An automated method to process, visualize, and publish quality controlled CTD (conductivity, temperature, depth) data using open-source technology

Ship-based Conductivity, Temperature, Depth (CTD) instrumentation and associated bottle sampling are central oceanographic equipment utilized on research vessels globally. The data collected by the CTD instrument provides vital information on Essential Ocean Variables (EOVs), used widely by marine and climate disciplines. Some of the main challenges with profiling CTD data are the complex data processing configurations associated with it, inconsistency of data processing between groups and research cruises where hydrography is not the primary focus, leading to divergence in data processing methods. In order to underpin our understanding of oceanographic processes, it is essential that there is an open and transparent data pipeline for CTD data acquisition, processing, quality control and publication, ensuring data is reported in a consistent and reliable manner. The aim of the work presented here was to develop tools to consistently process and visualize data at sea and postcruise to automate the archiving and publication of quality-controlled data. A data processing routine was developed using Jupyter Notebooks, written in Python, to create a dynamic and interactive graphical user interface (GUI) to process, visualize, quality check and publish CTD acquired data. The routine makes use of the Sea-Bird software processing steps. Use of these tools has vastly reduced data processing time and created a consistent method to process data on survey, as well as reprocess archived data from previous surveys following a standardized, consistent data process flow.