Sea surface salinity variability in response to the Congo river discharge

Chao, Yi; Farrara, John D.; Schumann, Guy; Andreadis, Konstantinos M.; Möller, D.

doi:10.1016/j.csr.2015.03.005

Cited by 28 publications

(24 citation statements)

References 24 publications

(35 reference 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%

Structure of the Freshened Surface Layer in the Kara Sea During Ice‐Free Periods

et al. 2021

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The Kara Sea is a semi-enclosed sea located between the Siberian coast in the south, Novaya Zemlya in the west, and Severnaya Zemlya in the east (Figure 1). The water depth is less than 50 m at more than 40% of the Kara Sea; shallow areas are located mainly in the central and southeastern parts of the sea. This sea receives enormous freshwater discharge (∼1,500 km 3 annually) mainly from two large estuaries, namely, the Yenisei Gulf (630 km 3 from the Yenisei River) and the Gulf of Ob (530 km 3 from the Ob, Pur, and Taz rivers; Gordeev et al., 1996; Pavlov et al., 1996). Continental discharge to the Kara Sea has very large seasonal variability with a short freshet period in June-July that provides ∼50% of annual runoff and a long low discharge period in October-April caused by freezing of the inflowing rivers (Pavlov et al., 1996; Figure 1). Freshwater discharge forms the large freshened surface layer (FSL) in the Kara Sea which is among the largest freshwater reservoirs in the Arctic Ocean

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Section: Discussionmentioning

confidence: 80%

Structure of the Freshened Surface Layer in the Kara Sea During Ice‐Free Periods

et al. 2021

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“…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%

Following the Mangroves: diversification in the banded lampeye Aplocheilichthys spilauchen (Duméril, 1861) (Cyprinodontiformes: Procatopodidae) along the Atlantic coast of Africa

et al. 2021

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Available ecological information, an extensive distributional range, conflicting osteological data, and a proposed early Miocene origin provide the impetus for the present study which investigates genetic structuring, biogeographic, and phylogenetic relationships within the Aplocheilichthys spilauchen lineage. Through the analysis of the mitochondrial gene COI, species delimitation methods (ABGD, GB, GMYC, bPTP) were applied, recognizing 6-7 OTUs with absolute pairwise genetic distances ranging between 8 and 22%. The onset of diversification is estimated to be within the middle Miocene and both dispersal and vicariance-shaped A. spilauchen diversity and distribution, as suggested by time-calibrated and ancestral range reconstruction (S-DIVA) analyses. We report for the first time, a pattern of diversification within a lineage of brackish water fish that is concordant with the historical distribution of coastal mangroves forests, shaped by a series of historical events that likely affected forest cover since the middle Miocene (e.g. major climate shifts and sealevel fluctuations, onset of the modern Congo River outlet, increased volcanism in the Cameroon Volcanic Line).

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“…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%

Optimum satellite remote sensing of the marine carbonate system using empirical algorithms in the global ocean, the Greater Caribbean, the Amazon Plume and the Bay of Bengal

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Shutler

et al. 2019

Remote Sensing of Environment

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Improving our ability to monitor ocean carbonate chemistry has become a priority as the ocean continues to absorb carbon dioxide from the atmosphere. This long-term uptake is reducing the ocean pH; a process commonly known as ocean acidification. The use of satellite Earth Observation has not yet been thoroughly explored as an option for routinely observing surface ocean carbonate chemistry, although its potential has been highlighted. We demonstrate the suitability of using empirical algorithms to calculate total alkalinity (A T) and total dissolved inorganic carbon (C T), assessing the relative performance of satellite, interpolated in situ, and climatology datasets in reproducing the wider spatial patterns of these two variables. Both A T and C T in situ data are reproducible, both regionally and globally, using salinity and temperature datasets, with satellite observed salinity from Aquarius and SMOS providing performance comparable to other datasets for the majority of case studies. Global root mean squared difference (RMSD) between in situ validation data and satellite estimates is 17 μmol kg −1 with bias < 5 μmol kg −1 for A T and 30 μmol kg −1 with bias < 10 μmol kg −1 for C T. This analysis demonstrates that satellite sensors provide a credible solution for monitoring surface synoptic scale A T and C T. It also enables the first demonstration of observation-based synoptic scale A T and C T temporal mixing in the Amazon plume for 2010-2016, complete with a robust estimation of their uncertainty.

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Sea surface salinity variability in response to the Congo river discharge

Cited by 28 publications

References 24 publications

Structure of the Freshened Surface Layer in the Kara Sea During Ice‐Free Periods

Structure of the Freshened Surface Layer in the Kara Sea During Ice‐Free Periods

Following the Mangroves: diversification in the banded lampeye Aplocheilichthys spilauchen (Duméril, 1861) (Cyprinodontiformes: Procatopodidae) along the Atlantic coast of Africa

Optimum satellite remote sensing of the marine carbonate system using empirical algorithms in the global ocean, the Greater Caribbean, the Amazon Plume and the Bay of Bengal

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