Quality Controlled Argo Profiling Float Oxygen Data: Open Source Sharing and Version Control Using IPython Notebooks on GitHub

Abstract:

Profiling floats equipped with biogeochemical sensors are an ideal platform for observing the seasonal evolution of physical and chemical processes from the surface to the deep interior. As of August 2015, there have reportedly been 765 floats equipped with oxygen sensors with 363 currently active. Although new insights into oceanic biogeochemical processes have come from these data, the profiling oxygen data set has not been fully utilized because the dissolved oxygen data does not undergo QC procedures at the Argo data centers. The oxygen sensors on profiling floats have been demonstrated to produce highly stable and precise data over many months and years but only a small percentage have been verified with discrete samples taken at deployment to determine the sensor accuracy. Takeshita et al (2013) presented a climatology based quality control procedure utilizing the World Ocean Atlas 2009 (WOA09). We used a straightforward approach mentioned in their paper to calculate the sensor gain by comparing the surface %Sat(float) to the surface %Sat(WOA09) using > 1 year of data. We have developed Python scripts to provide QC’d data that are freely available and easily shared using IPython Notebooks hosted on GitHub. We will examine the consistency of the corrected oxygen data set, relative to existing climatologies, and its use in oceanographic studies.