© 2017 Martínez-Vicente, Evers-King, Roy, Kostadinov, Tarran, Graff, Brewin, Dall'Olmo, Jackson, Hickman, Röttgers, Krasemann, Marañón, Platt and Sathyendranath. The differences among phytoplankton carbon (C phy ) predictions from six ocean color algorithms are investigated by comparison with in situ estimates of phytoplankton carbon. The common satellite data used as input for the algorithms is the Ocean Color Climate Change Initiative merged product. The matching in situ data are derived from flow cytometric cell counts and per-cell carbon estimates for different types of pico-phytoplankton. This combination of satellite and in situ data provides a relatively large matching dataset (N > 500), which is independent from most of the algorithms tested and spans almost two orders of magnitude in C phy . Results show that not a single algorithm outperforms any of the other when using all matching data. Concentrating on the oligotrophic regions (Chlorophyll-a concentration, B, less than 0.15 mg Chl m -3 ), where flow cytometric analysis captures most of the phytoplankton biomass, reveals significant differences in algorithm performance. The bias ranges from -35 to +150% and unbiased root mean squared difference from 5 to 10 mg C m -3 among algorithms, with chlorophyll-based algorithms performing better than the rest. The backscattering-based algorithms produce different results at the clearest waters and these differences are discussed in terms of the different algorithms used for optical particle backscattering coefficient (b bp ) retrieval.
Martínez-Vicente, V., Evers-King, H., Roy, S., Kostadinov, T. S., Tarran, G. A., Graff, J. R., … Sathyendranath, S. (2017). Intercomparison of Ocean Color Algorithms for Picophytoplankton Carbon in the Ocean. Frontiers in Marine Science, 4. https://doi.org/10.3389/fmars.2017.00378