Wind speed and mesoscale features drive net autotrophy in the South Atlantic Ocean

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