BGC-Argo network has been progressively expanded to reach an operational status, whose observation is more and more recognized and used for science activities but also for cross comparison (and to some extent cross-validation) with data coming from other sources. In that spirit, during the last 4 years many efforts have been spent on facilitating the cross-comparison between optical data and derived products from BGC-Argo, and similar parameters that can be derived from Ocean Colour observations from space. The very interesting aspect of this cross comparison is the way to derive, by deduction and physical/biological considerations, which of the two datasets is reliable, or if the two are of good quality etc. An operation platform has been set up (see seasiderendezvous.eu) which allows, in real time, to get matchups between BGC floats measurement and concomitant Ocean Colour data. Doing this exercise has allowed few years ago to put the first elements for a Real Time Quality Control, that is now in place at Coriolis data center. Still, the Ocean Colour is not used operationally for QC, although this was later used experimentally in the QC performed in the frame of Copernicus In Situ Thematic Assembly Centre (INSTAC). The main reason for this non-use is a lack of quantification of uncertainties for both data sources (BGC Argo and Copernicus Ocean Colour data). Early this year, Mignot et al, have proposed to use the Triple Collocation Method (TCM) to quantify uncertainties related to the cross comparison of in situ data (sampling) with modelled results and with BGC-Argo observations for Oxygen, Nitrates and Chlorophyll. We are presently working on a similar approach at global level, using BGC-Argo, Copernicus Glocolour datasets and CMEMS Global modelling (Mignot et al., 2019).
Apart from initial datasets (Copernicus-Globcolour for OC, Copernicus Global model (NEMO/PSICES) and BGC-Argo) and methodology, the result that is proposed to be presented at OSM, is a quantification of uncertainties of Ocean Colour derived products, of BGC-Argo in comparison with modeling. This would be a good contribution to assimilation procedures of both BGC-Argo and Ocean Colour data into biogeochemical modelling, and, back to the initial question, it would constitute a valuable input for sound QC between BGC-Argo and Ocean Colour.