Isotope (δD, δ18О) systematics in waters of the Russian Arctic seas

Дубинина, Е. О.; Kossova, S. А.; Miroshnikov, А. Yu.; Kokryatskaya, N. M.

doi:10.1134/s0016702917110052

Cited by 21 publications

(17 citation statements)

References 36 publications

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“…The Ob-Yenisei and Lena plumes are the main sources of low salinity water in the surface layer in the Kara and Laptev seas during ice-free periods. As during this season the impact of the sea ice melting on salinity in coastal areas is negligible 48 , variability of surface salinity in the Vilkitsky, Sannikov, and Laptev straits is indicative of eastward spreading of these river plumes. The analysis of wind forcing, salinity data, and satellite imagery shows that generally there are two salinity regimes in the Vilkitsky Strait (indicated by boxes in Fig.…”

Section: Discussionmentioning

confidence: 99%

Freshwater transport between the Kara, Laptev, and East-Siberian seas

Osadchiev

Pisareva

Spivak

et al. 2020

Sci Rep

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The Kara and Laptev seas receive about one half of total freshwater runoff to the Arctic Ocean from the ob, Yenisei, and Lena rivers. Discharges of these large rivers form freshened surface water masses over wide areas in these seas. these water masses, i.e., the ob-Yenisei and Lena river plumes, generate an eastward buoyancy boundary current that accounts for the large-scale zonal freshwater transport along the Siberian part in the Arctic ocean. in this study we investigate spreading of the ob-Yenisei plume from the Kara Sea to the Laptev Sea through the Vilkitsky Strait and of the Lena plume from the Laptev Sea to the east-Siberian Sea through the Laptev and Sannikov straits during ice-free season. Large horizontal density gradient between freshened plume water and salty ambient sea water is the main driver of these processes, however, their intensity strongly depends on local wind forcing. the ob-Yenisei plume is spreading to the Laptev Sea in a narrow alongshore current which is induced by strong and long-term southwesterly winds. Under other wind forcing the plume does not reach the Vilkitsky Strait. the Lena plume is almost constantly spreading to the east-Siberian Sea as a large-scale surface water mass which intensity is governed by eastward ekman transport and is prone to large synoptic variability. The Ob, Yenisei and Lena rivers contribute large volumes of freshwater discharge into the Kara (~ 1,500 km 3 annually from the Ob and Yenisei rivers) and Laptev (~ 800 km 3 annually from the Lena River) seas that account for approximately one half of the total river runoff into the Arctic Ocean 1-3. Most of the continental runoff to the Kara and Laptev seas is discharged during ice-free period in June-September and forms sea-wide Ob-Yenisei and Lena river plumes which are among the largest freshwater reservoirs in the Arctic Ocean 4-6. River plumes are freshened surface-advected water masses, which seasonally form a relatively thin surface layer, compared to ambient saline sea. As a result, dynamics of river plumes is buoyancy-driven and wind-driven 7-12 , which is also true for large Ob-Yenisei and Lena plumes 3,13-18. It was previously investigated, that in the absence of strong wind forcing the Coriolis force and large salinity gradient between river plumes and ambient shelf water induce a baroclinic flow along the coast, which was previously addressed in many studies 7,19-21. This flow can be favored or impeded by local wind forcing. The associated eastward freshwater transport along large segments of northern shores of Eurasia and North America is an important part of large-scale freshwater transport pathways in the Arctic Ocean 22-27. Eastward alongshore spreading of the Ob-Yenisei and Lena plumes as a buoyancy-driven boundary current was described as a part of the Siberian Coastal Current (SCC) 22 which is the Eurasian branch of the Riverine Coastal Domain (RCD) 26. However, only few previous studies specifically addressed spreading of these river plumes from their source sea to an eastward sea, i.e., ...

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Section: Discussionmentioning

confidence: 99%

Freshwater transport between the Kara, Laptev, and East-Siberian seas

Osadchiev

Pisareva

Spivak

et al. 2020

Sci Rep

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“…If the Transpolar Drift acts as a source of Arctic Ocean shelf-derived micronutrients to the North Atlantic, dissolved Fe, dMn, dCo, dNi and dCu enrichment in Fram Strait should show a correlation with meteoric freshwater and ligand content similar to observations in the Central Arctic Ocean. For the calculation of meteoric freshwater contents, we use oxygen isotope measurements (δ 18 O) from GN05 (Meyer et al, 2021) with a freshwater reference δ 18 O value of −20‰ which is an average for riverine discharge to the Arctic Ocean shelves (Bauch et al, 2011;Dubinina et al, 2017). The δ 18 O measurements reveal an east-to-west gradient of meteoric freshwater contents in surface waters of Fram Strait (Figure S6 in Supporting Information S1).…”

Section: Siberian Shelf Sourcesmentioning

confidence: 99%

Arctic – Atlantic Exchange of the Dissolved Micronutrients Iron, Manganese, Cobalt, Nickel, Copper and Zinc With a Focus on Fram Strait

Krisch

Hopwood

Roig

et al. 2022

Global Biogeochemical Cycles

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The Arctic Ocean is considered a source of micronutrients to the Nordic Seas and the North Atlantic Ocean through the gateway of Fram Strait (FS). However, there is a paucity of trace element data from across the Arctic Ocean gateways, and so it remains unclear how Arctic and North Atlantic exchange shapes micronutrient availability in the two ocean basins. In 2015 and 2016, GEOTRACES cruises sampled the Barents Sea Opening (GN04, 2015) and FS (GN05, 2016) for dissolved iron (dFe), manganese (dMn), cobalt (dCo), nickel (dNi), copper (dCu) and zinc (dZn). Together with the most recent synopsis of Arctic-Atlantic volume fluxes, the observed trace element distributions suggest that FS is the most important gateway for Arctic-Atlantic dissolved micronutrient exchange as a consequence of Intermediate and Deep Water transport. Combining fluxes from FS and the Barents Sea Opening with estimates for Davis Strait (GN02, 2015) suggests an annual net southward flux of 2.7 ± 2.4 Gg•a −1 dFe, 0.3 ± 0.3 Gg•a −1 dCo, 15.0 ± 12.5 Gg•a −1 dNi and 14.2 ± 6.9 Gg•a −1 dCu from the Arctic toward the North Atlantic Ocean. Arctic-Atlantic exchange of dMn and dZn were more balanced, with a net southbound flux of 2.8 ± 4.7 Gg•a −1 dMn and a net northbound flux of 3.0 ± 7.3 Gg•a −1 dZn. Our results suggest that ongoing changes to shelf inputs and sea ice dynamics in the Arctic, especially in Siberian shelf regions, affect micronutrient availability in FS and the high latitude North Atlantic Ocean. Plain Language SummaryRecent studies have proposed that the Arctic Ocean is a source of micronutrients such as dissolved iron (dFe), manganese (dMn), cobalt (dCo), nickel (dNi), copper (dCu) and zinc (dZn) to the North Atlantic Ocean. However, data at the Arctic Ocean gateways including Fram Strait and the Barents Sea Opening have been missing to date and so the extent of Arctic micronutrient transport toward the Atlantic Ocean remains unquantified. Here, we show that Fram Strait is the most important gateway for Arctic-Atlantic micronutrient exchange which is a result of deep water transport at depths >500 m. Combined with a flux estimate for Davis Strait, this study suggests that the Arctic Ocean is a net source of dFe, dNi and dCu, and possibly also dCo, toward the North Atlantic Ocean. Arctic-Atlantic dMn and dZn exchange seems more balanced. Properties in the East Greenland Current showed substantial similarities to observations in the upstream Central Arctic Ocean, indicating that Fram Strait may export micronutrients from Siberian riverine discharge and shelf sediments >3,000 km away. Increasing Arctic river discharge, permafrost thaw and coastal erosion, all consequences of ongoing climate change, may therefore alter future Arctic Ocean micronutrient transport to the North Atlantic Ocean.

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“…High latitude regions have both the highest and lowest slopes in the data set (>0.5 and < 0.2). Sea ice melt and formation are implicated as key drivers of the δ 18 O sw ‐salinity relationships in these areas (Bauch et al., 2005, 2010; Dubinina et al., 2017; LeGrande & Schmidt, 2006). A sea ice signal may manifest in two parts: during formation, we expect large increases in salinity associated with brine exclusion (Rohling, 2013).…”

Section: Discussionmentioning

confidence: 99%

“…In both cases, we expect low slopes or slopes near zero as stable oxygen isotope fractionation between sea ice and water is very small, but salinity changes remain comparatively large, as seawater and sea ice salinities are often >10 PSU different. Large modifications in salinity may even lead to a decoupling of the δ 18 O sw ‐salinity correlation (Dubinina et al., 2017), where the range in salinity is so comparatively large compared to δ 18 O sw that there is no significant relationship. Low R 2 values in such high latitude regions may thus be due to sea ice related freshwater fluxes, leading to δ 18 O sw ‐salinity decoupling.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Solutions to Regional Surface Ocean δ¹⁸O‐Salinity Relationships for Paleoclimatic Reconstruction

Murray,

Muñoz,

Conroy

2023

Paleoceanog and Paleoclimatol

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Stable isotope – based reconstructions of past ocean salinity and hydroclimate depend on accurate, regionally constrained relationships between the stable oxygen isotopic composition of seawater (δ18Osw) and salinity in the surface ocean. An increasing number of δ18Osw observations suggest greater spatial variability in this relationship than previously considered, highlighting the need to reassess these relationships on a global scale. Here, we use available, paired δ18Osw and salinity data (N = 11,119) to create global interpolations of each variable. We then use a self organizing map, a specialized form of machine learning, to define 19 regions with unique δ18Osw – salinity relationships in the surface (< 50 m) ocean. Inclusion of atmospheric moisture‐related variables and oceanic tracer data in additional self‐organizing map experiments indicates global surface δ18Osw‐salinity spatial patterns are strongly forced by the atmosphere, as the SOM spatial output is highly similar despite no overlapping input data. Our approach is a useful update to the previously delimited regions, and highlights the utility of neural network pattern extraction in spatio‐temporally sparse datasets.

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Isotope (δD, δ18О) systematics in waters of the Russian Arctic seas

Cited by 21 publications

References 36 publications

Freshwater transport between the Kara, Laptev, and East-Siberian seas

Freshwater transport between the Kara, Laptev, and East-Siberian seas

Arctic – Atlantic Exchange of the Dissolved Micronutrients Iron, Manganese, Cobalt, Nickel, Copper and Zinc With a Focus on Fram Strait

Machine Learning Solutions to Regional Surface Ocean δ¹⁸O‐Salinity Relationships for Paleoclimatic Reconstruction

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Isotope (δD, δ18О) systematics in waters of the Russian Arctic seas

Cited by 21 publications

References 36 publications

Freshwater transport between the Kara, Laptev, and East-Siberian seas

Freshwater transport between the Kara, Laptev, and East-Siberian seas

Arctic – Atlantic Exchange of the Dissolved Micronutrients Iron, Manganese, Cobalt, Nickel, Copper and Zinc With a Focus on Fram Strait

Machine Learning Solutions to Regional Surface Ocean δ18O‐Salinity Relationships for Paleoclimatic Reconstruction

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Product

Resources

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Machine Learning Solutions to Regional Surface Ocean δ¹⁸O‐Salinity Relationships for Paleoclimatic Reconstruction