To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: a) the mismatch between satellite, in situ and model data on phytoplankton composition, b) the lack of quantitative uncertainty estimates provided with satellite data, c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: i) an increased communication and round-robin exercises among and within the related expert groups, ii) the launching of higher spectrally and spatially resolved sensors, iii) the development of algorithms that exploit hyperspectral information, and of iv) techniques to merge and synergistically use the various streams of continuous information on phytoplankton diversity from various satellite sensors’ and in situ data to ensure long-term monitoring of phytoplankton composition.

Regional relationships to estimate the main Phytoplankton Functional Types (PFTs) and Size Classes (PSCs) from satellite data are presented. Following the abundance-based approach and selecting the Total Chlorophyll a (TChla) as descriptor of the trophic status of the environment, empirical relations between the TChla concentration and seven accessory pigments, marker for the main algal groups, have been developed for the Mediterranean Sea. Using only in-situ data acquired in this basin, firstly a previous regional diagnostic pigment analysis has been conducted to evaluate the specific pigment ratios featuring the phytoplankton assemblage that occurs in the Mediterranean Sea. Secondly, the new regional PFT and PSC algorithms have been calibrated and validated on the in-situ dataset. The statistical analysis showed a very good predictive power for all the new regional models. A quantitative comparison with global abundance-based models applied to our validation dataset showed that the regionalization improves the uncertainty and the spread of about one order of magnitude for all the classes (e.g. in the nano class, where the mean bias error improves from -0.056 to 0.001 mg m-3). These results highlighted that a regionalization for the PSC and PFT estimates are required, to take into account the peculiar bio-optical properties of the Mediterranean Sea. Finally, the new regional equations have been applied to the Mediterranean TChla satellite (1998-2015) time series to estimate annual and monthly PFT and PSC climatology. The analysis of the climatological maps, relative to the phytoplankton assemblage distribution patterns, reveals that all the three size classes reach their maxima in the higher nutrient areas, with absolute values greater than 3 mg m-3 of TChla for micro-, and about 1.6 and 0.4 mg m-3 for nano- and pico-phytoplankton respectively. Moreover, the nano component shows intermediate percentage values in the whole basin, ranging from 30 to 40% of the TChla in the western basin, up to 45% in the more productive areas. In terms of chlorophyll concentration, in the coastal areas we find the predominance of the Diatoms and Haptophytes, while in the ultra-oligotrophic waters Prokaryotes predominates on the other groups, constituting the principal component of the pico-phytoplankton.

The seasonal and year-to-year variability of the phytoplankton size class (PSC) spatial distribution has been examined in the Mediterranean Sea by using the entire time series of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) space observations (1998–2010). Daily maps of PSCs have been determined using an empirical model based on a synoptic relationship between surface chlorophyll a and diagnostic pigments referred to different taxonomic groups. The analysis of micro-, nano- and pico-phytoplankton satellite time series (1998–2010) describes, quantitatively, the algal assemblage structure over the basin and reveals that the main contribution to chlorophyll a in most of the Mediterranean Sea comes from the pico-phytoplankton component, especially in nutrient-poor environments. Regions with different and peculiar features are the Northwestern Mediterranean Sea, the Alborán Sea and several coastal areas, such as the North Adriatic Sea. In these areas, local interactions between physical and biological components modulate the composition of the three phytoplankton size classes. It results that, during the spring bloom season, micro-phytoplankton dominates in areas of intense vertical winter mixing and deep/intermediate water formation, while in coastal areas micro-phytoplankton dominates in all seasons because of the nutrient supply from the terrestrial inputs. In the Alborán Sea, where the Atlantic inflow modulates the nutrient availability, any predominance of one class over the other two has been observed. The nano-phytoplankton component instead remains widespread over the entire basin along the year, and its contribution to chlorophyll a is of the order of 30–40 %. The largest inter-annual signal occurs in the Northwestern Mediterranean Sea, driven by the year-to-year variation in intensity and extension of the spring bloom, followed by the Alborán Sea, in which the inter-annual variability is strongly modulated by the Atlantic inflow. In absence of sufficient in situ data of community composition, the satellite-based analysis demonstrated that pico-, nano- and micro-phytoplankton classes often coexist. The predominance of one group over the other ones is strongly dependent on the physical and biological processes occurring at the mesoscale. These processes directly influence the nutrient and light availability, which are the principal forcing for the algae growth.

In this work we produced a long‐term reanalysis of the phytoplankton community structure in the Mediterranean Sea and used it to define ecoregions. These were based on the spatial variability of the phytoplankton type fractions and their influence on selected carbon fluxes. A regional ocean color product of four phytoplankton functional types (PFTs; diatoms, dinoflagellates, nanophytoplankton, and picophytoplankton) was assimilated into a coupled physical‐biogeochemical model of the Mediterranean Sea (Proudman Oceanographic Laboratory Coastal Ocean Modelling System‐European Regional Seas Ecosystem Model, POLCOMS–ERSEM) by using a 100‐member ensemble Kalman filter, in a reanalysis simulation for years 1998–2014. The reanalysis outperformed the reference simulation in representing the assimilated ocean color PFT fractions to total chlorophyll, although the skill for the ocean color PFT concentrations was not improved significantly. The reanalysis did not impact noticeably the reference simulation of not assimilated in situ observations, with the exception of a slight bias reduction for the situ PFT concentrations, and a deterioration of the phosphate simulation. We found that the Mediterranean Sea can be subdivided in three PFT‐based ecoregions, derived from the spatial variability of the PFT fraction dominance or relevance. Picophytoplankton dominates the largest part of open ocean waters; microphytoplankton dominates in a few, highly productive coastal spots near large‐river mouths; nanophytoplankton is relevant in intermediate‐productive coastal and Atlantic‐influenced waters. The trophic and carbon sedimentation efficiencies are highest in the microphytoplankton ecoregion and lowest in the picophytoplankton and nanophytoplankton ecoregions. The reanalysis and regionalization offer new perspectives on the variability of the structure and functioning of the phytoplankton community and related biogeochemical fluxes, with foreseeable applications in Blue Growth of the Mediterranean Sea.

The Ocean Colour Thematic Assembly Centre (OCTAC) of the Copernicus Marine Service delivers state-of-the-art Ocean Colour core products for both global oceans and European seas, derived from multiple satellite missions. Since 2015, the OCTAC has provided global and regional high-level merged products that offer value-added information not directly available from space agencies. This is achieved by integrating observations from various missions, resulting in homogenized, inter-calibrated datasets with broader spatial coverage than single-sensor data streams. OCTAC enhanced continuously the basin-level accuracy of essential ocean variables (EOVs) across the global ocean and European regional seas, including the Atlantic, Arctic, Baltic, Mediterranean, and Black seas. From 2019 onwards, new EOVs have been introduced, focusing on phytoplankton functional groups, community structure, and primary production. This paper provides an overview of the evolution of the OCTAC catalogue from 2015 to date, evaluates the accuracy of global and regional products, and outlines plans for future product development.

A relevant indicator for the eutrophication status in the Baltic Sea is the Chlorophyll-a concentration (Chl-a). Alas, ocean color remote sensing applications to estimate Chl-a in this brackish basin, characterized by large gradients in salinity and dissolved organic matter, are hampered by its optical complexity and atmospheric correction limits. This study presents Chl-a retrieval improvements for a fully reprocessed multi-sensor time series of remote-sensing reflectances (R_rs) at ~1 km spatial resolution for the Baltic Sea. A new ensemble scheme based on multilayer perceptron neural net (MLP) bio-optical algorithms has been implemented to this end. The study documents that this approach outperforms band-ratio algorithms when compared to in situ datasets, reducing the gross overestimates of Chl-a observed in the literature for this basin. The R_rs and Chl-a time series were then exploited for eutrophication monitoring, providing a quantitative description of spring and summer phytoplankton blooms in the Baltic Sea over 1998–2019. The analysis of the phytoplankton dynamics enabled the identification of the latitudinal variations in the spring bloom phenology across the basin, the early blooming in spring in the last two decades, and the description of the spatiotemporal coverage of summer cyanobacterial blooms in the central and southern Baltic Sea.