconut Creek (Florida), ISSN 0749-0208.

The accuracy of the particle tracking model (PTM), which is widely used for predicting spilled oil diffusion and supporting search and rescue in the ocean, is significantly affected by current and wind, which necessitates the development of suitable accuracy improvement techniques to increase human safety and preserve the environment. To address this issue, we herein established a method of improving PTM accuracy by comparing high-frequency radar (HFR) current data with those of the coastal model. Particle tracking was simulated using a ∼300-m-resolution current field of the Korea Operational Oceanographic System (KOOS) coastal circulation forecasting system, a ∼3-km-resolution current field of the HFR system installed on Jeju Island, and a 4-km-resolution KOOS weather forecasting system (wind data). To compare the effects of two currents on PTM accuracy, drifters were dropped from the center of the HFR-system grid, and performance was evaluated by comparing the actual drifter moving path with that predicted by PTM. PTM accuracy was calculated by comparing the acceptable duration and accuracy (drifting object located within 1 km) with 10-day moving path data, and the application of two-dimensional current measurement data and wind data was shown to significantly increase prediction accuracy.

©Coastal Education and Research Foundation, Inc. 2019
Jung-Woon Choi, Kyu-Min Song, and Jin-Yong Choi "Accuracy Improvement of Particle Tracking Model Using 2-D Current Measurement (HF-Radar) Data," Journal of Coastal Research 91(sp1), 251-255, (28 August 2019). https://doi.org/10.2112/SI91-051.1
Received: 9 October 2018; Accepted: 14 December 2018; Published: 28 August 2019
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