OOI uses the SAMI2-pH sensor from Sunburst Sensors, LLC to measure seawater pH throughout the different arrays. Assessing the data quality from this instrument is an involved process as there are multiple parameters produced by the instrument that are then used to calculate the seawater pH. These measurements are subject to different sources of error, and those errors can propagate through the calculations to create an erroneous seawater pH value. Based upon the vendor documentation and MATLAB code Sunburst provides to convert the raw measurements, OOI data team members have created a set of rules from those different measurements to flag the pH data as either pass, suspect or fail.
The resulting flags can be used to remove failed data from further analysis. They can also be used to help generate annotations for further Human in the Loop (HITL) QC checks of the data to help refine quality metrics for the data. OOI team member, Chris Wingard (OSU), has written up the QC process as a Python Jupyter notebook. This notebook and other example notebooks are freely available to the scientific community via the OOI GitHub site (within the OOI Data Team Python toolbox accessed from https://oceanobservatories.org/community-tools/ ).
In this notebook, Wingard shows how the quality rules can be used to remove bad pH data from a time series, and how they can be used to then create annotations. The impact of using these flags is shown with a set of before and after plots of the seawater pH as a function of temperature. The quality controlled data can then be used to estimate the seasonal cycle of pH to set climatological quality control flags.
Here an example is shown using data from a pH sensor on the Oregon Inshore Surface Mooring (CE01ISSM) near surface instrument frame (NSIF), deployed at 7 m depth (site depth is 25 m).
Evans, W., B. Hales, and P. G. Strutton (2011), Seasonal cycle of surface ocean pCO2on the Oregon shelf,J. Geophys. Res., 116, C05012, doi:10.1029/2010JC006625.