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.
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.
the Creative Commons Attribution 4.0 License.
Argo salinity: bias and uncertainty evaluation
School of Oceanography, University of Washington, Seattle, WA, USA
John Gilson
Scripps Institution of Oceanography, La Jolla, CA, USA
Cécile Cabanes
Laboratoire d'Océanographie Physique et Spatiale (LOPS), University of Brest, CNRS, Ifremer, IRD, IUEM, Brest, France
UAR 3113, University of Brest, CNRS, IRD, IUEM, Brest, France
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Cited
15 citations as recorded by crossref.
- Global Mean Sea Level Rise Inferred From Ocean Salinity and Temperature Changes A. Bagnell & T. DeVries 10.1029/2022GL101004
- Barystatic sea level change observed by satellite gravimetry: 1993–2022 Y. Nie et al. 10.1073/pnas.2425248122
- Regional sea level trend budget over 2004–2022 M. Bouih et al. 10.5194/os-21-1425-2025
- Capability of the Mediterranean Argo network to monitor sub-regional climate change indicators C. Chevillard et al. 10.3389/fmars.2024.1416486
- Assessment of the Representativeness and Uncertainties of CTD Temperature Profiles M. Le Menn et al. 10.3390/jmse13020213
- Global and regional ocean mass budget closure since 2003 C. Ludwigsen et al. 10.1038/s41467-024-45726-w
- Best practices for Core Argo floats - part 1: getting started and data considerations T. Morris et al. 10.3389/fmars.2024.1358042
- Cause of Substantial Global Mean Sea Level Rise Over 2014–2016 W. Llovel et al. 10.1029/2023GL104709
- Dense Water Formation in the North–Central Aegean Sea during Winter 2021–2022 M. Potiris et al. 10.3390/jmse12020221
- Evaluation of the effects of Argo data quality control on global ocean data assimilation systems I. Ishikawa et al. 10.3389/fmars.2024.1496409
- Technical note: Determining Arctic Ocean halocline and cold halostad depths based on vertical stability E. Metzner & M. Salzmann 10.5194/os-19-1453-2023
- Reconstructing monthly 20$$^\textrm{th}$$ century salinity fields using a data-driven method and Argo data E. Oulhen et al. 10.1007/s10236-025-01690-7
- DSE-NN: Discretized Spatial Encoding Neural Network for Ocean Temperature and Salinity Interpolation in the North Atlantic S. Liu et al. 10.3390/jmse12061013
- Jason y los argonautas: temporalidad, usabilidad y conocimiento tácito en el monitoreo oceánico de Argo L. Camprubí 10.3989/asclepio.2024.25
- Editorial: Demonstrating observation impacts for the ocean and coupled prediction P. Oke et al. 10.3389/fmars.2025.1588067
13 citations as recorded by crossref.
- Global Mean Sea Level Rise Inferred From Ocean Salinity and Temperature Changes A. Bagnell & T. DeVries 10.1029/2022GL101004
- Barystatic sea level change observed by satellite gravimetry: 1993–2022 Y. Nie et al. 10.1073/pnas.2425248122
- Regional sea level trend budget over 2004–2022 M. Bouih et al. 10.5194/os-21-1425-2025
- Capability of the Mediterranean Argo network to monitor sub-regional climate change indicators C. Chevillard et al. 10.3389/fmars.2024.1416486
- Assessment of the Representativeness and Uncertainties of CTD Temperature Profiles M. Le Menn et al. 10.3390/jmse13020213
- Global and regional ocean mass budget closure since 2003 C. Ludwigsen et al. 10.1038/s41467-024-45726-w
- Best practices for Core Argo floats - part 1: getting started and data considerations T. Morris et al. 10.3389/fmars.2024.1358042
- Cause of Substantial Global Mean Sea Level Rise Over 2014–2016 W. Llovel et al. 10.1029/2023GL104709
- Dense Water Formation in the North–Central Aegean Sea during Winter 2021–2022 M. Potiris et al. 10.3390/jmse12020221
- Evaluation of the effects of Argo data quality control on global ocean data assimilation systems I. Ishikawa et al. 10.3389/fmars.2024.1496409
- Technical note: Determining Arctic Ocean halocline and cold halostad depths based on vertical stability E. Metzner & M. Salzmann 10.5194/os-19-1453-2023
- Reconstructing monthly 20$$^\textrm{th}$$ century salinity fields using a data-driven method and Argo data E. Oulhen et al. 10.1007/s10236-025-01690-7
- DSE-NN: Discretized Spatial Encoding Neural Network for Ocean Temperature and Salinity Interpolation in the North Atlantic S. Liu et al. 10.3390/jmse12061013
2 citations as recorded by crossref.
Latest update: 08 Aug 2025
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.
This article describes the instrument bias in the raw Argo salinity data from 2000 to 2021. The...
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