Abstract

A comprehensive in situ dataset of chlorophyll a (Chl a; N = 18,001), net primary production (NPP; N = 165) and net community production (NCP; N = 95), were used to evaluate the performance of Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-A) algorithms for these parameters, in the South Atlantic Ocean, to facilitate the accurate generation of satellite NCP time series. For Chl a, five algorithms were tested using MODIS-A data, and OC3-CI performed best, which was subsequently used to compute NPP. Of three NPP algorithms tested, a Wavelength Resolved Model (WRM) was the most accurate, and was therefore used to estimate NCP with an empirical relationship between NCP with NPP and sea surface temperature (SST). A perturbation analysis was deployed to quantify the range of uncertainties introduced in satellite NCP from input parameters. The largest reductions in the uncertainty of satellite NCP came from MODIS-A derived NPP using the WRM (40%) and MODIS-A Chl a using OC3-CI (22%). The most accurate NCP algorithm, was used to generate a 16 year time series (2002 to 2018) from MODIS-A to assess climate and environmental drivers of NCP across the South Atlantic basin. Positive correlations between wind speed anomalies and NCP anomalies were observed in the central South Atlantic Gyre (SATL), and the Benguela Upwelling (BENG), indicating that autotrophic conditions may be fuelled by local wind-induced nutrient inputs to the mixed layer. Sea Level Height Anomalies (SLHA), used as an indicator of mesoscale eddies, were negatively correlated with NCP anomalies offshore of the BENG upwelling fronts into the SATL, suggesting autotrophic conditions are driven by mesoscale features. The Agulhas bank and Brazil-Malvinas confluence regions also had a strong negative correlation between SLHA and NCP anomalies, similarly indicating that NCP is forced by mesoscale eddy generation in this region. Positive correlations between SST anomalies and the Multivariate ENSO Index (MEI) in the SATL, indicated the influence of El Niño events on the South Atlantic Ocean, however the plankton community response was less clear.

Publication Date

2021-01-01

Publication Title

Remote Sensing of Environment

Volume

260

ISSN

0034-4257

Acceptance Date

2021-04-02

Deposit Date

2026-06-15

Funding

DF was supported by a GW4+ Doctoral Training Partnership studentship from the UK Natural Environment Research Council (NERC; NE/L002434/1). GT was supported by the AMT4SentinelFRM (ESRIN/RFQ/3-14457/16/I-BG) and AMT4OceanSatFlux (4000125730/18/NL/FF/gp) contracts from the European Space Agency and by NERC National Capability funding to Plymouth Marine Laboratory for the Atlantic Meridional Transect (AMT). PL was supported by SPBU travel grant # 41128672. GT and MK were also funded by NERC International Opportunity Fund Grant Satellite estimates of marine net community production in the South Atlantic from Sentinel-3 (SemSAS; NE/P00878X/1). MK was partially funded by P&D ANP/BRASOIL Project no. 48610.011013/2014-66; Dalio Foundation Proj. Amazon Reefs. FB and MC were supported by four Oceanographic Institute of the University of São Paulo (IOUSP) projects (FAPESP 2015/01373-0; CNPq 442926/2015-4; FAPESP 2014/50820-7; CNPq 565060/2010-4) for the collection of the Chl a data used in the BRAZ dataset. We would like to thank the captain and crew of RRS Discovery, RRS James Clark Ross and RRS James Cook for conducting the AMTs. We also thank the Natural Environment Research Council Earth Observation Data Acquisition and Analysis Service (NEODAAS) for use of the Linux cluster to process the MODIS-A satellite imagery. The altimeter products were produced by Ssalto/Duacs and distributed by Aviso+, with support from Cnes (https://www.aviso.altimetry.fr). The AMT is funded by NERC through its National Capability Long-term Single Centre Science Programme, Climate Linked Atlantic Sector Science (NE/R015953/1). This study contributes to the international IMBeR project and is contribution number 354 of the AMT programme.

Keywords

Environmental drivers, in situ uncertainty, MODIS-A, Ocean colour, Ocean metabolism, South Atlantic Ocean

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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