Argo salinity: bias and uncertainty evaluation

Wong, Annie P. S.; Gilson, John; Cabanes, Cécile

doi:https://doi.org/10.5194/essd-15-383-2023

Articles | Volume 15, issue 1

https://doi.org/10.5194/essd-15-383-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-15-383-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 1

Data description paper

|

20 Jan 2023

Data description paper |

| 20 Jan 2023

Argo salinity: bias and uncertainty evaluation

Annie P. S. Wong, John Gilson, and Cécile Cabanes

Data sets

Argo float data and metadata from Global Data Assembly Centre (Argo GDAC) Argo https://doi.org/10.17882/42182

Short summary

This article describes the instrument bias in the raw Argo salinity data from 2000 to 2021. The main cause of this bias is sensor drift. Using Argo data without filtering out this instrument bias has been shown to lead to spurious results in various scientific applications. We describe the Argo delayed-mode process that evaluates and adjusts such instrument bias, and we estimate the uncertainty of the Argo delayed-mode salinity dataset. The best ways to use Argo data are illustrated.