DRAFT Getting started with GO-BGC Data

Everything you need to begin working with the data

GO-BGC data can be used freely, with no restrictions. However, we ask that GO-BGC is properly acknowledged when used in a publication or a product. 

Float data can be accessed in various formats through multiple data portals


GO-BGC Data Pathway

Float Deployment

Research vessels deploy floats in areas of the ocean where more data is needed.

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Data Transmission

After ascending from 2000m collecting measurements, the float makes contact with an Argo satellite and transmits the most recent sampling profile data.

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Data Assembly

The Argo satellite transmits float data to Data Assembly Centers (DACs).

Real-time Data

At the DACs float data is filtered using Argo standards.

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Delayed-mode Quality Control

Data experts review the float data and compare it to ocean chemistry models. Data is adjusted to account for sensor performance as well.

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Adjusted Data

Validated data is recommended for all users and is made avialble in archive updates every 4 months.

GO-BGC Data Tutorials

MATLAB, Python, and R Github toolboxes are available to help you select, download, and visualize GO-BGC data.  These toolboxes access the synthetic profile (sprof) files directly from the Argo GDAC.  Detailed instructions on how to read sprof files are included in the Github readme files and available through these tutorial videos (also available through our Resources tab):

Intro
MatLab
Python
R

Key functionalities of the toolboxes allow you to:

    • Download a specific float using its WMO ID number
    • Select and download floats that are equipped with desired sensors
    • Select and download profiles made within a specific geographic location and time
    • Create a variety of plots, including trajectory of float(s), raw and QC’d profile data, and contour plots. 

Data Adjustment

BGC float data are automatically adjusted to deliver science quality data in near-real time following established protocols that are specific to each parameter. Documentation on how each parameter is adjusted can be found here. Below, you can find videos that summarize the adjustment process, as well as the quality of the resultant data.

O2 Measurements

For adjusting O2 data skip to

29:16

pH Measurements

For adjusting pH data skip to

24:39

Nitrate Measurements

For adjusting nitrate data skip to

19:52

Delayed Mode Quality Control

This methods article by Tanya Maurer, Josh Plant, and Ken Johnson at MBARI explains more about Delayed Mode Quality Control.

Post-deployment quality control (QC) of float-based oxygen, nitrate, and pH data is a crucial step in the processing and dissemination of such data, as in situ chemical sensors remain in early stages of development. In situ calibration of chemical sensors on profiling floats using atmospheric reanalysis and empirical algorithms can bring accuracy to within 3 μmol O2 kg–1, 0.5 μmol NO3– kg–1, and 0.007 pH units..

Routine QC efforts utilizing these methods can be conducted manually through visual inspection of data to assess sensor drifts and offsets, but more automated processes are preferred to support the growing number of BGC floats and reduce subjectivity among delayed-mode operators. The BGC-Argo data center at MBARI has developed the SAGE and SAGE-O2 software tools to facilitate the QC process.  The paper by Maurer et al. describes these tools, which are available to the public on Github.