Combining BioGeoChemical-Argo (BGC-Argo) floats and satellite observations for water column estimations of the particulate backscattering coefficient

García-Jiménez, Jorge; Ruescas, Ana B.; Amorós-López, Julia; Sauzède, Raphaëlle

doi:https://doi.org/10.5194/os-21-1677-2025

Articles | Volume 21, issue 4

https://doi.org/10.5194/os-21-1677-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/os-21-1677-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 4

Technical note

|

05 Aug 2025

Technical note |

| 05 Aug 2025

Combining BioGeoChemical-Argo (BGC-Argo) floats and satellite observations for water column estimations of the particulate backscattering coefficient

Jorge García-Jiménez, Ana B. Ruescas, Julia Amorós-López, and Raphaëlle Sauzède

Data sets

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

Model code and software

SatArgoBbp: Estimating particulate backscattering coefficient in the upper ocean using BGC-Argo floats and satellite observations IPL-UV https://github.com/IPL-UV/SatArgoBbp

Short summary

Estimation of particulate organic carbon (POC) relies on proxies like the particulate backscattering coefficient (b_bp) derived from BioGeoChemical-Argo (BGC-Argo) floats and satellite data. BGC-Argo floats provide global insights into vertical bio-optical dynamics. This study integrates Sentinel-3 OLCI (Ocean and Land Colour Instrument) data and machine learning approaches to improve b_bp estimates in the top 250 m of the water column. The results differ based on the dynamics of the study areas.