An open source Python interface to the quality control of ocean in-situ observations.

CODC-QC is an open source Python interface to the quality control of ocean in-situ observations (e.g, temperature profiles, salinity profiles etc.). It was developed to reduce human-workload and time-consuming on manual quality control as well as adapt the increasing volume of daily real-time data flow on observing system and large data centers.

The in-situ observations collected from the ocean are quality-heterogeneous. Decades of efforts have been dedicated to developing different manual or automatic quality control (QC) system to improve the quality and availability of ocean database, which is one of the basic tasks in many oceanic studies.

The goals of developing the auutomatic QC (AutoQC) is to provide a quality-hemogeonous database, with reduciing human-workload and time-consuming on manual QC as well as adapting the increasing volume of daily real-time data flow on observing system and large data centers.

Here, we delveoped an AutoQC system (we refer to this procedure as CODC-QC system (CAS-Ocean Data Center (CODC) Quality Control system) to quality control the ocean in-situ observations.

• We strongly recommend to use version 3.7 of Python to run CODCQC
• If you have already installed Python3.7, then you can use pip from PyPI to install CODCQC

python3 -m pip install CODCQC

please make sure PIP fits your version of Python3.X. In some machines, you should use pip3 install CODC_QC because "pip" may be linked to python2.X

Why CODC-QC

• CODC-QC contains several QC checks that can be easily combined and tuned by users.
• CODC-QC provides many typical data interface for inputting raw data.
• The QC flags in CODC-QC are optional multiple categories, which depends on user's purposes.
• CODC-QC is a climatology-based automatic quality control algorithm. It is good at detecting bad data with paying an acceptable low price of sacrificing good data.
• The performance of CODC-QC has been meticulously analyzed and evaluated by comparing it with other international QC systems in peer review now.

In this version, CODC-QC is only avaliable for temperature observations. It convers all temperature data instrument types (e.g., Bottle, XBT, CTD, Argo, APB etc.). In the future, CODC-QC will extent to salinity observations and oxygen observations.

We are warmly welcome feedback/questions/fork/pull requests/improved the CODC-QC project!!

If you have any questions/suggestions about this program, or if you find some bugs in this program, or even if you are willing to debug/improved the CODC-QC project, please feel free and do not hesitate to tell us via:

• Create an issue in the Github community
• Pull requests your debugged/improved codes in the Github community
• Send an email to us: [email protected]  or [email protected]

For more information of CODCQC, please visit our IAP/CAS ocean group webiste: http://www.ocean.iap.ac.cn or https://doi.org/10.1016/j.dsr.2022.103961

Tan Z., Cheng L., Gouretski V., Zhang B., Wang Y., Li F., Liu Z., Zhu J., 2022: A new automatic quality control system for ocean in-situ temperature observations and impact on ocean warming estimate. Deep Sea Research Part I, 103961, https://doi.org/10.1016/j.dsr.2022.103961

Author: Zhetao Tan ([email protected]) Contributor: Lijing Cheng, Viktor Gourestki, Yanjun Wang, Bin Zhang Center for Ocean Mega-Science, Chinese Academy of Sciences (COMS/CAS) Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS)