Preprints
https://doi.org/10.5194/egusphere-2024-818
https://doi.org/10.5194/egusphere-2024-818
28 Mar 2024
 | 28 Mar 2024

Interannual variability of Sea Surface Salinity in North-Eastern Tropical Atlantic: influence of freshwater fluxes

Clovis Thouvenin-Masson, Jacqueline Boutin, Vincent Échevin, Alban Lazar, and Jean-Luc Vergely

Abstract. In tropical regions, the fresh water flux entering the ocean originates primarily from precipitation and, to a lesser extent when considering basin scale averages, from continental rivers. Nevertheless, at regional scale, river flows can have a significant impact on the surface ocean dynamics. Riverine fresh water modifies salinity, and therefore density, stratification and circulation. With its particular coastline, relatively high cumulative river discharge, and the vicinity of Inter Tropical Convergence Zone (ITCZ), the eastern Southern North Tropical Atlantic (e-SNTA) region off Northwest Africa is a particularly interesting location to study the linkage between precipitations, river outflows and Sea Surface Salinity (SSS). Here we focus on the regional e-SNTA SSS seasonal cycle and interannual variability. We quantify the impact of river runoff and precipitation on SSS by means of regional simulations forced by different interannual and climatological river runoffs and precipitation products. The simulated SSS are compared with the Climate Change Initiative (CCI) SSS, in situ SSS from Argo, ships and a coastal mooring, and the GLORYS reanalysis SSS. The analysis of the salinity balance in the mixed layer is conducted to explore the dynamics influencing the SSS variability. Overall, the simulations reproduce well the seasonal cycle and interannual variability despite a positive mean model bias north of 15N. The seasonal cycle is impacted by the phasing of the different runoff products. The mixed layer SSS decrease during the rainy season is mainly driven by precipitation followed by runoff by means of horizontal advection and partly compensated by vertical mixing. In terms of interannual anomalies, river runoffs have a more direct impact on SSS than precipitation. This study highlights the importance of properly constraining river runoff and precipitation to simulate realistic SSS, and the importance of observing SSS in coastal regions to validate such constraints.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Clovis Thouvenin-Masson, Jacqueline Boutin, Vincent Échevin, Alban Lazar, and Jean-Luc Vergely

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-818', Anonymous Referee #1, 03 May 2024
  • RC2: 'Comment on egusphere-2024-818', Anonymous Referee #2, 29 May 2024
  • RC3: 'Comment on egusphere-2024-818', Anonymous Referee #3, 05 Jun 2024
Clovis Thouvenin-Masson, Jacqueline Boutin, Vincent Échevin, Alban Lazar, and Jean-Luc Vergely
Clovis Thouvenin-Masson, Jacqueline Boutin, Vincent Échevin, Alban Lazar, and Jean-Luc Vergely

Viewed

Total article views: 367 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
281 67 19 367 14 12
  • HTML: 281
  • PDF: 67
  • XML: 19
  • Total: 367
  • BibTeX: 14
  • EndNote: 12
Views and downloads (calculated since 28 Mar 2024)
Cumulative views and downloads (calculated since 28 Mar 2024)

Viewed (geographical distribution)

Total article views: 361 (including HTML, PDF, and XML) Thereof 361 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 15 Jul 2024
Download
Short summary
Our research focuses on understanding the impact of river runoff and precipitation on sea surface salinity (SSS) in the eastern Southern North Tropical Atlantic (e-SNTA) region off Northwest Africa. By analyzing regional simulations and observational data, we find that river flows significantly influence SSS variability, particularly after the rainy season. Our findings underscore that a main source of uncertainty to represent SSS variability in this region comes from river runoffs estimates.