The Arctic Ocean as a dead end for floating plastics in the North Atlantic branch of the Thermohaline Circulation.

Mercury species export from the Arctic to the Atlantic Ocean

The Arctic Ocean is a fundamental node in the global hydrological cycle and the ocean's thermohaline circulation. We here assess the system's key functions and processes: (1) the delivery of fresh and low‐salinity waters to the Arctic Ocean by river inflow, net precipitation, distillation during the freeze/thaw cycle, and Pacific Ocean inflows; (2) the disposition (e.g., sources, pathways, and storage) of freshwater components within the Arctic Ocean; and (3) the release and export of freshwater components into the bordering convective domains of the North Atlantic. We then examine physical, chemical, or biological processes which are influenced or constrained by the local quantities and geochemical qualities of freshwater; these include stratification and vertical mixing, ocean heat flux, nutrient supply, primary production, ocean acidification, and biogeochemical cycling. Internal to the Arctic the joint effects of sea ice decline and hydrological cycle intensification have strengthened coupling between the ocean and the atmosphere (e.g., wind and ice drift stresses, solar radiation, and heat and moisture exchange), the bordering drainage basins (e.g., river discharge, sediment transport, and erosion), and terrestrial ecosystems (e.g., Arctic greening, dissolved and particulate carbon loading, and altered phenology of biotic components). External to the Arctic freshwater export acts as both a constraint to and a necessary ingredient for deep convection in the bordering subarctic gyres and thus affects the global thermohaline circulation. Geochemical fingerprints attained within the Arctic Ocean are likewise exported into the neighboring subarctic systems and beyond. Finally, we discuss observed and modeled functions and changes in this system on seasonal, annual, and decadal time scales and discuss mechanisms that link the marine system to atmospheric, terrestrial, and cryospheric systems.

Natural Fe-binding organic ligands in Fram Strait and over the northeast Greenland shelf

Releases of anthropogenic radionuclides from European nuclear fuel reprocessing plants enter the surface circulation of the high-latitude North Atlantic and are transported northward into the Arctic Ocean and southward from the Nordic Seas into the deep North Atlantic, thereby providing tracers of water circulation, mixing, ventilation, and deep-water formation. Early tracer studies focused on 137Cs, which revealed some of the first significant insights into the Arctic Ocean circulation, while more recent work has benefited from advances in accelerator mass spectrometry to enable the measurement of the conservative, long-lived radionuclide tracers 129I and 236U. The latest studies of these tracers, supported by simulations using the North Atlantic-Arctic Ocean-Sea Ice Model (NAOSIM) and enhanced by the use of transit time distributions to more precisely accommodate mixing, have provided a rich inventory of transport data for circulation in the Arctic and North Atlantic Oceans that are of great importance to global thermohaline circulation and climate.

Abstract. The North Atlantic north of 50∘ N is one of the most intense ocean sink areas for atmospheric CO2 considering the flux per unit area, 0.27 Pg-C yr−1, equivalent to −2.5 mol C m−2 yr−1. The northwest Atlantic Ocean is a region with high anthropogenic carbon inventories. This is on account of processes which sustain CO2 air–sea fluxes, in particular strong seasonal winds, ocean heat loss, deep convective mixing, and CO2 drawdown by primary production. The region is in the northern limb of the global thermohaline circulation, a path for the long-term deep-sea sequestration of carbon dioxide. The surface water masses in the North Atlantic are of contrasting origins and character, with the northward-flowing North Atlantic Drift, a Gulf Stream offspring, on the one hand and on the other hand the cold southward-moving low-salinity Polar and Arctic waters with signatures from Arctic freshwater sources. We have studied by observation the CO2 air–sea flux of the relevant water masses in the vicinity of Iceland in all seasons and in different years. Here we show that the highest ocean CO2 influx is to the Arctic and Polar waters, respectively, -3.8±0.4 and -4.4±0.3 mol C m−2 yr−1. These waters are CO2 undersaturated in all seasons. The Atlantic Water is a weak or neutral sink, near CO2 saturation, after poleward drift from subtropical latitudes. These characteristics of the three water masses are confirmed by data from observations covering 30 years. We relate the Polar Water and Arctic Water persistent undersaturation and CO2 influx to the excess alkalinity derived from Arctic sources. Carbonate chemistry equilibrium calculations clearly indicate that the excess alkalinity may support at least 0.058 Pg-C yr−1, a significant portion of the North Atlantic CO2 sink. The Arctic contribution to the North Atlantic CO2 sink which we reveal was previously unrecognized. However, we point out that there are gaps and conflicts in the knowledge about the Arctic alkalinity and carbonate budgets and that future trends in the North Atlantic CO2 sink are connected to developments in the rapidly warming and changing Arctic. The results we present need to be taken into consideration for the following question: will the North Atlantic continue to absorb CO2 in the future as it has in the past?

Trends in marine debris along the U.S. Pacific Coast and Hawai’i 1998–2007

Floating marine debris is ubiquitous in marine environments but knowledge about quantities in remote regions is still limited. Here, we present the results of an extensive survey of floating marine debris by experts, trained scientists from fields other than pollution or non-professional citizen scientists. A total of 276 visual ship-based surveys were conducted between 2015 and 2020 in the Northeast (NE) Atlantic from waters off the Iberian Peninsula to the Central Arctic, however, with a focus on Arctic waters. Spatiotemporal variations among regional seas (Central Arctic, Barents Sea, Greenland Sea, Norwegian Sea, North Sea) and oceanic regions (Arctic waters and the temperate NE Atlantic) were explored. The overall median debris concentration was 11 items km-2, with considerable variability. The median concentration was highest in the North Sea with 19 items km-2. The Nordic seas, except the Central Arctic showed median concentrations ranging from 9 to 13 items km-2. Plastic accounted for 91% of all floating items. Miscellaneous fragments, films, ropes and nets, packaging materials, expanded polystyrene and straps were the most frequently observed plastic types. Although the median debris concentration in the Central Arctic was zero, this region was not entirely free of floating debris. The variations between regional seas and oceanic regions were statistically not significant indicating a continuous supply by a northward transportation of floating debris. The data show a slight annual decrease and clear seasonal differences in debris concentrations with higher levels observed during summer. A correlation between debris concentrations and environmental and spatial variables was found, explaining partly the variability in the observations. Pollution levels were 500 times lower than those recorded on the seafloor indicating the seafloor as a sink for marine debris. The Arctic was characterised by similar pollution levels as regions in temperate latitudes highlighting that Arctic ecosystems face threats from plastic pollution, which add to the effects of rapid climate change.

Past numerical simulation studies found that debris loading from sand-sized particles may substantially affect tornado dynamics, causing reductions in near-surface wind speeds up to 50%. To further examine debris loading effects, simulations are performed using a large-eddy simulation model with a two-way drag force coupling between air and sand. Simulations encompass a large range of surface debris fluxes that cause negligible to substantial impact on tornado dynamics for a high-swirl tornado vortex simulation. Simulations are considered for a specific case with a single vortex flow type (swirl ratio, intensity, and translation velocity) and a fixed set of debris and aerodynamic parameters. Thus, it is stressed that these findings apply to the specific flow and debris parameters herein and would likely vary for different flows or debris parameters. For this specific case, initial surface debris fluxes are varied over a factor of 16 384, and debris cloud mass varies by only 42% of this range because a negative feedback reduces near-surface horizontal velocities. Debris loading effects on the axisymmetric mean flow are evident when maximum debris loading exceeds 0.1 kg kg−1, but instantaneous maximum wind speed and TKE exhibit small changes at smaller debris loadings (greater than 0.01 kg kg−1). Initially, wind speeds are reduced in a shallow, near-surface layer, but the magnitude and depth of these changes increases with higher debris loading. At high debris loading, near-surface horizontal wind speeds are reduced by 30%–60% in the lowest 10 m AGL. In moderate and high debris loading scenarios, the number and intensity of subvortices also decrease close to the surface.

The biogeographical analysis of the Barents Sea sponge fauna was undertaken on the basis of their modern distribution. Samples of sponges were collected in the Barents Sea during four annual multispecies trawl surveys (2003–2006) by the Knipovich Polar Research Institute of Marine Fisheries and Oceanography (PINRO) research vessels F. Nansen, Smolensk and Muklevich. Also, in 2019 fresh samples were collected during the benthic trawl survey by the PINRO research vessel F. Nansen. A total of 64 sponge species were studied. Among them, there was a large group of 24 (37.5% of the total number) boreal species – invaders from the North Atlantic, and their distribution in the Arctic Ocean is confined to the western Barents Sea. Since these species do not spread deep into the Arctic Ocean, they do not really affect the characteristics of the modern Arctic fauna. The second major component (24 species; 37.5%) of the Barents Sea sponge fauna (and the primary component of the modern Arctic fauna as a whole) is represented by Arctic endemics. A characteristic feature of some arctic sponges (endemics) is that there are pairs of morphologically and genetically close species inhabiting the North Atlantic. Their distributional ranges do not overlap significantly but are immediately adjacent to each other (vicariant species). The origin of vicariant species pairs among sponges inhabiting the Arctic and the adjoining North Atlantic was associated with glacial/interglacial cycles of the Quaternary, which drastically reorganised the boreal North Atlantic faunal elements that inhabited the Arctic Ocean in the Pliocene epoch. However, if we take a closer look not only at these species pairs but also at their close relatives inhabiting the North Atlantic, Arctic and North Pacific oceans, we see that they share the same roots as the North Pacific ones, and probably have evolved from the latter. The last species group, the arctic-boreal (16 species; 25%), is rather arbitrary and unified species of uncertain origin.

During a long period of its Cenozoic history, the Arctic Ocean was isolated from any global thermohaline circulation system. Thus, the opening and subsequent widening of the Fram Strait, the only deep-water connection between the Arctic and Atlantic oceans, was a fundamental tectonic process with extensive consequences for the global ocean circulation and paleoclimate evolution as well as for sedimentation processes in the adjacent ocean basins and along the continental margins.In order to reconstruct both the development of the ocean circulation within and the glacial history of the Arctic-Atlantic gateway we interpreted sediment packages imaged in reflection seismic profiles together with updated stratigraphic information from existing Ocean Drilling Program (ODP) holes. Our new, high resolution seismic stratigraphy for the Molloy Basin (central Fram Strait) is based on a revised chronology for ODP Site 909 and on reprocessed seismic reflection data with now better resolution than in previous studies.An improved core-log-seismic integration for ODP Site 909 and crossing seismic reflection profile AWI-20020300 was substantial in deriving the new seismic stratigraphy as well as characterizing the seismic units lithologically (Gruetzner et al., 2022). The core-seismic integration was combined with a revised magnetostratigraphy calibrated by new palynomorph bioevents which shifts previously used stratigraphies for ODP Site 909 (e.g. Myhre et al., 1995) to significantly younger ages in the time interval from c. 15 Ma to 3 Ma. The new stratigraphy implies that prominent maxima in coarse sand particles and kaolinite, often interpreted as evidence for ice rafting in the Fram Strait occur at c. 10.8 Ma, c. 3 Myr later as previously inferred. In the late Tortonian (< 7.5 Ma), sediment transport became current controlled, most probably through a western, recirculating branch of the West Spitsbergen Current. This current influence was strongly enhanced between c. 6.4 and 4.6 Ma and likely linked to the subsiding Hovgaard (Hovgård) Ridge and the widening of the AAG. Late Pliocene to Pleistocene seismic reflectors correlate with episodes of elevated ice-rafted detritus input related to major phases in Northern Hemisphere ice sheet growth such as the prominent glacial inception MIS M2 and the intensification of Northern Hemisphere glaciation starting at c. 2.7 Ma.Tracing the most prominent reflectors in a dense net (~5800 km) of re-processed seismic profiles allowed us to extrapolate these events into the western Boreas Basin and towards the adjacent Northeast Greenland continental margin. Subsequently compilations of updated digital isochron and depth-to-horizon maps were used to map depocenter geometries of current controlled sediments and mass-transport deposits within the western part of the Arctic-Atlantic gateway. ReferencesGruetzner, J., Matthiessen, J., Geissler, W.H., Gebhardt, A.C., Schreck, M. (2022). A revised core-seismic integration in the Molloy Basin (ODP Site 909): Implications for the history of ice rafting and ocean circulation in the Atlantic-Arctic gateway. Global and Planetary Change, 215, 103876.Myhre, A. M., Thiede, J., Firth, J. V., Ahagon, N., Black, K. S., Bloemendal, J., et al. (1995). Site 909. Proceedings of the Ocean Drilling Program, Part A: Initial Reports, 151, 159-220.

<p>The sharp decline of Arctic sea ice in recent decades has captured the attention of the climate science<br>community. A majority of climate analyses performed to date have used monthly or seasonal data. Here,<br>however, we analyze daily sea ice data for 1979–2016 using the self-organizing map (SOM) method to further<br>examine and quantify the contributions of atmospheric circulation changes to the melt-season Arctic sea ice<br>variability. Our results reveal two main variability modes: the Pacific sector mode and the Barents and Kara<br>Seas mode, which together explain about two-thirds of the melt-season Arctic sea ice variability and more<br>than 40% of its trend for the study period. The change in the frequencies of the two modes appears to be<br>associated with the phase shift of the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation<br>(AMO). The PDO and AMO trigger anomalous atmospheric circulations, in particular, the<br>Greenland high and the North Atlantic Oscillation and anomalous warm and cold air advections into the<br>Arctic Ocean. The changes in surface air temperature, lower-atmosphere moisture, and downwelling longwave<br>radiation associated with the advection are consistent with the melt-season sea ice anomalies observed<br>in various regions of the Arctic Ocean. These results help better understand the predictability of Arctic sea ice<br>on multiple (synoptic, intraseasonal, and interannual) time scales.</p>

The interannual and decadal variability of summer Arctic sea ice is analyzed, using the longest reconstruction (1850-2017) of Arctic sea ice extent available, and its relationship with the dominant internal variabilities of the climate system is further investigated quantitatively. The leading empirical orthogonal function (EOF) mode of summer Arctic sea ice variability captures an in-phase fluctuation over the Arctic Basin. The second mode characterizes a sea ice dipolar pattern with out-of-phase variability between the Pacific Arctic and the Atlantic Arctic. Summer sea ice variability is impacted by the major internal climate patterns: the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO) and Dipole Anomaly (DA), with descending order of importance based on the multiple regression analyses. The internal climate variability of the five teleconnection patterns accounts for up to 46% of the total variance in sea ice mode 1 (thermodynamical effect), and up to 30% of the total variance in mode 2 (dynamical effect). Furthermore, the variability of sea ice mode 1 decreased from 46% during 1953-2017 to 28% during 1979-2017, while the variability of mode 2 increased from 11% during 1953-2017 to 30% during 1979-2017. The increasingly greater reduction of Arctic summer sea ice during the recent four decades was enhanced with the positive ice/ocean albedo feedback loop being accelerated by the Arctic amplification, contributed in part by the atmospheric thermodynamical forcing from -AO, +NAO, +DA, +AMO, and –PDO and by the dynamical transpolar sea ice advection and outflow driven by +DA- and +AMO-derived strong anomalous meridional winds. Further analysis, using multiple large ensembles of climate simulations and single-forcing ensembles, indicates that the mode 1 of summer sea ice, dominated by the multidecadal oscillation, is partially a forced response to anthropogenic warming.

The sharp decline of Arctic sea ice in recent decades has captured the attention of the climate science community. A majority of climate analyses performed to date have used monthly or seasonal data. Here, however, we analyze daily sea ice data for 1979–2016 using the self-organizing map (SOM) method to further examine and quantify the contributions of atmospheric circulation changes to the melt-season Arctic sea ice variability. Our results reveal two main variability modes: the Pacific sector mode and the Barents and Kara Seas mode, which together explain about two-thirds of the melt-season Arctic sea ice variability and more than 40% of its trend for the study period. The change in the frequencies of the two modes appears to be associated with the phase shift of the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO). The PDO and AMO trigger anomalous atmospheric circulations, in particular, the Greenland high and the North Atlantic Oscillation and anomalous warm and cold air advections into the Arctic Ocean. The changes in surface air temperature, lower-atmosphere moisture, and downwelling longwave radiation associated with the advection are consistent with the melt-season sea ice anomalies observed in various regions of the Arctic Ocean. These results help better understand the predictability of Arctic sea ice on multiple (synoptic, intraseasonal, and interannual) time scales.

The Arctic Ocean has an important role in Earth's climate, both through surface processes such as sea-ice formation and transport, and through the production and export of waters at depth that contribute to the global thermohaline circulation. Deciphering the deep Arctic Ocean's palaeo-oceanographic history is a crucial part of understanding its role in climatic change. Here we show that sedimentary ratios of the radionuclides thorium-230 ((230)Th) and protactinium-231 ((231)Pa), which are produced in sea water and removed by particle scavenging on timescales of decades to centuries, respectively, record consistent evidence for the export of (231)Pa from the deep Arctic and may indicate continuous deep-water exchange between the Arctic and Atlantic oceans throughout the past 35,000 years. Seven well-dated box-core records provide a comprehensive overview of (231)Pa and (230)Th burial in Arctic sediments during glacial, deglacial and interglacial conditions. Sedimentary (231)Pa/(230)Th ratios decrease nearly linearly with increasing water depth above the core sites, indicating efficient particle scavenging in the upper water column and greater influence of removal by lateral transport at depth. Although the measured (230)Th burial is in balance with its production in Arctic sea water, integrated depth profiles for all time intervals reveal a deficit in (231)Pa burial that can be balanced only by lateral export in the water column. Because no enhanced sink for (231)Pa has yet been found in the Arctic, our records suggest that deep-water exchange through the Fram strait may export (231)Pa. Such export may have continued for the past 35,000 years, suggesting a century-scale replacement time for deep waters in the Arctic Ocean since the most recent glaciation and a persistent contribution of Arctic waters to the global ocean circulation.

The northern North Atlantic and Arctic oceans are morphologically and geologically complex. The constructive axial plate margin of the northern North Atlantic is propagating through Fram Strait, forming a young oceanic crust in the Nansen Basin of the Eurasian end of the deep water Arctic Ocean (Fig. 1). A complex transform along the continental margin of the Laptev Sea is the present termination of this Atlantic-Arctic Ocean spreading center. The North American end of the Arctic Ocean is floored by older oceanic crust carrying a thick sediment prism in the western end of the Canada Basin. The Barents Sea, like the other wide shallow water margins of the Asian Arctic Ocean and narrower continental shelf elsewhere around the Arctic margin, is an epicontinental sea (Eldholm & Talwani, 1977).KeywordsArctic OceanCanada BasinBottom Simulate ReflectorLomonosov RidgeAlpha RidgeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.