Advective pathways of nutrients and key ecological substances in the Arctic

Author(s):  
Myriel Vredenborg ◽  
Benjamin Rabe ◽  
Sinhue Torres-Valdès

<p>The Arctic Ocean is undergoing remarkable environmental changes due to global warming. The rise in the Arctic near-surface air temperature during the past decades is more than twice as high as the global average, a phenomenon known as the “Arctic Amplification”. As a consequence the Arctic summer sea ice extent has decreased by more than 40 % in recent decades, and moreover a year-round sea ice loss in extent and thickness was recorded. By opening up of large areas formerly covered by sea ice, the exchange of heat, moisture and momentum between the ocean and the atmosphere intensified. This resulted in changes in the ocean circulation and the water masses impacting the marine ecosystem. We investigate these changes by using a large set of hydrographic and biogeochemical data of the entire Arctic Ocean. To better quantify the current changes in the Arctic ecosystem we will compare our observational data analysis with high-resolution biogeochemical atmosphere-ice-ocean model simulations.</p>

2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.


2015 ◽  
Vol 28 (10) ◽  
pp. 4027-4033 ◽  
Author(s):  
Doo-Sun R. Park ◽  
Sukyoung Lee ◽  
Steven B. Feldstein

Abstract Wintertime Arctic sea ice extent has been declining since the late twentieth century, particularly over the Atlantic sector that encompasses the Barents–Kara Seas and Baffin Bay. This sea ice decline is attributable to various Arctic environmental changes, such as enhanced downward infrared (IR) radiation, preseason sea ice reduction, enhanced inflow of warm Atlantic water into the Arctic Ocean, and sea ice export. However, their relative contributions are uncertain. Utilizing ERA-Interim and satellite-based data, it is shown here that a positive trend of downward IR radiation accounts for nearly half of the sea ice concentration (SIC) decline during the 1979–2011 winter over the Atlantic sector. Furthermore, the study shows that the Arctic downward IR radiation increase is driven by horizontal atmospheric water flux and warm air advection into the Arctic, not by evaporation from the Arctic Ocean. These findings suggest that most of the winter SIC trends can be attributed to changes in the large-scale atmospheric circulations.


2018 ◽  
Vol 32 (1) ◽  
pp. 15-32 ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Sergey Danilov ◽  
Dmitry Sidorenko ◽  
Nikolay Koldunov ◽  
...  

Abstract The freshwater stored in the Arctic Ocean is an important component of the global climate system. Currently the Arctic liquid freshwater content (FWC) has reached a record high since the beginning of the last century. In this study we use numerical simulations to investigate the impact of sea ice decline on the Arctic liquid FWC and its spatial distribution. The global unstructured-mesh ocean general circulation model Finite Element Sea Ice–Ocean Model (FESOM) with 4.5-km horizontal resolution in the Arctic region is applied. The simulations show that sea ice decline increases the FWC by freshening the ocean through sea ice meltwater and modifies upper ocean circulation at the same time. The two effects together significantly increase the freshwater stored in the Amerasian basin and reduce its amount in the Eurasian basin. The salinification of the upper Eurasian basin is mainly caused by the reduction in the proportion of Pacific Water and the increase in that of Atlantic Water (AW). Consequently, the sea ice decline did not significantly contribute to the observed rapid increase in the Arctic total liquid FWC. However, the changes in the Arctic freshwater spatial distribution indicate that the influence of sea ice decline on the ocean environment is remarkable. Sea ice decline increases the amount of Barents Sea branch AW in the upper Arctic Ocean, thus reducing its supply to the deeper Arctic layers. This study suggests that all the dynamical processes sensitive to sea ice decline should be taken into account when understanding and predicting Arctic changes.


2021 ◽  
Vol 51 (1) ◽  
pp. 115-129
Author(s):  
Gianluca Meneghello ◽  
John Marshall ◽  
Camille Lique ◽  
Pål Erik Isachsen ◽  
Edward Doddridge ◽  
...  

AbstractObservations of ocean currents in the Arctic interior show a curious, and hitherto unexplained, vertical and temporal distribution of mesoscale activity. A marked seasonal cycle is found close to the surface: strong eddy activity during summer, observed from both satellites and moorings, is followed by very quiet winters. In contrast, subsurface eddies persist all year long within the deeper halocline and below. Informed by baroclinic instability analysis, we explore the origin and evolution of mesoscale eddies in the seasonally ice-covered interior Arctic Ocean. We find that the surface seasonal cycle is controlled by friction with sea ice, dissipating existing eddies and preventing the growth of new ones. In contrast, subsurface eddies, enabled by interior potential vorticity gradients and shielded by a strong stratification at a depth of approximately 50 m, can grow independently of the presence of sea ice. A high-resolution pan-Arctic ocean model confirms that the interior Arctic basin is baroclinically unstable all year long at depth. We address possible implications for the transport of water masses between the margins and the interior of the Arctic basin, and for climate models’ ability to capture the fundamental difference in mesoscale activity between ice-covered and ice-free regions.


2018 ◽  
Vol 44 (2) ◽  
pp. 659 ◽  
Author(s):  
M. Vázquez ◽  
R. Nieto ◽  
A. Drumond ◽  
L. Gimeno

The Arctic Ocean has suffered extreme reductions in sea ice in recent decades, and these observed changes suggest implications in terms of moisture transport. The Arctic region is a net sink of moisture in terms of the total hydrological cycle, however, its role as a moisture source for specific regions has not been extensively studied. Our results show that 80% of the moisture supply from the Arctic contributes to precipitation over itself, representing about 8% of the global moisture supply to the Arctic, the remaining 20% is distributed in the surrounding. A reduction in the sea ice extent could make the Arctic Ocean a slightly higher source of moisture to itself or to the surrounding areas. The analysis of the areas affected by Arctic moisture transport is important for establishing those areas vulnerable to change in a framework of a growing sea ice decline. To this end, the Lagrangian model FLEXPART was used in this work to establish the main sinks for the Arctic Ocean, focusing on the moisture transport from this region. The results suggest that most of the moisture loss occurs locally over the Arctic Ocean itself, especially in summer. Some moisture contribution from the Arctic Ocean to continental areas in North America and Eurasia is also noted in autumn and winter especially from Central Arctic, the East Siberian Sea, the Laptev, Kara, Barents, East Greenland and Bering Seas, and the Sea of Okhotsk.


2015 ◽  
Vol 72 (9) ◽  
pp. 2532-2538 ◽  
Author(s):  
Øystein Varpe ◽  
Malin Daase ◽  
Trond Kristiansen

Abstract A gigantic light experiment is taking place in the Arctic. Climate change has led to substantial reductions in sea ice extent and thickness in the Arctic Ocean. Sea ice, particularly when snow covered, acts as a lid hindering light to reach the waters underneath. Less ice will therefore mean more light entering the water column, with profound effects on pelagic and benthic ecosystems. Responses through primary production are so far well acknowledged. Here we argue that there is a need to broaden the view to include light-driven effects on fish, as they depend on light to locate prey. We used the Norwegian Earth System Model estimates of past and future sea ice area and thickness in the Arctic and applied attenuation coefficients for ice and snow to estimate light intensity. The results show a dramatic increase in the amount of light predicted to reach the future Arctic Ocean. We combined this insight with mechanistic understanding of how light modulates visual prey-detection and predict that fish will forage more efficiently as sea ice diminishes and that their populations will expand to higher latitudes, at least seasonally. Poleward shifts of boreal fish species have been predicted by many and to some extent observed, but a changing light environment has so far not been considered a driver. Expanding distributions and greater visual predation may restructure ecological relationships throughout the Arctic foodweb and lead to regime shifts. Research efforts should focus on the dynamics of how less sea ice will affect the feeding ecology and habitat usage of fish, particularly the northern limits of distributions. Mechanistic approaches to these topics offer insights beyond statistical correlations and extrapolations, and will help us understand how changing biophysical dynamics in the Arctic influence complex processes including production, predator–prey interactions, trait-evolution, and fisheries.


2015 ◽  
Vol 143 (6) ◽  
pp. 2363-2385 ◽  
Author(s):  
Keith M. Hines ◽  
David H. Bromwich ◽  
Lesheng Bai ◽  
Cecilia M. Bitz ◽  
Jordan G. Powers ◽  
...  

Abstract The Polar Weather Research and Forecasting Model (Polar WRF), a polar-optimized version of the WRF Model, is developed and made available to the community by Ohio State University’s Polar Meteorology Group (PMG) as a code supplement to the WRF release from the National Center for Atmospheric Research (NCAR). While annual NCAR official releases contain polar modifications, the PMG provides very recent updates to users. PMG supplement versions up to WRF version 3.4 include modified Noah land surface model sea ice representation, allowing the specification of variable sea ice thickness and snow depth over sea ice rather than the default 3-m thickness and 0.05-m snow depth. Starting with WRF V3.5, these options are implemented by NCAR into the standard WRF release. Gridded distributions of Arctic ice thickness and snow depth over sea ice have recently become available. Their impacts are tested with PMG’s WRF V3.5-based Polar WRF in two case studies. First, 20-km-resolution model results for January 1998 are compared with observations during the Surface Heat Budget of the Arctic Ocean project. Polar WRF using analyzed thickness and snow depth fields appears to simulate January 1998 slightly better than WRF without polar settings selected. Sensitivity tests show that the simulated impacts of realistic variability in sea ice thickness and snow depth on near-surface temperature is several degrees. The 40-km resolution simulations of a second case study covering Europe and the Arctic Ocean demonstrate remote impacts of Arctic sea ice thickness on midlatitude synoptic meteorology that develop within 2 weeks during a winter 2012 blocking event.


2017 ◽  
Author(s):  
Jun Ono ◽  
Hiroaki Tatebe ◽  
Yoshiki Komuro ◽  
Masato I. Nodzu ◽  
Masayoshi Ishii

Abstract. To assess the skill of predictions of the seasonal-to-interannual detrended sea ice extent in the Arctic Ocean (SIEAO) and to clarify the underlying physical processes, we conducted ensemble hindcasts, started on January 1st, April 1st, July 1st, and October 1st for each year from 1980 to 2011, for lead times of up three years, using the Model for Interdisciplinary Research on Climate (MIROC) version 5 initialized with the observed atmosphere and ocean anomalies and sea ice concentration. Significant skill is found for the winter months: the December SIEAO can be predicted up to 1 year ahead. This skill is attributed to the subsurface ocean heat content originating in the North Atlantic. The subsurface water flows into the Barents Sea from spring to fall and emerges at the surface in winter by vertical mixing, and eventually affects the sea ice variability there. Meanwhile, the September SIEAO predictions are skillful for lead times of up to 3 months, due to the persistence of sea ice in the Beaufort, Chukchi, and East Siberian Seas initialized in July, as suggested by previous studies.


2010 ◽  
Vol 10 (8) ◽  
pp. 18807-18878 ◽  
Author(s):  
S. J. Doherty ◽  
S. G. Warren ◽  
T. C. Grenfell ◽  
A. D. Clarke ◽  
R. E. Brandt

Abstract. Absorption of radiation by ice is extremely weak at visible and near-ultraviolet wavelengths, so small amounts of light-absorbing impurities in snow can dominate the absorption of solar radiation at these wavelengths, reducing the albedo relative to that of pure snow, contributing to the surface energy budget and leading to earlier snowmelt. In this study Arctic snow is surveyed for its content of light-absorbing impurities, expanding and updating the 1983–1984 survey of Clarke and Noone. Samples were collected in Alaska, Canada, Greenland, Svalbard, Norway, Russia, and the Arctic Ocean during 2005–2009, on tundra, glaciers, ice caps, sea ice, frozen lakes, and in boreal forests. Snow was collected mostly in spring, when the entire winter snowpack is accessible for sampling. Sampling was carried out in summer on the Greenland ice sheet and on the Arctic Ocean, of melting glacier snow and sea ice as well as cold snow. About 1200 snow samples have been analyzed for this study. The snow is melted and filtered; the filters are analyzed in a specially designed spectrophotometer system to infer the concentration of black carbon (BC), the fraction of absorption due to non-BC light-absorbing constituents and the absorption Ångstrom exponent of all particles. The reduction of snow albedo is primarily due to BC, but other impurities, principally brown (organic) carbon, are typically responsible for ~40% of the visible and ultraviolet absorption. The meltwater from selected snow samples was saved for chemical analysis to identify sources of the impurities. Median BC amounts in surface snow are as follows (nanograms of carbon per gram of snow): Greenland 3, Arctic Ocean snow 7, melting sea ice 8, Arctic Canada 8, Subarctic Canada 14, Svalbard 13, Northern Norway 21, Western Arctic Russia 26, Northeastern Siberia 17. Concentrations are more variable in the European Arctic than in Arctic Canada or the Arctic Ocean, probably because of the proximity to BC sources. Individual samples of falling snow were collected on Svalbard, documenting the springtime decline of BC from March through May. Absorption Ångstrom exponents are 1.5–1.7 in Norway, Svalbard, and Western Russia, 2.1–2.3 elsewhere in the Arctic, and 2.5 in Greenland. Correspondingly, the estimated contribution to absorption by non-BC constituents in these regions is ~25%, 40%, and 50%, respectively. It has been hypothesized that when the snow surface layer melts some of the BC is left at the top of the snowpack rather than being carried away in meltwater. This process was observed in a few locations and would cause a positive feedback on snowmelt. The BC content of the Arctic atmosphere has declined markedly since 1989, according to the continuous measurements of near-surface air at Alert (Canada), Barrow (Alaska), and Ny-Ålesund (Svalbard). Correspondingly, the new BC concentrations for Arctic snow are somewhat lower than those reported by Clarke and Noone for 1983–1984, but because of methodological differences it is not clear that the differences are significant.


2020 ◽  
Vol 37 (8) ◽  
pp. 1477-1495 ◽  
Author(s):  
An T. Nguyen ◽  
Patrick Heimbach ◽  
Vikram V. Garg ◽  
Victor Ocaña ◽  
Craig Lee ◽  
...  

AbstractThe lack of continuous spatial and temporal sampling of hydrographic measurements in large parts of the Arctic Ocean remains a major obstacle for quantifying mean state and variability of the Arctic Ocean circulation. This shortcoming motivates an assessment of the utility of Argo-type floats, the challenges of deploying such floats due to the presence of sea ice, and the implications of extended times of no surfacing on hydrographic inferences. Within the framework of an Arctic coupled ocean–sea ice state estimate that is constrained to available satellite and in situ observations, we establish metrics for quantifying the usefulness of such floats. The likelihood of float surfacing strongly correlates with the annual sea ice minimum cover. Within the float lifetime of 4–5 years, surfacing frequency ranges from 10–100 days in seasonally sea ice–covered regions to 1–3 years in multiyear sea ice–covered regions. The longer the float drifts under ice without surfacing, the larger the uncertainty in its position, which translates into larger uncertainties in hydrographic measurements. Below the mixed layer, especially in the western Arctic, normalized errors remain below 1, suggesting that measurements along a path whose only known positions are the beginning and end points can help constrain numerical models and reduce hydrographic uncertainties. The error assessment presented is a first step in the development of quantitative methods for guiding the design of observing networks. These results can and should be used to inform a float network design with suggested locations of float deployment and associated expected hydrographic uncertainties.


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