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CODC-v1: a quality-controlled and bias-corrected ocean temperature profile database from 1940-2023
Bin Zhang1,2,3, Lijing Cheng4,5,6,7, Zhetao Tan2,8,9
1Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.
Scientific Data
|June 22, 2024
Summary
A new global ocean temperature profile database, CODC-v1, offers over 17 million quality-controlled subsurface profiles from 1940-2023. This bias-corrected dataset enhances ocean and climate research with improved data accuracy and comprehensive coverage.
Area of Science:
- Oceanography
- Climate Science
- Data Science
Background:
- High-quality ocean in situ profile observations are crucial for ocean and climate research.
- Existing databases may lack comprehensive global coverage or advanced quality control.
Purpose of the Study:
- To introduce the Chinese Academy of Science (CAS) Oceanography Data Center version 1 (CODC-v1) database.
- To provide a global, quality-controlled, and bias-corrected dataset of ocean subsurface temperature profiles.
Main Methods:
- Compilation of over 17 million temperature profiles (1940-2023) from diverse sources, including the World Ocean Database and Chinese institutes.
- Implementation of a novel quality control system considering local temperature distributions, topographic barriers, and climate change impacts.
- Correction of biases in Mechanical Bathythermographs (MBTs), eXpendable Bathythermographs (XBTs), and Bottle data (OSD) using recent correction schemes.
Main Results:
- The CODC-v1 database contains over 17 million temperature profiles, representing a significant expansion of global oceanographic data.
- The implemented quality control and bias correction methods ensure a high-quality, reliable dataset.
- The database integrates data not previously available in other global repositories.
Conclusions:
- CODC-v1 provides a valuable, bias-corrected resource for ocean and climate research and operational oceanography.
- The database's comprehensive nature and rigorous quality control make it suitable for a wide range of scientific applications.
- This dataset will advance our understanding of ocean dynamics and climate variability.
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