@Article{GouveiaGhWaPaCoAr:2019:SaStAm,
               author = "Gouveia, Nelson de Almeida and Gherardi, Douglas Francisco 
                         Marcolino and Wagner, Fabien Hubert and Paes, E. T. and Coles, V. 
                         J. and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Universidade Federal Rural da 
                         Amazonia (UFRA)} and {University of Maryland Center for 
                         Environmental Science} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "The salinity structure of the Amazon river plume drives 
                         spatiotemporal variation of oceanic primary productivity",
              journal = "Journal of Geophysical Research: Biogeosciences",
                 year = "2019",
               volume = "124",
               number = "1",
                pages = "147--165",
                month = "Jan.",
             keywords = "primary productivity, salinity, Amazon river plume, remote 
                         sensing.",
             abstract = "The Amazon river is a major source of terrestrially derived 
                         organic carbon to the tropical Atlantic Ocean. Field, satellite 
                         and a vertically generalized production model data were used to 
                         estimate empirical surface salinity and fit an inverse logit 
                         function to investigate the limiting effect of salinity on the 
                         productivity in the Amazon river plume. Satellite data included 
                         Moderate Resolution Imaging Spectroradiometer, Soil Moisture and 
                         Ocean Salinity, and Aquarius missions. Previous empirical surface 
                         salinity models have relied on a very narrow range of salinity 
                         values and satellite data to estimate the spatial extent of the 
                         river plume. The empirical surface salinity model presented here 
                         extended the range of salinity values and captures all the main 
                         surface mesoscale features, particularly those related to the main 
                         path of the low-salinity water. We also show that it is possible 
                         to gain new insights on the spatiotemporal variability of the 
                         Amazon river plume by improving the empirical surface salinity and 
                         expanding its sampling period with the aid of remote sensing data. 
                         The variability of primary productivity is dominated by the 
                         subannual (6 month) and annual (12 month) frequency bands. 
                         Low-salinity river water influences surface primary productivity 
                         continuously during the year through mechanisms associated with 
                         the western tropical Atlantic circulation and vertical mixing.",
                  doi = "10.1029/2018JG004665",
                  url = "http://dx.doi.org/10.1029/2018JG004665",
                 issn = "2169-8953",
             language = "en",
           targetfile = "gouveia_salinity.pdf",
        urlaccessdate = "27 abr. 2024"
}