해양과학기지 시계열 관측 자료 품질관리 시스템 구축: 국제 관측자료 품질관리 방안 수온 관측 자료 시범적용과 문제점

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...

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Veröffentlicht in:Ocean and polar research 2020, 42(3), , pp.195-210
Hauptverfasser: 민용침, 정진용, 장찬주, 이재익, 정종민, 민인기, 심재설, 김용선, Min, Yongchim, Jeong, Jin-Yong, Jang, Chan Joo, Lee, Jaeik, Jeong, Jongmin, Min, In-Ki, Shim, Jae-Seol, Kim, Yong Sun
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Sprache:kor
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Zusammenfassung: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.
ISSN:1598-141X
2234-7313
DOI:10.4217/OPR.2020.42.3.195