65 research outputs found

    Structure and forcing of the overflow at the Storfjorden sill and its connection to the Arctic coastal polynya in Storfjorden

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    Storfjorden (Svalbard) is a sill-fjord with an active polynya and exemplifies the dense water formation process over the Arctic shelves. Here we report on our simulations of Storfjorden covering the freezing season of 1999–2000 using an eddy-permitting 3-D ocean circulation model with a fully coupled dynamic and thermodynamic sea-ice model. The model results in the polynya region and of the dense water plume flowing over the sill crest are compared to observations. The connections of the overflow at the sill to the dense water production at the polynya and to the local wind forcing are investigated. Both the overflow and the polynya dynamics are found to be sensitive to wind forcing. In response to freezing and brine rejection over the polynya, the buoyancy forcing initiates an abrupt positive density anomaly. While the ocean integrates the buoyancy forcing over several polynya events (about 25 days), the wind forcing dominates the overflow response at the sill at weather scale. In the model, the density excess is diluted in the basin and leads to a gradual build-up of dense water behind the sill. The overflow transport is typically inferred from observations using a single current profiler at the sill crest. Despite the significant variability of the plume width, we show that a constant overflow width of 15 km produces realistic estimates of the overflow volume transport. Another difficulty in monitoring the overflow is measuring the plume thickness in the absence of hydrographic profiles. Volume flux estimates assuming a constant plume width and the thickness inferred from velocity profiles explain 58% of the modelled overflow volume flux variance and agrees to within 10% when averaged over the overflow season

    Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends

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    Sea ice volume has decreased in the last decades, evoked by changes in sea ice area and thickness. Estimates of sea ice area and thickness rely on a number of geophysical parameters which introduce large uncertainties. To quantify these uncertainties we use freeboard retrievals from ICESat and investigate different assumptions about snow depth, sea ice density and area. We find that uncertainties in ice area are of minor importance for the estimates of sea ice volume during the cold season in the Arctic basin. The choice of mean ice density used when converting sea ice freeboard into thickness mainly influences the resulting mean sea ice thickness, while snow depth on top of the ice is the main driver for the year-to-year variability, particularly in late winter. The absolute uncertainty in the mean sea ice thickness is 0.28 m in February/March and 0.21 m in October/November. The uncertainty in snow depth contributes up to 70% of the total uncertainty and the ice density 30–35%, with higher values in October/November. We find large uncertainties in the total sea ice volume and trend. The mean total sea ice volume is 10 120 ± 1280 km<sup>3</sup> in October/November and 13 250 ± 1860 km<sup>3</sup> in February/March for the time period 2005–2007. Based on these uncertainties we obtain trends in sea ice volume of &minus;1450 ± 530 km<sup>3</sup> a<sup>&minus;1</sup> in October/November and &minus;880 ± 260 km<sup>3</sup> a<sup>&minus;1</sup> in February/March over the ICESat period (2003–2008). Our results indicate that, taking into account the uncertainties, the decline in sea ice volume in the Arctic between the ICESat (2003–2008) and CryoSat-2 (2010–2012) periods may have been less dramatic than reported in previous studies. However, more work and validation is required to quantify these changes and analyse possible unresolved biases in the freeboard retrievals

    Heat in the Barents Sea: transport, storage, and surface fluxes

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    A column model is set up for the Barents Sea to explore sensitivity of surface fluxes and heat storage from varying ocean heat transport. Mean monthly ocean transport and atmospheric forcing are synthesised and force the simulations. Results show that by using updated ocean transports of heat and freshwater the vertical mean hydrographic seasonal cycle can be reproduced fairly well. &lt;br&gt;&lt;br&gt; Our results indicate that the ~70 TW of heat transported to the Barents Sea by ocean currents is lost in the southern Barents Sea as latent, sensible, and long wave radiation, each contributing 23–39 TW to the total heat loss. Solar radiation adds 26 TW in the south, as there is no significant ice production. &lt;br&gt;&lt;br&gt; The northern Barents Sea receives little ocean heat transport. This leads to a mixed layer at the freezing point during winter and significant ice production. There is little net surface heat loss annually in the north. The balance is achieved by a heat loss through long wave radiation all year, removing most of the summer solar heating. &lt;br&gt;&lt;br&gt; During the last decade the Barents Sea has experienced an atmospheric warming and an increased ocean heat transport. The Barents Sea responds to such large changes by adjusting temperature and heat loss. Decreasing the ocean heat transport below 50 TW starts a transition towards Arctic conditions. The heat loss in the Barents Sea depend on the effective area for cooling, and an increased heat transport leads to a spreading of warm water further north

    Loss of sea ice during winter north of Svalbard

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    Sea ice loss in the Arctic Ocean has up to now been strongest during summer. In contrast, the sea ice concentration north of Svalbard has experienced a larger decline during winter since 1979. The trend in winter ice area loss is close to 10% per decade, and concurrent with a 0.3°C per decade warming of the Atlantic Water entering the Arctic Ocean in this region. Simultaneously, there has been a 2°C per decade warming of winter mean surface air temperature north of Svalbard, which is 20–45% higher than observations on the west coast. Generally, the ice edge north of Svalbard has retreated towards the northeast, along the Atlantic Water pathway. By making reasonable assumptions about the Atlantic Water volume and associated heat transport, we show that the extra oceanic heat brought into the region is likely to have caused the sea ice loss. The reduced sea ice cover leads to more oceanic heat transferred to the atmosphere, suggesting that part of the atmospheric warming is driven by larger open water area. In contrast to significant trends in sea ice concentration, Atlantic Water temperature and air temperature, there is no significant temporal trend in the local winds. Thus, winds have not caused the long-term warming or sea ice loss. However, the dominant winds transport sea ice from the Arctic Ocean into the region north of Svalbard, and the local wind has influence on the year-to-year variability of the ice concentration, which correlates with surface air temperatures, ocean temperatures, as well as the local wind

    Kvasir-Capsule, a video capsule endoscopy dataset

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    Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work demonstrates the promising benefits of AI-based computer-assisted diagnosis systems for VCE. They also show great potential for improvements to achieve even better results. Also, medical data is often sparse and unavailable to the research community, and qualified medical personnel rarely have time for the tedious labelling work. We present Kvasir-Capsule, a large VCE dataset collected from examinations at a Norwegian Hospital. Kvasir-Capsule consists of 117 videos which can be used to extract a total of 4,741,504 image frames. We have labelled and medically verified 47,238 frames with a bounding box around findings from 14 different classes. In addition to these labelled images, there are 4,694,266 unlabelled frames included in the dataset. The Kvasir-Capsule dataset can play a valuable role in developing better algorithms in order to reach true potential of VCE technology

    Supercooled Southern Ocean waters

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    In cold polar waters, temperatures sometimes drop below the freezing point, a process referred to as supercooling. However, observational challenges in polar regions limit our understanding of the spatial and temporal extent of this phenomenon. We here provide observational evidence that supercooled waters are much more widespread in the seasonally ice-covered Southern Ocean than previously reported. In 5.8% of all analyzed hydrographic profiles south of 55°S, we find temperatures below the surface freezing point (“potential” supercooling), and half of these have temperatures below the local freezing point (“in situ” supercooling). Their occurrence doubles when neglecting measurement uncertainties. We attribute deep coastal-ocean supercooling to melting of Antarctic ice shelves and surface-induced supercooling in the seasonal sea-ice region to wintertime sea-ice formation. The latter supercooling type can extend down to the permanent pycnocline due to convective sinking plumes—an important mechanism for vertical tracer transport and water-mass structure in the polar ocean

    Potential climatic transitions with profound impact on Europe

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    We discuss potential transitions of six climatic subsystems with large-scale impact on Europe, sometimes denoted as tipping elements. These are the ice sheets on Greenland and West Antarctica, the Atlantic thermohaline circulation, Arctic sea ice, Alpine glaciers and northern hemisphere stratospheric ozone. Each system is represented by co-authors actively publishing in the corresponding field. For each subsystem we summarize the mechanism of a potential transition in a warmer climate along with its impact on Europe and assess the likelihood for such a transition based on published scientific literature. As a summary, the ‘tipping’ potential for each system is provided as a function of global mean temperature increase which required some subjective interpretation of scientific facts by the authors and should be considered as a snapshot of our current understanding. <br/

    Effects of Hydrographic Variability on the Spatial, Seasonal and Diel Diving Patterns of Southern Elephant Seals in the Eastern Weddell Sea

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    Weddell Sea hydrography and circulation is driven by influx of Circumpolar Deep Water (CDW) from the Antarctic Circumpolar Current (ACC) at its eastern margin. Entrainment and upwelling of this high-nutrient, oxygen-depleted water mass within the Weddell Gyre also supports the mesopelagic ecosystem within the gyre and the rich benthic community along the Antarctic shelf. We used Conductivity-Temperature-Depth Satellite Relay Data Loggers (CTD-SRDLs) to examine the importance of hydrographic variability, ice cover and season on the movements and diving behavior of southern elephant seals in the eastern Weddell Sea region during their overwinter feeding trips from Bouvetøya. We developed a model describing diving depth as a function of local time of day to account for diel variation in diving behavior. Seals feeding in pelagic ice-free waters during the summer months displayed clear diel variation, with daytime dives reaching 500-1500 m and night-time targeting of the subsurface temperature and salinity maxima characteristic of CDW around 150–300 meters. This pattern was especially clear in the Weddell Cold and Warm Regimes within the gyre, occurred in the ACC, but was absent at the Dronning Maud Land shelf region where seals fed benthically. Diel variation was almost absent in pelagic feeding areas covered by winter sea ice, where seals targeted deep layers around 500–700 meters. Thus, elephant seals appear to switch between feeding strategies when moving between oceanic regimes or in response to seasonal environmental conditions. While they are on the shelf, they exploit the locally-rich benthic ecosystem, while diel patterns in pelagic waters in summer are probably a response to strong vertical migration patterns within the copepod-based pelagic food web. Behavioral flexibility that permits such switching between different feeding strategies may have important consequences regarding the potential for southern elephant seals to adapt to variability or systematic changes in their environment resulting from climate change
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