Study reveals improved estimates of particulate organic carbon using satellite data in oceanic environments, suggesting better monitoring strategies.
Carbon fluxes from the atmosphere to the ocean and from the ocean surface to the deep ocean are a key pathway in the long-term sequestration of anthropogenic CO2. Particulate Organic Carbon (POC), which comprises living plankton, detritus and other microscopic organisms, is a very dynamic carbon pool in surface waters, so an ability to assess POC reliably from satellites and autonomous profilers is fundamental to the quantification of the reservoirs and fluxes of carbon within the ocean, and to assess their response to climate change. In situ records from sample filtration during dedicated hydrographic surveys are limited both in terms of spatial coverage and time, so reliable algorithms are required that make use of readily available autonomously collected data that provide much better spatial and temporal coverage. In this paper, algorithms that use ocean colour data from satellites to estimate POC are re-assessed, and then the satellite-derived products are compared with near-surface in situ observations from biogeochemical (BGC) Argo profilers. The satellites and in situ BGC-Argo records match each other to within 30%, but a regional bias persists that may be related to the BGC-Argo fluorometers overestimating the chlorophyll concentration in the Southern Ocean. A simple coarse-resolution regional correction to the observed chlorophyll-a concentration and backscatter coefficient, plus the removal of clear outliers, improves the agreement to approximately 15%. The association of POC with the surface chlorophyll value is so strong that an algorithm based on chlorophyll-a alone provides an almost equally good estimate of POC compared with more complex algorithms that incorporate additional bio-optical variables such as the backscattering coefficient.
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Quartly et al. (2026) studied this question.
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