Intercomparison of Ocean Color Algorithms for Picophytoplankton Carbon in the Ocean

Frontiers in Marine Science

Emilio Marañón¹  Jason R. Graff²  Shovonlal Roy³  Tihomir S. Kostadinov⁵  Hajo Krasemann⁶  Rüdiger Röttgers⁶  Anna E. Hickman⁷  Robert J. W. Brewin⁸  Giorgio Dall'Olmo⁸  Shubha Sathyendranath⁸  Tom Jackson⁹  Víctor Martínez-Vicente⁹  Glen A. Tarran⁹  Hayley Evers-King⁹  Trevor Platt⁹ 

[1] Departamento de Ecología y Biología Animal, Universidade de Vigo, Vigo, Spain;Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States;Department of Geography and Environmental Sciences, School of Agriculture, Policy and Development, University of Reading, Reading, United Kingdom;Department of Geography and the Environment, University of Richmond, Richmond, VA, United States;Division of Hydrologic Sciences, Desert Research Institute, Reno, NV, United States;Helmholtz-Zentrum Geesthacht, Center for Materials and Coastal Research, Geesthacht, Germany;Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, Southampton, United Kingdom;Plymouth Marine Laboratory, National Centre for Earth Observation, Plymouth, United Kingdom;Plymouth Marine Laboratory, Plymouth, United Kingdom;

关键词: phytoplankton carbon;    carbon-to-chlorophyll;    ocean color remote sensing;    picophytoplankton;    flow cytometry;    optical water class;   

DOI  :  10.3389/fmars.2017.00378

来源: DOAJ

【 摘 要 】

The differences among phytoplankton carbon (Cphy) 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 Cphy. 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 (bbp) retrieval.

【 授权许可】

Unknown