@Article{FordTSKLSPSLCBLKB:2021:WiSpMe,
               author = "Ford, Daniel and Tilstone, Gavin H. and Shutler, Jamie D. and 
                         Kitidis, Vassilie and Lobanova, Polina and Schwarz, Jill and 
                         Poulton, Alex J. and Serret, Pablo and Lamont, Tarron and Chuqui, 
                         Mateus and Barlow, Ray and Lozano, Jose and Kampel, Milton and 
                         Brandini, Frederico",
          affiliation = "{Plymouth Marine Laboratory} and {Plymouth Marine Laboratory} and 
                         {University of Exeter} and {Plymouth Marine Laboratory} and {St. 
                         Petersburg State University} and {University of Plymouth} and 
                         {Heriot-Watt University} and {Universidad de Vigo} and {Oceans \& 
                         Coasts Research} and {Universidade de S{\~a}o Paulo (USP)} and 
                         {Bayworld Centre for Research \& Education} and {Universidad de 
                         Vigo} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade de S{\~a}o Paulo (USP)}",
                title = "Wind speed and mesoscale features drive net autotrophy in the 
                         South Atlantic Ocean",
              journal = "Remote Sensing of Environment",
                 year = "2021",
               volume = "260",
                pages = "e112435",
                month = "July",
             keywords = "MODIS-A, in situ uncertainty, Ocean colour, Environmental drivers, 
                         South Atlantic Ocean, Ocean metabolism.",
             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 Niņo 
                         events on the South Atlantic Ocean, however the plankton community 
                         response was less clear.",
                  doi = "10.1016/j.rse.2021.112435",
                  url = "http://dx.doi.org/10.1016/j.rse.2021.112435",
                 issn = "0034-4257",
             language = "en",
           targetfile = "ford_wind.pdf",
        urlaccessdate = "09 maio 2024"
}