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http://dx.doi.org/10.9765/KSCOE.2021.33.6.333

Long-gap Filling Method for the Coastal Monitoring Data  

Cho, Hong-Yeon (Marine Big-data Center, Korea Institute of Ocean Science and Technology, University of Science and Technology(UST))
Lee, Gi-Seop (Marine Big-data Center, Korea Institute of Ocean Science and Technology)
Lee, Uk-Jae (Marine Big-data Center, Korea Institute of Ocean Science and Technology)
Publication Information
Journal of Korean Society of Coastal and Ocean Engineers / v.33, no.6, 2021 , pp. 333-344 More about this Journal
Abstract
Technique for the long-gap filling that occur frequently in ocean monitoring data is developed. The method estimates the unknown values of the long-gap by the summation of the estimated trend and selected residual components of the given missing intervals. The method was used to impute the data of the long-term missing interval of about 1 month, such as temperature and water temperature of the Ulleungdo ocean buoy data. The imputed data showed differences depending on the monitoring parameters, but it was found that the variation pattern was appropriately reproduced. Although this method causes bias and variance errors due to trend and residual components estimation, it was found that the bias error of statistical measure estimation due to long-term missing is greatly reduced. The mean, and the 90% confidence intervals of the gap-filling model's RMS errors are 0.93 and 0.35~1.95, respectively.
Keywords
coastal monitoring data; gap-filling; trend; residuals; Ulleungdo buoy;
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