Abstract. This paper concerns the GlobColour-merged chlorophyll a products based on satellite observation (SeaWiFS, MERIS, MODIS, VIIRS and OLCI) and disseminated in the framework of the Copernicus Marine Environmental Monitoring Service (CMEMS). This work highlights the main advantages provided by the Copernicus GlobColour processor which is used to serve CMEMS with a long time series from 1997 to present at the global level (4 km spatial resolution) and for the Atlantic level 4 product (1 km spatial resolution). To compute the merged chlorophyll a product, two major topics are discussed: The first of these topics is the strategy for merging remote-sensing data, for which two options are considered. On the one hand, a merged chlorophyll a product computed from a prior merging of the remote-sensing reflectance of a set of sensors. On the other hand, a merged chlorophyll a product resulting from a combination of chlorophyll a products computed for each sensor. The second topic is the flagging strategy used to discard non-significant observations (e.g. clouds, high glint and so on). These topics are illustrated by comparing the CMEMS GlobColour products provided by ACRI-ST (Garnesson et al., 2019) with the OC-CCI/C3S project (Sathyendranath et al., 2018). While GlobColour merges chlorophyll a products with a specific flagging, the OC-CCI approach is based on a prior reflectance merging before chlorophyll a derivation and uses a more constrained flagging approach. Although this work addresses these two topics, it does not pretend to provide a full comparison of the two data sets, which will require a better characterisation and additional inter-comparison with in situ data.

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<p>With the extensive use of ocean color (OC) satellite products, diverse algorithms have been developed in the past decades to observe the phytoplankton community structure in terms of functional types, taxonomic groups and size classes. There is a need to combine satellite observations and biogeochemical modelling to enable comprehensive phytoplankton groups time series data and predictions under the changing climate. A prerequisite for this is continuous long-term satellite observations from past and current OC sensors with quantified uncertainties are essential to ensure their application. Previously we have configured an approach, namely OLCI-PFT (v1), to globally retrieve total chlorophyll a concentration (TChl-a), and chlorophyll a concentration (Chl-a) of multiple phytoplankton functional types (PFTs). This algorithm is developed based on empirical orthogonal functions (EOF) using satellite remote sensing reflectance (Rrs) products from the GlobColour archive (https://www.globcolour.info/). The algorithm can be applied to both, merged OC products and Sentinel 3A OLCI data. Global PFT Chl-a products of OLCI-PFT v1 are available on CMEMS under Ocean Products since July 2020. Lately we have updated the approach and established the OLCI-PFT v2 by including sea surface temperature (SST) as input data. The updated version delivers improved global products for the aforementioned PFT quantities. The per-pixel uncertainty of the retrieved TChl-a and PFT Chl-a products is estimated and validated by taking into account the uncertainties from both input data (satellite Rrs and SST) and model parameters through Monte Carlo simulations and analytical error propagation. The uncertainty of the OLCI-PFT products v2 was assessed on a global scale. For PFT Chl-a products this has been done for the first. The uncertainty of OLCI-PFT v2 TChl-a product is in general much lower than that of the TChl-a product generated in the frame of the ESA Ocean Colour Climate Change Initiative project (OC-CCI). The OLCI-PFT algorithm v1 and v2 have also been further adapted to use a merged MODIS-VIRRS input. Good consistency has been found between the OLCI-PFT products derived from using input data from the different OC sensors. This sets the ground to realize long-term continuous satellite global PFT products from OLCI-PFT. Satellite PFT uncertainty, as provided for our products, is essential to evaluate and improve coupled ecosystem-ocean models which simulate PFTs, and furthermore can be used to improve these models directly via data assimilation.</p>

As phytoplankton play a fundamental role in marine food webs and biogeochemical cycling, their community structure and taxonomic composition have been widely investigated in recent decades through various observational methods and ecological modeling (e.g.,

Abstract. This work concerns the chlorophyll products based on Satellite Observation and disseminated in the frame of the Copernicus Marine Environmental Monitoring Service (CMEMS). This work highlights the main advantages provided by the Copernicus Globcolour processor which is used to serve the CMEMS with a long time series from 1997 to present with level 3 & 4 products at Global level (4 km of spatial resolution) and for the Atlantic level 4 product (1 km). It discusses the different ways to merge data coming from different sensors and it is shown that the GlobColour processor approach provide a better flexibility. At present, it is the only one CMEMS processor able to ingest the OLCI-S3A in the merged product (OLCI-S3A data are ingested in the operational CMEMS products since the April 2018 release). Behind the merging, the flagging strategy to go from level 2 provided by spatial agencies to the level 3 CMEMS products is also discussed. A better spatial coverage is demonstrated, including the coastal area which is of particular interest for many users involved in the EU Water Framework and Marine Strategy Framework Directive.