2015
DOI: 10.1016/j.csr.2015.03.005
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Sea surface salinity variability in response to the Congo river discharge

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Cited by 28 publications
(24 citation statements)
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“…This feature is not typical for other large river plumes (e.g., the Amazon [Lentz, 1995;Molleri et al, 2010], Congo [Y. Chao et al, 2015;Denamiel et al, 2013], Mississippi [Fournier et al, 2016;Walker, 1996], and Pearl [Dong et al, 2004;Xu et al, 2019] river plumes) and is caused by the formation of FSL during the relatively short freshet period in June-July. In June, the central Kara Sea is covered by ice and FSL experiences only low influence of wind forcing.…”
Section: Discussionmentioning
confidence: 80%
“…This feature is not typical for other large river plumes (e.g., the Amazon [Lentz, 1995;Molleri et al, 2010], Congo [Y. Chao et al, 2015;Denamiel et al, 2013], Mississippi [Fournier et al, 2016;Walker, 1996], and Pearl [Dong et al, 2004;Xu et al, 2019] river plumes) and is caused by the formation of FSL during the relatively short freshet period in June-July. In June, the central Kara Sea is covered by ice and FSL experiences only low influence of wind forcing.…”
Section: Discussionmentioning
confidence: 80%
“…6 ). Recent data on the extent of the Congo River plume and its influence on sea surface salinity and temperature over expansive coastal regions (Materia et al, 2012 ; Denamiel et al, 2013 ; Chao et al, 2015 ) highlights the importance of the origin of the present-day Congo River outlet for the expansion of mangroves throughout the region. During wet seasons, the Congo plume connects with the Niger River plume, and a lower salinity is recorded for the entire Gulf of Guinea up to and including the region around the Congo outlet.…”
Section: Discussionmentioning
confidence: 99%
“…Plumes can also cause horizontal salinity gradients with spatial scales smaller than the footprint of the satellite radiometers. Typical horizontal SSS gradients for the plumes from the Amazon (Lentz and Limeburner, 1995) or Congo (Chao et al, 2015) exceed 0.2 pss km −1 and extend more than 250 km from the river mouth. Therefore, in the vicinity of a river plume, a spatially sparse array of in situ sensors can exhibit very different SSS variability from that observed by a satellite sensor, even if the measurements are all coincident.…”
Section: A T and C T Algorithm Biasesmentioning
confidence: 99%