Quality control of marine big data-a case study of real-time observation station data in Qingdao

Chengcheng QIAN; Aichao LIU; Rui HUANG; Qingrong LIU; Wenkun XU; Shan ZHONG; Le YU

doi:10.1007/s00343-019-8258-y

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Quality control of marine big data-a case study of real-time observation station data in Qingdao

Updated：2023-05-20

- Quality control of marine big data-a case study of real-time observation station data in Qingdao
- Journal of Oceanology and Limnology Vol. 37, Issue 6, Pages: 1983-1993(2019)
- Affiliations：
  
  1.North China Sea Marine Forecasting Center of State Oceanic Administration, Qingdao 266061, China
  2.Qingdao Geotechnical Investigation and Surveying Research Institute, Qingdao 266000, China
  3.Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266000, China
- Author bio：
  
  LIU Aichao, E-mail:liuaichao@ncs.mnr.gov.cn
- Funds：
- DOI：10.1007/s00343-019-8258-y
  CLC：
- Received：21 September 2018，
  
  Accepted：17 December 2018，
  
  Online First：23 January 2019，
  
  Published：2019-11
- Accepted：
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Chengcheng QIAN, Aichao LIU, Rui HUANG, et al. Quality control of marine big data-a case study of real-time observation station data in Qingdao[J]. Journal of Oceanology and Limnology, 2019, 37(6): 1983-1993.
DOI：

Chengcheng QIAN, Aichao LIU, Rui HUANG, et al. Quality control of marine big data-a case study of real-time observation station data in Qingdao[J]. Journal of Oceanology and Limnology, 2019, 37(6): 1983-1993. DOI： 10.1007/s00343-019-8258-y.

摘要

Abstract

Offshore waters provide resources for human beings

while on the other hand

threaten them because of marine disasters. Ocean stations are part of offshore observation networks

and the quality of their data is of great significance for exploiting and protecting the ocean. We used hourly mean wave height

temperature

and pressure real-time observation data taken in the Xiaomaidao station (in Qingdao

China) from June 1

2017

to May 31

2018

to explore the data quality using eight quality control methods

and to discriminate the most effective method for Xiaomaidao station. After using the eight quality control methods

the percentages of the mean wave height

temperature

and pressure data that passed the tests were 89.6%

88.3%

and 98.6%

respectively. With the marine disaster (wave alarm report) data

the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions. The mean wave height is often affected by dynamic marine disasters

so the continuity test method is not effective. The correlation test with other related parameters would be more useful for the mean wave height.

关键词

Keywords

references

Ingleby B, Huddleston M. 2007. Quality control of ocean temperature and salinity profiles—historical and real-time data. J. Marine Syst. , 65 (1-4): 158-175, https://doi.org/10.1016/j.jmarsys.2005.11.019..

Kearns E, Woody C, Bushnell M. 2004. QARTOD-I Report. First Workshop Report on the Quality Assurance of Real-Time Ocean Data. December 3-5, 2003. National Data Buoy Center, NWS/NOAA, Stennis Space Center, MS. 89pp, https://doi.org/10.25607/OBP-380 https://doi.org/10.25607/OBP-380 . Accessed on 2018-04-23.

Li X K, Li F J. 1997. Marine hydro-meteorological real-time data quality control. Mar. Forecasts , 14 (3): 71-79. (in Chinese).

Lorenc A C, Hammon O. 1988. Objective quality control of observations using Bay esian methods: theory, and a practical implementation. Quart. J. Roy. Meteor. Soc. , 114 (480): 515-543, https://doi.org/10.1002/qj.49711448012..

Morello E B, Lynch T P, Slawinski D, Howell B, Hughes D, Timms G P. 2011. Quantitative quality control (QC) procedures for the Australian national reference stations: sensor data. In: Proceedings of Oceans' 11MTS/IEEE KONA. IEEE, Waikoloa, Hawaii, USA.

National Data Buoy Center. 2009. Handbook of Automated Data Quality Control Checks and Procedures. Stennis Space Center, Mississippi, USA.

NOAA, Integrated Ocean Observing System (IOOS) Program Office. 2008. Data Integration Framework (DIF) Customer Implementation Project Summary and Performance Assessment Plan, Version 1.1. NOAA, IOOS, Quebec City, QC, Canada.

North China Sea Branch of the State Oceanic Administration. 1993. The North China Sea Marine Hydrology and Climate. Ocean Publishing House, Beijing, p.63-190. (in Chinese)

Shi M C, Gao G P, Bao X W. 2008. Methods of Marine Survey. China Ocean University Press, Qingdao, China, p.6-123. (in Chinese)

SOA (State Oceanic Administration, China). 2018. China Marine Disasters Bulletin, http://gc.mnr.gov.cn/201806/t20180619_1798021.html http://gc.mnr.gov.cn/201806/t20180619_1798021.html .Accessed on 2018-04-23. (in Chinese)

Thadathil P, Ghosh A K, Pattanaik J, Ratnakaran L. 1998. A quality-control procedure for surface temperature and surface layer inversion in the XBT data archive from the Indian Ocean. J. Atomos. Ocean Technol. , 16 (7): 980-982, https://doi.org/10.1175/1520-0426(1999)016 < 0980AQCPFS > 2.0.CO; 2..

Wan Daud W M N. 2010. Quality control for unmanned meteorological stations in Malaysian meteorological department, https://www.wmo.int/pages/prog/www/IMOP/publications/IOM-109_TECO-2012/Session2/P2_01_WanDaud_QC_Unmanned_Meteorological_Stations.pdf https://www.wmo.int/pages/prog/www/IMOP/publications/IOM-109_TECO-2012/Session2/P2_01_WanDaud_QC_Unmanned_Meteorological_Stations.pdf Accessed on 2018-04-23.

Xu F, Ignatov A. 2014. In situ SST quality monitor ( i Quam). J. Atomos. Ocean. Technol. , 31 (1): 164-180, https://doi.org/10.1175/JTECH-D-13-00121.1..

Xu J, Yu D T, Yuan Z J, Li B, XuZ Z. 2014. Implementation of marine environment monitoring data quality control system. Adv. Mater. Res. , 926-930 : 4254-4257, https://doi.org/10.4028/www.scientific.net/AMR.926-930.4254 https://doi.org/10.4028/www.scientific.net/AMR.926-930.4254 ..

Yang Y, Mao Q S, Wei G H, Dong M M, Dong C. 2017. Quality control methods and application for the oceanic station observed data in the delayed mode. Ocean Dev. Manag. , 34 (10): 109-113. (in Chinese with English abstract).

Yu T, Han G J, Guan C L, Geng Z G. 2010. Several important issues in salinity quality control of Argo float. Mar. Geod. , 33 (4): 424-436, https://doi.org/10.1080/01490419.2010.518496..

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