This dataset collection contains a 10 year monthly climatology and monthly composites of the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) over the globe for the period Sep 1997-2007, as produced by the Plymouth Marine Laboratory (PML) using SeaWIFs data. Accompanying maps are also available. This dataset contributes to fulfilling the first objective of the National Centre for Earth Observation (NCEO) Theme 2 programme (Monitoring, Diagnosis and Prediction of the Global Carbon-Cycle), Quantification of ocean biogeochemistry and carbon fluxes sub-theme 6 (ST6): Quantify the global oceanic organic C cycle using OC data, partitioned into phytoplankton (pigments, biomass, size structure & PFTs), particulate organic C, coloured dissolved organic matter (CDOM), dissolved and particulate inorganic components. Understanding the interaction between phytoplankton and the in-water light field is crucial to model ocean primary production and to improve our comprehension of the role of biological processes in the ocean–carbon cycle. The absorption coefficient of phytoplankton is a fundamental quantity in marine primary production models because: - it alters the transmission of light underwater; - it modifies the photosynthetic response of phytoplankton to available light; - it can be used as a direct indicator of phytoplankton abundance and phytoplankton size; - it can be used as an indicator of environmental variability It is well known that the phytoplankton absorption coefficient is a function of the dominant phytoplankton pigment, chlorophyll-a, and that this relationship is directly linked to changes in both pigment composition and size structure.

This dataset contains the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) over the globe for the period 1997-2007, as produced by the Plymouth Marine Laboratory (PML) using SeaWIFs data. A 10 year monthly climatology is available together with accompanying maps. This dataset was produced as part of the National Centre for Earth Observation (NCEO) Theme 2 programme (Monitoring, Diagnosis and Prediction of the Global Carbon-Cycle), Quantification of ocean biogeochemistry and carbon fluxes sub-theme 6 (ST6).

This dataset contains the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) in monthly averages over the globe for the period 1997-2007, as produced by the Plymouth Marine Laboratory (PML) using SeaWIFs data (The dataset was produced by the Plymouth Marine Laboratory by applying the algorithm of Brewin et al. (2010) directly to monthly SeaWiFS Level 3 composites of chlorophyll on a pixel-by-pixel basis.). A 10 year monthly climatology is also available as a separate dataset. Accompanying maps are available. This dataset was produced as part of the National Centre for Earth Observation (NCEO) Theme 2 programme (Monitoring, Diagnosis and Prediction of the Global Carbon-Cycle), Quantification of ocean biogeochemistry and carbon fluxes sub-theme 6 (ST6).

This dataset contains monthly global carbon products for pico-, nano- and microphytoplankton (C_picophyto, C_nanophyto and C_microphyto, respectively, in mg C m-3) and the total phytoplankton community (C_phyto in mg C m-3) for the period of 1998 to 2020 at 9 km spatial resolution. A spectrally-resolved photoacclimation model was unified with a primary production model that simulated photosynthesis as a function of irradiance using a two-parameter photosynthesis versus irradiance (P-I) function to estimate the carbon content of marine phytoplankton based on ocean-colour remote sensing products (Sathyendranath et al. 2020 and references therein for details). The photoacclimation model contains a maximum chlorophyll-to-carbon ratio for three different phytoplankton size classes (pico-, nano- and microphytoplankton) that was inferred from field data, as in Sathyendranath et al. (2020). Chlorophyll-a products were obtained from the European Space Agency (ESA) Ocean Colour Climate Change Initiative (OC-CCI v5.0 dataset). Photosynthetic Active Radiation (PAR) products were obtained from the National Aeronautics and Space Administration (NASA) and were corrected for inter-sensor bias in products. Mixed Layer Depth (MLD) was obtained from the French Research Institute for Exploration of the Sea (Ifremer). In situ datasets P-I parameters were incorporated as described in Kulk et al. (2020). The phytoplankton carbon products were generated as part of the ESA Biological Pump and Carbon Exchange Processes (BICEP) project. Support from the Simons Foundation grant ‘Computational Biogeochemical Modeling of Marine Ecosystems’ (CBIOMES, number 549947) and from the National Centre of Earth Observation (NCEO) is acknowledged. Data are provided as netCDF files containing carbon products for pico-, nano- and microphytoplankton (C_picophyto, C_nanophyto and C_microphyto, respectively, in mg C m-3) and the total phytoplankton community (C_phyto in mg C m-3) for the period of 1998 to 2020 at 9 km spatial resolution. Additional variables that were used for the calculation of the phytoplankton carbon products are also provided, including chlorophyll-a (chl_a in mg m-3), photosynthetically activate radiation (par, in µmol photons m-2 d-1), mixed layer depth (mld in m) and the mean spectral nondimensional irradiance (mean_spectral_i_star). References: Sathyendranath, S.; Platt, T.; Kovač, Ž.; Dingle, J.; Jackson, T.; Brewin, R.J.W.; Franks, P.; Marañón, E.; Kulk, G.; Bouman, H.A. Reconciling models of primary production and photoacclimation. Applies Optics, 2020, 59, C100. doi.org/10.1364/AO.386252 Kulk, G.; Platt, T.; Dingle, J.; Jackson, T.; Jönsson, B.F.; Bouman, H.A., Babin, M.; Doblin, M.; Estrada, M.; Figueiras, F.G.; Furuya, K.; González, N.; Gudfinnsson, H.G.; Gudmundsson, K.; Huang, B.; Isada, T.; Kovač, Ž.; Lutz, V.A.; Marañón, E.; Raman, M.; Richardson, K.; Rozema, P.D.; Van de Poll, W.H.; Segura, V.; Tilstone, G.H.; Uitz, J.; van Dongen-Vogels, V.; Yoshikawa, T.; Sathyendranath S. Primary production, an index of climate change in the ocean: Satellite-based estimates over two decades. Remote Sens. 2020, 12,826. doi:10.3390/rs12050826