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

민용침; 정진용; 장찬주; 이재익; 정종민; 민인기; 심재설; 김용선

doi:10.4217/opr.2020.42.3.195

해양과학기지 시계열 관측 자료 품질관리 시스템 구축: 국제 관측자료 품질관리 방안 수온 관측 자료 시범적용과 문제점
Quality Control of Observed Temperature Time Series from the Korea Ocean Research Stations: Preliminary Application of Ocean Observation Initiative's Approach and Its Limitation 원문보기

Ocean and polar research, v.42 no.3, 2020년, pp.195 - 210

Abstract ▼ AI-Helper

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.

주제어

표/그림 (14)

그림 Fig. 1. Schematic illustration of the Ieodo Ocean Research Station (I-ORS), with the geographic locations of the Korea Ocean Research Station (KORS) in the Yellow and East China Seas
표 Table 1. The comparison of the quality controls from QARTOD, NDBC, and OOI
그림 Fig. 2. Observed (a) temperature and (b) salinity timeseries at the levels of 5 m, 20 m, and 38 m from Ieodo Ocean Research Station (I-ORS) during 2013. The temperature-salinity diagram is illustrated in (c)
표 Table 2. Summary of maintenance for the I-ORS CT sensor during 2013
그림 Fig. 3. The applied results of global range check to the observed water temperature from the I-ORS at the levels of (a) 5 m, (b) 20 m, and (c) 38 m during 2013. The flagged data by this check are marked with black crosses
그림 Fig. 4. Histogram of observed temperature in percentage from the I-ORS during 2004-2019. The red line shows a log-normal distribution of the observed temperatures
그림 Fig. 5. Same as Fig. 3 but except local range check. The gray colors represent passed data by previous QC, i.e., global range check. The black crosses indicate the flagged data by this check, and colors are passed ones
그림 Fig. 6. Same as Fig. 5 but except spike check. Insets show expanded view of a specific period
그림 Fig. 7. Same as Fig. 5 but except stuck check
그림 Fig. 8. Same as Fig. 5 but except gradient check
그림 Fig. 9. The qualified temperature by applying the OOI's standard QCs to the 2013 I-ORS water temperature timeseries
표 Table 3. The summarized result of the application of the OOI quality control to the temperature timeseries observed from the I-ORS in 2013. The number within the blankets is percentage (%) divided by expected total data number with a 10-min interval (i.e. 52,560)
그림 Fig. 10. The application of the OOI QCs to water temperatures observed from the I-ORS for the period of 2007 and 2019. The upper panel shows the raw time series and the lower one is the qualified time series after applying the OOI's QCs. The gray colors in (b) represent the flagged data
그림 Fig. 11. Examples of water temperature and density inversions at the I-ORS occupied at (a) 23 August 2016, (b) 26 April 2017, and (c) 21 November 2018. Blue represents a layer with temperature inversion only, and yellow with both temperature and density inversion

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