posted on 2025-08-01, 14:19authored byRJW Brewin, G Dall’Olmo, J Gittings, X Sun, PK Lange, DE Raitsos, HA Bouman, I Hoteit, J Aiken, S Sathyendranath
We describe an approach to partition a vertical profile of chlorophyll-a concentration into contributions from two communities of phytoplankton: one (community 1) that resides principally in the turbulent mixed-layer of the upper ocean and is observable through satellite visible radiometry; the other (community 2) residing below the mixed-layer, in a stably stratified environment, hidden from the eyes of the satellite. The approach is tuned to a time-series of profiles from a Biogeochemical-Argo float in the northern Red Sea, selected as its location transitions from a deep mixed layer in winter (characteristic of vertically well-mixed systems) to a shallow mixed layer in the summer with a deep chlorophyll-a maximum (characteristic of vertically stratified systems). The approach is extended to reproduce profiles of particle backscattering, by deriving the chlorophyll-specific backscattering coefficients of the two communities and a background coefficient assumed to be dominated by non-algal particles in the region. Analysis of the float data reveals contrasting phenology of the two communities, with community 1 blooming in winter and 2 in summer, community 1 negatively correlated with epipelagic stratification, and 2 positively correlated. We observe a dynamic chlorophyll-specific backscattering coefficient for community 1 (stable for community 2), positively correlated with light in the mixed-layer, suggesting seasonal changes in photoacclimation and/or taxonomic composition within community 1. The approach has the potential for monitoring vertical changes in epipelagic biogeography and for combining satellite and ocean robotic data to yield a three-dimensional view of phytoplankton distribution.
Funding
549947,SS
BICEP
European Space Agency (ESA)
King Abdullah University of Science and Technology (KAUST)
This is the final version. Available from American Geophysical Union / Wiley via the DOI in this record.
These data were collected and made freely available by the International Argo Program and the national programs that contribute to it (https://argo.ucsd.edu, https://www.ocean-ops.org). The Argo Program is part of the Global Ocean Observing System. All data and code used in the paper are provided openly on a GitHub page (https://github.com/rjbrewin/Two-community-phyto-model). This includes an example Jupyter Notebook Python Script, processing this BGC-Argo float and tuning the models. Details of how to run it without having to install software are provided as Supplementary Material to this manuscript.