韩国海洋研究站观测温度时间序列的质量控制:海洋观测倡议方法的初步应用及其局限性

Q4 Engineering
Yongchim Min, Jin-Yong Jeong, C. Jang, Jaeik Lee, Jong-min Jeong, In-ki Min, J. Shim, Y. Kim
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引用次数: 1

摘要

来自黄海和东海韩国海洋研究站(KORS)的观测时间序列具有各种噪声源,包括水下传感器上的生物污垢、电源间歇性耗尽、电缆泄漏以及传感器信号之间的干扰。除了这些技术问题之外,与背景潮流相关的复杂波浪往往会导致海洋时间序列的大幅振荡。此类技术和环境问题需要区域优化的自动质量控制(QC)程序。在实现这一最终目标之前,我们检查了海洋观测倡议(OOI)标准QC的方法,以调查该程序是否与KORS相关。OOI QC由三个分类测试组成,包括数据的全局/局部范围、包括尖峰和梯度在内的时间变化,以及与其卡住和漂移相关的传感器相关问题。这些OOI QC算法已应用于KORS之一Ieodo站的水温时间序列。通过全局/局部范围检查和尖峰检查成功标记明显的异常值。由于频繁的传感器清洁和维护,卡滞和漂移检查几乎没有检测到与传感器相关的错误。然而,梯度检查未能标记出倾向于紧密结合在一起的剩余异常值,而且往往倾向于将可能良好的数据标记为错误的数据,尤其是以温跃层附近相当大的波动为特征的数据。这些结果表明,梯度检查可能与涉及相当大的自然波动以及技术问题的观测结果无关。我们的研究强调了一种新算法的必要性,例如使用多个移动窗口代替梯度检查的基于标准差的异常值检查,以及使用相关变量进行内部一致性检查的额外算法,以建立KORS的标准QC程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quality Control of Observed Temperature Time Series from the Korea Ocean Research Stations: Preliminary Application of Ocean Observation Initiative’s Approach and Its Limitation
The observed time series from the Korea Ocean Research Stations (KORS) in the Yellow and East China Seas (YECS) have various sources of noise, including bio-fouling on the underwater sensors, intermittent depletion of power, cable leakage, and interference between the sensors’ signals. Besides these technical issues, intricate waves associated with background tidal currents tend to result in substantial oscillations in oceanic time series. Such technical and environmental issues require a regionally optimized automatic quality control (QC) procedure. Before the achievement of this ultimate goal, we examined the approach of the Ocean Observatories Initiative (OOI)’s standard QC to investigate whether this procedure is pertinent to the KORS. The OOI QC consists of three categorized tests of global/local range of data, temporal variation including spike and gradient, and sensor-related issues associated with its stuck and drift. These OOI QC algorithms have been applied to the water temperature time series from the Ieodo station, one of the KORS. Obvious outliers are flagged successfully by the global/local range checks and the spike check. Both stuck and drift checks barely detected sensor-related errors, owing to frequent sensor cleaning and maintenance. The gradient check, however, fails to flag the remained outliers that tend to stick together closely, as well as often tend to mark probably good data as wrong data , especially data characterized by considerable fluctuations near the thermocline. These results suggest that the gradient check might not be relevant to observations involving considerable natural fluctuations as well as technical issues. Our study highlights the necessity of a new algorithm such as a standard deviation-based outlier check using multiple moving windows to replace the gradient check and an additional algorithm of an inter-consistency check with a related variable to build a standard QC procedure for the KORS.
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来源期刊
Ocean and Polar Research
Ocean and Polar Research Engineering-Ocean Engineering
CiteScore
0.80
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0.00%
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