Cite this paper:
QIAN Chengcheng, LIU Aichao, HUANG Rui, LIU Qingrong, XU Wenkun, ZHONG Shan, YU Le. Quality control of marine big data-a case study of real-time observation station data in Qingdao[J]. HaiyangYuHuZhao, 2019, 37(6): 1983-1993

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

QIAN Chengcheng1,3, LIU Aichao1, HUANG Rui1, LIU Qingrong1, XU Wenkun2, ZHONG Shan1, YU Le1
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
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.
Key words:    quality control|real-time station data|marine big data|Xiaomaidao Station|marine disaster   
Received: 2018-09-21   Revised: 2019-01-23
Tools
PDF (1019 KB) Free
Print this page
Add to favorites
Email this article to others
Authors
Articles by QIAN Chengcheng
Articles by LIU Aichao
Articles by HUANG Rui
Articles by LIU Qingrong
Articles by XU Wenkun
Articles by ZHONG Shan
Articles by YU Le
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 RealTime Ocean Data. December 3-5, 2003. National Data Buoy Center, NWS/NOAA, Stennis Space Center, MS. 89pp, 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 Bayesian 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.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<0980:AQC PFS>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. Accessed on 2018-04-23.
Xu F, Ignatov A. 2014. In situ SST quality monitor (iQuam). 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., 926-930:4 254-4 257, https://doi.org/10.4028/www.scientific.net/AMR.926-930.4254.
Yang Y, Miao 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/10.1080/01490419.2010.5 18496.