A new automatic quality control system for ocean profile observations and impact on ocean warming estimate

doi:10.1016/j.dsr.2022.103961

CORC > 海洋研究所 > 中国科学院海洋研究所

	A new automatic quality control system for ocean profile observations and impact on ocean warming estimate
	Tan, Zhetao 2,4; Cheng, Lijing 2,3,4; Gouretski, Viktor 4,5; Zhang, Bin 3,6; Wang, Yanjun 3,6; Li, Fuchao 3,6; Liu, Zenghong 1; Zhu, Jiang 4
刊名	DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS
	2023-04-01
卷号	194 页码:19
关键词	Quality control Ocean observations Temperature Ocean heat content Outlier Climate
ISSN号	0967-0637
DOI	10.1016/j.dsr.2022.103961
通讯作者	Cheng, Lijing(chenglij@mail.iap.ac.cn)
英文摘要	The rapidly growing global archive of hydrographic in-situ observations is characterized by a high degree of the data quality heterogeneity. Different data applications (e.g., ocean warming studies) require an internally consistent dataset and therefore the development of an automated quality control (QC) system permitting to reliably identify outliers in profile data obtained by different instrumentation types. In this study, we present a new automatic QC procedure (CAS-Ocean Data Center (CODC) Quality Control system; CODC-QC) for ocean insitu temperature observations, which includes a suite of distinct quality checks (14 in total) to identify temperature outliers. Unlike many existing QC procedures, no assumption is made of a Gaussian distribution law in the new approach as the oceanic variables (e.g., temperature and salinity) are typically skewed. Instead, the time-varying 0.5% and 99.5% quantiles are used as thresholds in CODC-QC to define the local climatological parameter ranges. In addition to temperature ranges, we constructed the local climatological ranges for the vertical temperature gradient which increased the ability of the scheme to identify spurious profiles. The performance of CODC-QC procedure was evaluated using two expert/manual QCed benchmark datasets. This evaluation demonstrated the effectiveness of the proposed scheme in removing spurious data and minimizing the percentage of mistakenly flagged good data. Additionally, the CODC-QC was applied to the global World Ocean Database (WOD) amounting to 16,804,361 temperature profiles from 1940 to 2021. Based on the statistics of temperature outliers, we suggest a significant dependency of the quality of temperature observations on instrumentation type. Finally, as ocean heat content (OHC) is a fundamental indicator of climate change, the impact of different QC systems on OHC estimates is examined. Preliminary results based on an existing mapping approach indicate that the application of the CODC-QC system leads to a 3.33% (15.09%) difference for linear trend of the global 0-2000m OHC changes within 1955-1990 (1991-2021) compared to the WOD-QC, implying a non-negligible source of error in OHC estimates. The new AutoQC system could support further improvement of the oceanic climate records and other applications.
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences[XDB42040402] ; open fund of State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, MNR, China[QNHX2133] ; National Natural Science Foundation of China[42122046] ; National Natural Science Foundation of China[42076202] ; Program of Oceanographic Data Center, Chinese Academy of Sciences[CAS-WX2022SDC-XK11]
WOS关键词	TEMPERATURE ; DEPTH
WOS研究方向	Oceanography
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000995867300001
内容类型	期刊论文
源URL	[http://ir.qdio.ac.cn/handle/337002/183141]
专题	中国科学院海洋研究所
通讯作者	Cheng, Lijing
作者单位	1.Minist Nat Resources, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, Hangzhou, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao, Peoples R China 4.Chinese Acad Sci, Inst Atmospher Phys, Int Ctr Climate & Environm Sci, Beijing, Peoples R China 5.Univ Hamburg, Integrated Climate Data Ctr, Ctr Earth Syst Res & Sustainabil, Hamburg, Germany 6.Chinese Acad Sci, Inst Oceanol, Oceanog Data Ctr, Qingdao, Peoples R China
推荐引用方式 GB/T 7714	Tan, Zhetao,Cheng, Lijing,Gouretski, Viktor,et al. A new automatic quality control system for ocean profile observations and impact on ocean warming estimate[J]. DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS,2023,194:19.
APA	Tan, Zhetao.,Cheng, Lijing.,Gouretski, Viktor.,Zhang, Bin.,Wang, Yanjun.,...&Zhu, Jiang.(2023).A new automatic quality control system for ocean profile observations and impact on ocean warming estimate.DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS,194,19.
MLA	Tan, Zhetao,et al."A new automatic quality control system for ocean profile observations and impact on ocean warming estimate".DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS 194(2023):19.