scholarly journals The polar night shift: seasonal dynamics and drivers of Arctic Ocean microbiomes revealed by autonomous sampling

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Matthias Wietz ◽  
Christina Bienhold ◽  
Katja Metfies ◽  
Sinhué Torres-Valdés ◽  
Wilken-Jon von Appen ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Mixed Layer Depth ◽  
Night Shift ◽  
Ice Cover ◽  
The Arctic ◽  
Nutrient Concentrations ◽  
Polar Night ◽  
Degrading Bacteria ◽  
The Arctic Ocean ◽  
Chemoautotrophic Bacteria

AbstractThe Arctic Ocean features extreme seasonal differences in daylight, temperature, ice cover, and mixed layer depth. However, the diversity and ecology of microbes across these contrasting environmental conditions remain enigmatic. Here, using autonomous samplers and sensors deployed at two mooring sites, we portray an annual cycle of microbial diversity, nutrient concentrations and physical oceanography in the major hydrographic regimes of the Fram Strait. The ice-free West Spitsbergen Current displayed a marked separation into a productive summer (dominated by diatoms and carbohydrate-degrading bacteria) and regenerative winter state (dominated by heterotrophic Syndiniales, radiolarians, chemoautotrophic bacteria, and archaea). The autumn post-bloom with maximal nutrient depletion featured Coscinodiscophyceae, Rhodobacteraceae (e.g. Amylibacter) and the SAR116 clade. Winter replenishment of nitrate, silicate and phosphate, linked to vertical mixing and a unique microbiome that included Magnetospiraceae and Dadabacteriales, fueled the following phytoplankton bloom. The spring-summer succession of Phaeocystis, Grammonema and Thalassiosira coincided with ephemeral peaks of Aurantivirga, Formosa, Polaribacter and NS lineages, indicating metabolic relationships. In the East Greenland Current, deeper sampling depth, ice cover and polar water masses concurred with weaker seasonality and a stronger heterotrophic signature. The ice-related winter microbiome comprised Bacillaria, Naviculales, Polarella, Chrysophyceae and Flavobacterium ASVs. Low ice cover and advection of Atlantic Water coincided with diminished abundances of chemoautotrophic bacteria while others such as Phaeocystis increased, suggesting that Atlantification alters microbiome structure and eventually the biological carbon pump. These insights promote the understanding of microbial seasonality and polar night ecology in the Arctic Ocean, a region severely affected by climate change.

scholarly journals The Polar Night Shift: Annual Dynamics and Drivers of Microbial Community Structure in the Arctic Ocean

2021 ◽  
Author(s):  
Matthias Wietz ◽  
Christina Bienhold ◽  
Katja Metfies ◽  
Sinhue Torres-Valdes ◽  
Wilken-Jon von Appen ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Night Shift ◽  
Ice Cover ◽  
Atlantic Water ◽  
The Arctic ◽  
Polar Night ◽  
Phytoplankton Diversity ◽  
Degrading Bacteria ◽  
The Arctic Ocean ◽  
Chemoautotrophic Bacteria

Change is a constant in the Arctic Ocean, with extreme seasonal differences in daylight, ice cover and temperature. The biodiversity and ecology of marine microbes across these extremes remain poorly understood. Here, using an array of autonomous samplers and sensors, we portray an annual cycle of microbial biodiversity, nutrient budgets and oceanography in the major biomes of the Fram Strait. In the ice-free West Spitsbergen Current, community turnover followed the solar cycle, with distinct separation of a productive summer state dominated by diatoms and carbohydrate-degrading bacteria, and a regenerative winter state dominated by heterotrophic Syndiniales, radiolarians, chemoautotrophic bacteria and archaea. Winter mixing of the water column replenishing nitrate, phosphate and silicate, and the onset of light were the major turning points. The summer succession of Phaeocystis, Grammonema and Thalassiosira coincided with ephemeral peaks of Formosa, Polaribacter and NS clades, indicating metabolic relationships between phytoplankton and bacteria. In the East Greenland Current, ice cover and greater sampling depth coincided with weaker seasonality, featuring weaker bloom/decay events and an ice-related winter microbiome. Low ice cover and advection of Atlantic Water coincided with diminished abundances of chemoautotrophic bacteria while Phaeocystis and Flavobacteriaceae increased, suggesting that Atlantification alters phytoplankton diversity and the biological carbon pump. Our findings promote the understanding of microbial seasonality in Arctic waters, illustrating the ecological importance of the polar night and providing an essential baseline of microbial dynamics in a region severely affected by climate change.

scholarly journals Changes in the Arctic Ocean carbon cycle with diminishing ice cover

2020 ◽  
Author(s):  
Michael D. DeGrandpre ◽  
Wiley Evans ◽  
Mary-Louise Timmermans ◽  
Richard A. Krishfield ◽  
William J Williams ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Arctic Ocean ◽  
Ice Cover ◽  
The Arctic ◽  
Ocean Carbon Cycle ◽  
The Arctic Ocean ◽  
Ocean Carbon

Increasing Multiyear Sea Ice Loss in the Beaufort Sea: A New Export Pathway for the Diminishing Multiyear Ice Cover of the Arctic Ocean

2021 ◽  
Author(s):  
David Gareth Babb ◽  
Ryan J. Galley ◽  
Stephen E. L. Howell ◽  
Jack Christopher Landy ◽  
Julienne Christine Stroeve ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Beaufort Sea ◽  
Ice Cover ◽  
The Arctic ◽  
Export Pathway ◽  
The Arctic Ocean ◽  
Multiyear Ice

scholarly journals Nautical electronic maps of S-411 standard and their suitability in navigation for assessment of ice cover condition of the Arctic Ocean

2016 ◽  
Vol 48 (1) ◽  
pp. 17-28 ◽  
Author(s):  
Tadeusz Pastusiak
Keyword(s):  
Arctic Ocean ◽  
Ice Cover ◽  
Research Process ◽  
Data Sources ◽  
The Arctic ◽  
Quality Of Data ◽  
Vector Maps ◽  
The Arctic Ocean ◽  
Wide Availability

Abstract The research on the ice cover of waterways, rivers, lakes, seas and oceans by satellite remote sensing methods began at the end of the twentieth century. There was a lot of data sources in diverse file formats. It has not yet carried out a comparative assessment of their usefulness. A synthetic indicator of the quality of data sources binding maps resolution, file publication, time delay and the functionality for the user was developed in the research process. It reflects well a usefulness of maps and allows to compare them. Qualitative differences of map content have relatively little impact on the overall assessment of the data sources. Resolution of map is generally acceptable. Actuality has the greatest impact on the map content quality for the current vessel’s voyage planning in ice. The highest quality of all studied sources have the regional maps in GIF format issued by the NWS / NOAA, general maps of the Arctic Ocean in NetCDF format issued by the OSI SAF and the general maps of the Arctic Ocean in GRIB-2 format issued by the NCEP / NOAA. Among them are maps containing information on the quality of presented parameter. The leader among the map containing all three of the basic characteristics of ice cover (ice concentration, ice thickness and ice floe size) are vector maps in GML format. They are the new standard of electronic vector maps for the navigation of ships in ice. Publishing of ice cover maps in the standard electronic map format S-411 for navigation of vessels in ice adopted by the International Hydrographic Organization is advisable in case is planned to launch commercial navigation on the lagoons, rivers and canals. The wide availability of and exchange of information on the state of ice cover on rivers, lakes, estuaries and bays, which are used exclusively for water sports, ice sports and ice fishing is possible using handheld mobile phones, smartphones and tablets.

scholarly journals Impact of Variable Atmospheric and Oceanic Form Drag on Simulations of Arctic Sea Ice*

2014 ◽  
Vol 44 (5) ◽  
pp. 1329-1353 ◽  
Author(s):  
Michel Tsamados ◽  
Daniel L. Feltham ◽  
David Schroeder ◽  
Daniela Flocco ◽  
Sinead L. Farrell ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Form Drag ◽  
Drag Coefficients ◽  
Arctic Sea ◽  
The Arctic Ocean ◽  
Range Of Values

Abstract Over Arctic sea ice, pressure ridges and floe and melt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air–ice and ice–ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air–ice and ocean–ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.

Fracture of the ice cover on the Arctic Ocean

2010 ◽  
pp. 361-390
Author(s):  
Erland M. Schulson ◽  
Paul Duval
Keyword(s):  
Arctic Ocean ◽  
Ice Cover ◽  
The Arctic ◽  
The Arctic Ocean

scholarly journals Incorporation of satellite-derived thin-ice data into a global OGCM simulation

2019 ◽  
Vol 53 (11) ◽  
pp. 7113-7130
Author(s):  
Takahiro Toyoda ◽  
Katsushi Iwamoto ◽  
L. Shogo Urakawa ◽  
Hiroyuki Tsujino ◽  
Hideyuki Nakano ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Model Simulation ◽  
Mixed Layer Depth ◽  
The Arctic ◽  
Sea Ice Thickness ◽  
Ice Volume ◽  
The Arctic Ocean ◽  
Polar Ocean ◽  
Ice Production

Abstract The presence of thin sea ice is indicative of active freezing conditions in the polar ocean. We propose a simple yet effective method to incorporate information of thin-ice category into coupled ocean–sea-ice model simulations. In our approach, the thin-ice distribution restricts thick-ice extent and constrains atmosphere–ocean heat exchange through the sea ice. Our model simulation with the incorporation of satellite-derived thin-ice data for the Arctic Ocean showed much improved representation of sea-ice and upper-ocean fields, including sea-ice thickness in the Canadian Archipelago and the region north of Greenland, mixed-layer depth over the Central Arctic, and surface-layer salinity over the open ocean. Enhanced sea-ice production by the thin-ice data constraint increased the total sea-ice volume of the Arctic Ocean by $$5 \times 10^{3}$$ 5 × 10 3 –$$10 \times 10^{3}$$ 10 × 10 3  km3. Subsequent sea-ice melting was also enhanced, leading to the greater amplitude of the seasonal cycle by approximately $$2 \times 10^{3}$$ 2 × 10 3  km3 (15% of the baseline value from the experiment without the thin-ice data incorporation). Overall, our results demonstrate that the incorporation of satellite-derived information on thin sea ice has great potential for the improvement of coupled ocean–sea-ice simulations.

scholarly journals Arctic sea-ice area and volume production:1996/97 versus 1997/98

2002 ◽  
Vol 34 ◽  
pp. 447-453 ◽  
Author(s):  
Ron Kwok
Keyword(s):  
Arctic Ocean ◽  
Large Scale ◽  
Heat Budget ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Volume Production ◽  
Area And Volume

AbstractThe RADARSAT geophysical processor system (RGPS) produces measurements of ice motion and estimates of ice thickness using repeat synthetic aperture radar maps of the Arctic Ocean. From the RGPS products, we compute the net deformation and advection of the winter ice cover using the motion observations, and the seasonal ice area and volume production using the estimates of ice thickness. The results from the winters of 1996/97 and 1997/98 are compared. The second winter is of particular interest because it coincides with the Surface Heat Budget of the Arctic Ocean (SHEBA) field program. The character of the deformation of the ice cover from the two years is very different. Over a domain covering a large part of the western Arctic Ocean (~2.5 × 106 km2), the net divergence of that area during the 6 months of the first winter was 2.7% and for the second winter was 49.3%. In a subregion where the SHEBA camp was located, the net divergence was almost 38% compared to a net divergence of the same subregion of ~9% in 1996/97. The resulting deformation created a much larger volume of seasonal ice than in the earlier year. The net seasonal ice-volume production is 1.6 times (0.38 m vs 0.62 m) that of the first year. In addition to the larger divergence, this part of the ice cover advected a longer distance toward the Chukchi Sea over the same time-span. The total coverage of multi-year ice remained almost identical at ~2.08 × 106 km2, or 83% of the initial area of the domain. In this paper, we compare the behavior of the ice cover over the two winters and discuss these observations in the context of large-scale ice motion and atmospheric-pressure pattern.

Growth of Wave Height with Retreating Ice Cover in the Arctic

2020 ◽  
Author(s):  
Changlong Guan ◽  
Jingkai Li
Keyword(s):  
Arctic Ocean ◽  
Surface Waves ◽  
Wave Height ◽  
Open Water ◽  
Ice Cover ◽  
Wave Climate ◽  
Least Square ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Wave Heights

<p>For the Arctic surface waves, one of the most uncontroversial viewpoints is that their escalation in the past few years is mainly caused by the ice extent reduction. Ice retreat enlarges the open water area, i.e., the effective fetch, and thus allows more wind input energy and available distance for wave evolution. This knowledge has been supported by a few previous studies on the Arctic waves which analyzed the correlation between time-series variations in wave height and ice coverage. However, from the perspective of space, the detailed relationship between retreating ice cover and increasing surface waves is not well studied. Hence, we performed such a study for the whole Arctic and its subregions, which will be helpful for a better understanding of the wave climate and for forecasting waves in the Arctic Ocean.</p><p>Wave data are produced by twelve-year (2007-2018) hindcasts of summer melt seasons (May-Sept.) and numerical tests with WAVEWATCH III. When a viscoelastic wave-ice model and a spherical multiple-cell grid are applied, simulated wave heights agree with available buoy data and previous research. After the validations, simulated significant wave heights over twelve-year summer melt seasons are used to demonstrate the detailed relationship between the escalation of wave height and reduction of ice extent for the whole Arctic and seven subregions. Through least square regression, we find that the mean wave height in the Arctic Ocean will increase by 0.071m (10<sup>6</sup>km<sup>2</sup>)<sup>-1</sup> when the ice extent is smaller than 9.4×10<sup>6</sup>km<sup>2</sup>, and roughly 51% is contributed by the enlarged fetch. By analyzing the nondimensional wave energy and comparing the simulated wave height with Wilson IV, we prove the swell is widespread during the summertime in the current Arctic Ocean. Furthermore, we also display the variations in probabilities of occurrence of large waves as ice-edge retreats in seven subregions. Assuming that an ice free period occurs in the Arctic in September, the model results show that the simulated mean wave height is approximately 1.6m and the large waves occur much more frequently, which mean that the growth rate of wave height will be higher if the minimum ice extent keeps reducing in the future.</p>

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