New Estimate of Organic Carbon Export From Optical Measurements Reveals the Role of Particle Size Distribution and Export Horizon

D. J. Clements,S. Yang, T. Weber, A. M. P. McDonnell, R. Kiko, L. Stemmann, D. Bianchi

GLOBAL BIOGEOCHEMICAL CYCLES(2023)

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摘要
Export of sinking particles from the surface ocean is critical for carbon sequestration and to provide energy to the deep biosphere. The magnitude and spatial patterns of this export have been estimated in the past by in situ particle flux observations, satellite-based algorithms, and ocean biogeochemical models; however, these estimates remain uncertain. Here, we use a recent machine learning reconstruction of global ocean particle size distributions (PSDs) from Underwater Vision Profiler 5 measurements to estimate carbon fluxes by sinking particles (35 mu m-5 mm equivalent spherical diameter) from the surface ocean. We combine global maps of PSD properties with empirical relationships constrained against in situ flux observations to calculate particulate carbon export from the euphotic zone (5.8 +/- 0.1 Pg C y(-1)) and annual maximum mixed layer depths (6.1 +/- 0.1 Pg C y(-1)). The new flux reconstructions suggest a less variable seasonal cycle in the tropical ocean and a more persistent export in the Southern Ocean than previously recognized. Smaller particles (less than 418 mu m) contribute most of the flux globally, while larger particles become more important at high latitudes and in tropical upwelling regions. Export from the annual maximum mixed layer exceeds that from the euphotic zone over most of the low-latitude ocean, suggesting shallow particle recycling and net heterotrophy in the deep euphotic zone. These estimates open the way to fully three-dimensional global reconstructions of particle fluxes in the ocean, supported by the growing database of in situ optical observations.
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carbon export,global carbon cycle,machine learning,remote sensing,particulate organic matter
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