scholarly journals Biometry of Distephanus medianoctisol (Silicoflagellata) in the sea-ice covered environment of the central Arctic Ocean, summer 2004

10.5109/13527 ◽  
2009 ◽  
Vol 32 (2) ◽  
pp. 57-68
Author(s):  
Hideto Tsutsui ◽  
Kozo Takahashi
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Central Arctic Ocean

scholarly journals rRNA and rDNA based assessment of sea ice protist biodiversity from the central Arctic Ocean

2015 ◽  
Vol 51 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Anique Stecher ◽  
Stefan Neuhaus ◽  
Benjamin Lange ◽  
Stephan Frickenhaus ◽  
Bánk Beszteri ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Central Arctic Ocean

scholarly journals Photosynthetic production in the Central Arctic during the record sea-ice minimum in 2012

2015 ◽  
Vol 12 (3) ◽  
pp. 2897-2945 ◽  
Author(s):  
M. Fernández-Méndez ◽  
C. Katlein ◽  
B. Rabe ◽  
M. Nicolaus ◽  
I. Peeken ◽  
...  
Keyword(s):  
Sea Ice ◽  
Primary Production ◽  
Arctic Ocean ◽  
Water Column ◽  
Primary Productivity ◽  
Ice Cover ◽  
Annual Production ◽  
Ice Algae ◽  
Central Arctic Ocean ◽  
Eurasian Basin

Abstract. The ice-covered Central Arctic Ocean is characterized by low primary productivity due to light and nutrient limitations. The recent reduction in ice cover has the potential to substantially increase phytoplankton primary production, but little is yet known about the fate of the ice-associated primary production and of the nutrient supply with increasing warming. This study presents results from the Central Arctic Ocean collected during summer 2012, when sea-ice reached a minimum extent since the onset of satellite observations. Net primary productivity (NPP) was measured in the water column, sea ice and melt ponds by 14CO2 uptake at different irradiances. Photosynthesis vs. irradiance (PI) curves were established in laboratory experiments and used to upscale measured NPP to the deep Eurasian Basin (north of 78° N) using the irradiance-based Central Arctic Ocean Primary Productivity (CAOPP) model. In addition, new annual production was calculated from the seasonal nutrient drawdown in the mixed layer since last winter. Results show that ice algae can contribute up to 60% to primary production in the Central Arctic at the end of the season. The ice-covered water column has lower NPP rates than open water due to light limitation. As indicated by the nutrient ratios in the euphotic zone, nitrate was limiting primary production in the deep Eurasian Basin close to the Laptev Sea area, while silicate was the main limiting nutrient at the ice margin near the Atlantic inflow. Although sea-ice cover was substantially reduced in 2012, total annual new production in the Eurasian Basin was 17 ± 7 Tg C yr-1, which is within the range of estimates of previous years. However, when adding the contribution by sub-ice algae, the annual production for the deep Eurasian Basin (north of 78° N) could double previous estimates for that area with a surplus of 16 Tg C yr-1. Our data suggest that sub-ice algae are an important component of the ice-covered Central Arctic productivity. It remains an important question if their contribution to productivity is on the rise with thinning ice, or if it will decline due to overall sea-ice retreat and be replaced by phytoplankton.

scholarly journals Low-level jet characteristics over the Arctic Ocean in spring and summer

2013 ◽  
Vol 13 (1) ◽  
pp. 2125-2153
Author(s):  
L. Jakobson ◽  
T. Vihma ◽  
E. Jakobson ◽  
T. Palo ◽  
A. Männik ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Temperature Inversion ◽  
The Arctic ◽  
Jet Streams ◽  
Central Arctic Ocean ◽  
Turbulent Layer ◽  
Low Level ◽  
Low Level Jet ◽  
Jet Characteristics

Abstract. Low-level jets (LLJ) are important for turbulence in the stably stratified atmospheric boundary layer, but their occurrence, properties, and generation mechanisms in the Arctic are not well known. We analysed LLJs over the central Arctic Ocean in spring and summer 2007 on the bases of data collected in the drifting ice station Tara. Instead of traditional radiosonde soundings, data from tethersonde soundings with a high vertical resolution were used. The Tara results showed a lower occurrence of LLJs (46%) than many previous studies over polar sea ice. Strong jet core winds contributed to growth of the turbulent layer. Complex relationship between the jet core height and the temperature inversion top height were detected: substantial correlation (r = 0.72; p < 0.01) occurred when the jet core was above the turbulent layer, but inside the turbulent layer there was no correlation. The most important forcing mechanism for LLJs was baroclinicity, which was responsible for generation of strong and warm LLJs, which on average occurred at lower altitudes than other jets. Baroclinic jets were mostly associated to transient cyclones instead of the climatological air temperature gradients. Besides baroclinicity, cases related to inertial oscillations, gusts, and fronts were detected. In approximately 50% of the observed LLJs the generation mechanism remained unclear, but in most of these cases the wind speed was strong in the whole vertical profile, the jet core representing only a weak maximum. Further research needs on LLJs in the Arctic include investigation of low-level jet streams and their effects on the sea ice drift and atmospheric moisture transport.

scholarly journals Benefits of sea ice thickness initialization for the Arctic decadal climate prediction skill in EC-Earth3

2020 ◽  
Author(s):  
Tian Tian ◽  
Shuting Yang ◽  
Mehdi Pasha Karami ◽  
François Massonnet ◽  
Tim Kruschke ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Climate Prediction ◽  
Arctic Sea Ice ◽  
Prediction Skill ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Central Arctic Ocean ◽  
Ice Volume ◽  
Arctic Sea

Abstract. A substantial part of Arctic climate predictability at interannual time scales stems from the knowledge of the initial sea ice conditions. Among all the variables characterizing sea ice, sea ice volume, being a product of sea ice area/concentration (SIC) and thickness (SIT), is the most sensitive parameter for climate change. However, the majority of climate prediction systems are only assimilating the observed SIC due to lack of long-term reliable global observation of SIT. In this study the EC-Earth3 Climate Prediction System with anomaly initialization to ocean, SIC and SIT states is developed. In order to evaluate the benefits of specific initialized variables at regional scales, three sets of retrospective ensemble prediction experiments are performed with different initialization strategies: ocean-only; ocean plus SIC; and ocean plus SIC and SIT initialization. The increased skill from ocean plus SIC initialization is small in most regions, compared to ocean-only initialization. In the marginal ice zone covered by seasonal ice, skills regarding winter SIC are mainly gained from the initial ocean temperature anomalies. Consistent with previous studies, the Arctic sea ice volume anomalies are found to play a dominant role for the prediction skill of September Arctic sea ice extent. Winter preconditioning of SIT for the perennial ice in the central Arctic Ocean results in increased skill of SIC in the adjacent Arctic coastal waters (e.g. the Laptev/East Siberian/Chukchi Seas) for lead time up to a decade. This highlights the importance of initializing SIT for predictions of decadal time scale in regional Arctic sea ice. Our results suggest that as the climate warming continues and the central Arctic Ocean might become seasonal ice free in the future, the controlling mechanism for decadal predictability may thus shift from being the sea ice volume playing the major role to a more ocean-related processes.

scholarly journals Arctic sea ice anomalies during the MOSAiC winter 2019/20

2021 ◽  
Author(s):  
Klaus Dethloff ◽  
Wieslaw Maslowski ◽  
Stefan Hendricks ◽  
Younjoo Lee ◽  
Helge F. Goessling ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Barents Sea ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
The Arctic ◽  
Turbulent Heat ◽  
Central Arctic Ocean ◽  
Sea Ice Thickness ◽  
The Arctic Oscillation

Abstract. As the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project went into effect during the winter of 2019/2020, the Arctic Oscillation (AO) has experienced some of the largest shifts from a highly negative index in November 2019 to an extremely positive index during January-February-March (JFM) 2020. Here we analyse the sea ice thickness (SIT) distribution based on CryoSat-2/SMOS satellite data augmented with results from the hindcast simulation by the fully coupled Regional Arctic System Model (RASM) for the time period from November 2019 through March 2020. A notable result of the positive AO phase during JFM 2020 were large SIT anomalies, up to 1.3 m, which emerged in the Barents-Sea (BS), along the northeastern Canadian coast and in parts of the central Arctic Ocean. These anomalies appear to be driven by nonlinear interactions between thermodynamic and dynamic processes. In particular, in the Barents- and Kara Seas (BKS) they are a result of an enhanced ice growth connected with the colder temperature anomalies and the consequence of intensified atmospheric-driven sea ice transport and deformations (i.e. divergence and shear) in this area. Low-pressure anomalies, which developed over the Eastern Arctic during JFM 2020, increased northerly winds from the cold Arctic Ocean to the BS and accelerated the southward drift of the MOSAiC ice floe. The satellite-derived and model-simulated sea ice velocity anomalies, which compared well during JFM 2020, indicate a strong acceleration of the Transpolar Drift relative to the mean for the past decade, with intensified speeds up to 6 km/day. As a consequence, sea ice transport and deformations driven by atmospheric wind forcing accounted for bulk of SIT anomalies, especially in January and February 2020. The unusual AO shift and the related sea ice anomalies during the MOSAiC winter 2019/20 are within the range of simulated states in the forecast ensemble. RASM intra-annual ensemble forecast simulations, forced with different atmospheric boundary conditions from November 1, 2019 through April 30, 2020, show a pronounced internally generated variability in the sea ice volume. A comparison of the respective SIT distribution and turbulent heat fluxes during the positive AO phase in JFM 2020 and the negative AO phase in JFM 2010 further corroborates the conclusion, that winter sea ice conditions of the Arctic Ocean can be significantly altered by AO variability.

Sympagohydra tuuli (Cnidaria, Hydrozoa): first report from sea ice of the central Arctic Ocean and insights into histology, reproduction and locomotion

2009 ◽  
Vol 156 (4) ◽  
pp. 541-554 ◽  
Author(s):  
Stefan Siebert ◽  
Friederike Anton-Erxleben ◽  
Rainer Kiko ◽  
Maike Kramer
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Central Arctic Ocean ◽  
First Report

230Th-excess inventory and distribution in a southern Mendeleev Ridge core (Arctic Ocean): linkage with late Quaternary sedimentological and paleogeographical changes

2020 ◽  
Author(s):  
Tengfei Song ◽  
Claude Hillaire-Marcel ◽  
Yanguang Liu
Keyword(s):  
Grain Size ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Late Quaternary ◽  
Critical Time ◽  
Clay Mineralogy ◽  
Sedimentation Rates ◽  
Central Arctic Ocean ◽  
Sea Levels ◽  
Ice Production

&lt;p&gt;In addition to &lt;sup&gt;14&lt;/sup&gt;C-data, sedimentary excesses in &lt;sup&gt;230&lt;/sup&gt;Th &amp;#160;(&lt;sup&gt;230&lt;/sup&gt;Th&lt;sub&gt;xs&lt;/sub&gt;) in central Arctic Ocean cored sequences yielded critical time constrains and sedimentation rates estimates, at least, at sites characterized by very low sedimentation rates (&lt;&lt; 1cm/ka). Closer to the Russian margin, where higher accumulation rates are recorded based on &lt;sup&gt;14&lt;/sup&gt;C-ages, the setting of a reliable stratigraphy based on &lt;sup&gt;230&lt;/sup&gt;Th&lt;sub&gt;xs&lt;/sub&gt; reveals more challenging, as illustrated here, based on the analysis of &amp;#160;a gravity core raised from the southern Mendeleev Ridge (core ARC7-E25; -179.4&amp;#176;E, 79.0&amp;#176;N; 1200 m water depth; 320 cm long). Subsamples were collected at a 4 to 8 cm interval. Measurements included: AMS &lt;sup&gt;14&lt;/sup&gt;C in foraminifera, grain size, bulk Xray mineralogy, clay mineralogy, geochemistry (C&lt;sub&gt;org&lt;/sub&gt;, C&lt;sub&gt;inorg&lt;/sub&gt;,&lt;sup&gt;13&lt;/sup&gt;C&lt;sub&gt;org&lt;/sub&gt;, &lt;sup&gt;238&lt;/sup&gt;U, &lt;sup&gt;234&lt;/sup&gt;U, &lt;sup&gt;230&lt;/sup&gt;Th, &lt;sup&gt;226&lt;/sup&gt;Ra, &lt;sup&gt;210&lt;/sup&gt;Pb). Data indicate that some sediment were lost at core top. Nevertheless, &lt;sup&gt;14&lt;/sup&gt;C and &lt;sup&gt;230&lt;/sup&gt;Th&lt;sub&gt;xs &amp;#160;&lt;/sub&gt;data allow estimating a mean sedimentation rate of about 6 to 7 mm/ka during the last two climatic cycles. A comparison of the &lt;sup&gt;230&lt;/sup&gt;Th&lt;sub&gt;xs &lt;/sub&gt;inventory and distribution pattern with those from other cores allows identifying important parameters involved in the cycling of the water column-produced &lt;sup&gt;230&lt;/sup&gt;Th in this basin and its sporadic sedimentary accumulation, in particular linkages with sea-ice production over shelves, thus sea-levels, sea-ice rafting routes, grain-size and mineralogy, potential winnowing of fine fractions, role of brines and relative duration of intervals with reduced or nil sedimentation preceding &lt;sup&gt;230&lt;/sup&gt;Th&lt;sub&gt;xs&lt;/sub&gt;-accumulation intervals.&lt;/p&gt;

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