%0 Journal Article
%4 sid.inpe.br/mtc-m21c/2019/02.28.10.54
%2 sid.inpe.br/mtc-m21c/2019/02.28.10.54.11
%@doi 10.1029/2018JG004665
%@issn 2169-8953
%T The salinity structure of the Amazon river plume drives spatiotemporal variation of oceanic primary productivity
%D 2019
%8 Jan.
%9 journal article
%A Gouveia, Nelson de Almeida,
%A Gherardi, Douglas Francisco Marcolino,
%A Wagner, Fabien Hubert,
%A Paes, E. T.,
%A Coles, V. J.,
%A Aragão, Luiz Eduardo Oliveira e Cruz de,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade Federal Rural da Amazonia (UFRA)
%@affiliation University of Maryland Center for Environmental Science
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress nelson.gouveia@inpe.br
%@electronicmailaddress douglas.gherardi@inpe.br
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress luiz.aragao@inpe.br
%B Journal of Geophysical Research: Biogeosciences
%V 124
%N 1
%P 147-165
%K primary productivity, salinity, Amazon river plume, remote sensing.
%X 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.
%@language en
%3 gouveia_salinity.pdf