Surface Freshwater Fluxes in the Arctic and Subarctic Seas during Contrasting Years of High and Low Summer Sea Ice Extent

Hall, Sarah B.; Subrahmanyam, Bulusu; Nyadjro, Ebenezer S.; Samuelsen, Annette

doi:10.3390/rs13081570

Cited by 5 publications

(6 citation statements)

References 77 publications

(104 reference statements)

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“…examined SMAP in the coastal waters of the Gulf of Maine and found the monthly SSS anomalies to be sufficiently accurate and applicable for coastal studies. Hall et al [2021] used SMAP and SMOS in the Arctic and found them to successfully capture sea ice extent and SSS variability, while Hackert et al [2019] demonstrated that including SMAP into the initialization of coupled model forecasts had positive impacts. Despite its quite extensive, successful applications in other seas and ocean basins, to date, and to the best of our knowledge, there has not been any dedicated study aimed at examining SSS variability from SMAP in the NWGoG.…”

Section: Introductionmentioning

confidence: 99%

Seasonal Variability of Sea Surface Salinity in the NW Gulf of Guinea from SMAP Satellite

Nyadjro

Foli

Agyekum

et al. 2021

Remote Sens Earth Syst Sci

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The advent of satellite-derived sea surface salinity (SSS) measurements has boosted scientific study in less-sampled ocean regions such as the northwestern Gulf of Guinea (NWGoG). In this study, we examine the seasonal variability of SSS in the NWGoG from the Soil Moisture Active Passive (SMAP) satellite and show that it is well-suited for such regional studies as it is able to reproduce the observed SSS features in the study region. SMAP SSS bias, relative to in-situ data comparisons, reflects the differences between skin layer measurements and bulk-surface measurements that have been reported by previous studies. The study results reveal three broad anomalous SSS features: a basin-wide salinification during boreal summer, a basin-wide freshening during winter, and a meridionally-oriented frontal system during other seasons. A salt budget estimation suggests that the seasonal SSS variability is dominated by changes in freshwater flux, zonal circulation and upwelling. Freshwater flux, primarily driven by the seasonally varying Intertropical Convergence Zone, is a dominant contributor to salt budget in all seasons except during fall. Regionally, SSS is most variable off southwestern Nigeria and controlled primarily by westward extensions of the Niger River. Anomalous salty SSS off the coasts of Cote d'Ivoire and Ghana especially during summer are driven mainly by coastal upwelling and horizontal advection.

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Section: Introductionmentioning

confidence: 99%

Seasonal Variability of Sea Surface Salinity in the NW Gulf of Guinea from SMAP Satellite

Nyadjro

Foli

Agyekum

et al. 2021

Remote Sens Earth Syst Sci

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“…The 1/12°degree CMEMS GLORYS12V1 reanalysis (hereafter referred to as GLORYS12V1) (Lellouche et al, 2021) is used as a comparison dataset alongside the satellite products over the common observational periods (since 2011/2015) in this region (Table 1). This reanalysis is chosen for its high spatial resolution, its good representation of Arctic SIC, and its previous application to salinity variability in the Subpolar North Atlantic and Arctic (Biló et al, 2022;Hall et al, 2021;Lellouche et al, 2021;Liu et al, 2022). For consistency with the satellite SSS products, the GLORYS12V1 reanalysis is re-gridded onto a 0.25°grid for comparison with in situ data.…”

Section: Reanalysesmentioning

confidence: 99%

“…ECMWF's fifth-generation reanalysis of global weather and climate (ERA5) monthly eastward and northward turbulent surface stress is used in assessing the main drivers of Laptev Sea interannual variability (Hersbach et al, 2020). The monthly mean NCEI Climate Prediction Center (CPC) Arctic Oscillation Index (AOI) (https://www.ncei.noaa.gov/ access/monitoring/ao/, last access: 5 March 2024) is also used to relate local eastward wind stress patterns to largerscale atmospheric circulation.…”

Section: Reanalysesmentioning

confidence: 99%

Drivers of Laptev Sea interannual variability in salinity and temperature

Hudson,

Martin,

Josey

et al. 2024

Ocean Sci.

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Abstract. Eurasian rivers provide a quarter of total fresh water to the Arctic, maintaining a persistent fresh layer that covers the surface Arctic Ocean. This freshwater export controls Arctic Ocean stratification, circulation, and basin-wide sea ice concentration. The Lena River supplies the largest volume of runoff and plays a key role in this system, as runoff outflows into the Laptev Sea as a particularly shallow plume. Previous in situ and modelling studies suggest that local wind forcing is a driver of variability in Laptev sea surface salinity (SSS) but there is no consensus on the roles of Lena River discharge and sea ice cover in contributing to this variability or on the dominant driver of variability. Until recently, satellite SSS retrievals were insufficiently accurate for use in the Arctic. However, retreating sea ice cover and continuous progress in satellite product development have significantly improved SSS retrievals, giving satellite SSS data true potential in the Arctic. In this region, satellite-based SSS is found to agree well with in situ data (r>0.8) and provides notable improvements compared to the reanalysis product used in this study (r>0.7) in capturing patterns and variability observed in in situ data. This study demonstrates a novel method of identifying the dominant drivers of interannual variability in Laptev Sea dynamics within reanalysis products and testing if these relationships appear to hold in satellite-based SSS, sea surface temperature (SST) data, and in situ observations. The satellite SSS data firmly establish what is suggested by reanalysis products and what has previously been subject to debate due to the limited years and locations analysed with in situ data; the zonal wind is the dominant driver of offshore or onshore Lena River plume transport. The eastward wind confines the plume to the southern Laptev Sea and drives alongshore transport into the East Siberian Sea, and westward wind drives offshore plume transport into the northern Laptev Sea. This finding is affirmed by the strong agreement in SSS pattern under eastward and westward wind regimes in all reanalyses and satellite products used in this study, as well as with in situ data. The pattern of SST also varies with the zonal wind component and drives spatial variability in sea ice concentration.

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“…This provides the maximum satellite data for comparison in September, and large variability in SSS to compare to ice extent. The two years 2016 and 2017 were the only two covered by every product compared, and as 2016 was a year of anomalously low ice, 2017 was chosen to compare the SSS and sea-ice extent to contrast some capabilities of the models [65]. ECCO is the only model simulation used here that assimilates satellite-derived salinity and uses the Aquarius product [39].…”

Section: Sea Surface Variability and Connection To Freshwatermentioning

confidence: 99%

Comparison of Freshwater Content and Variability in the Arctic Ocean Using Observations and Model Simulations

et al. 2023

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Freshwater content (FWC), generally characterized in the Arctic Ocean by salinities lower than 34.8 psu, has shifted in both quantity and distribution in recent decades in the Arctic Ocean. This has been largely driven by changes in the volume and salinity of freshwater sources and the direction and magnitude of major currents. In this study, we analyze the variability in FWC and other physical oceanographic variables from 1993 to 2021 in the Arctic Ocean and Beaufort Gyre (BG) using in situ and remote sensing observations and five ocean models and reanalysis products. Generally, ocean models and reanalysis products underestimate FWC in the BG when compared with observations. Modeled FWC and sea surface height (SSH) in the BG are well correlated during the time period and are similar to correlations of the observational data of these variables. ORAS5 compares best to EN4 salinity over the entire study period, although GLORYS12 agrees well pre-2007 and SODA post-2007. Outside the BG, consistency between modeled SSH, FWC, and limited observations varies between models. These comparisons help identify discrepancies in ocean model and reanalysis products while highlighting areas where future improvements are necessary to further our understanding of Arctic FWC. As observations are scarce in the Arctic, these products and their accuracy are important to studying this dynamic and vulnerable ocean.

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Surface Freshwater Fluxes in the Arctic and Subarctic Seas during Contrasting Years of High and Low Summer Sea Ice Extent

Cited by 5 publications

References 77 publications

Seasonal Variability of Sea Surface Salinity in the NW Gulf of Guinea from SMAP Satellite

Seasonal Variability of Sea Surface Salinity in the NW Gulf of Guinea from SMAP Satellite

Drivers of Laptev Sea interannual variability in salinity and temperature

Comparison of Freshwater Content and Variability in the Arctic Ocean Using Observations and Model Simulations

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