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. This paper concerns the GlobColour-merged chlorophyll  a products based on satellite observation (SeaWiFS, MERIS, MODIS, VIIRS andOLCI) and disseminated in the framework of the Copernicus MarineEnvironmental Monitoring Service (CMEMS). This work highlights the main advantages provided by the CopernicusGlobColour processor which is used to serve CMEMS with a long time seriesfrom 1997 to present at the global level (4 km spatial resolution) and forthe 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 productsprovided 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 priorreflectance merging before chlorophyll  a derivation and uses a moreconstrained flagging approach. Although this work addresses these two topics, it does not pretend toprovide a full comparison of the two data sets, which will require a bettercharacterisation and additional inter-comparison with in situ data.

ocean science

The CMEMS GlobColour chlorophyll &amp;lt;i&amp;gt;a&amp;lt;/i&amp;gt; product based on satellite observation: multi-sensor merging and flagging strategies