scholarly journals Microalgal community structure and primary production in Arctic and Antarctic sea ice: A synthesis

Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
Maria A. van Leeuwe ◽  
Letizia Tedesco ◽  
Kevin R. Arrigo ◽  
Philipp Assmy ◽  
Karley Campbell ◽  
...  
Keyword(s):  
Community Structure ◽  
Sea Ice ◽  
Climate Models ◽  
Ice Cores ◽  
The Arctic ◽  
Small Scale ◽  
Low Carbon ◽  
Bottom Communities ◽  
Biogeochemical Models ◽  
Microalgal Community

Sea ice is one the largest biomes on earth, yet it is poorly described by biogeochemical and climate models. In this paper, published and unpublished data on sympagic (ice-associated) algal biodiversity and productivity have been compiled from more than 300 sea-ice cores and organized into a systematic framework. Significant patterns in microalgal community structure emerged from this framework. Autotrophic flagellates characterize surface communities, interior communities consist of mixed microalgal populations and pennate diatoms dominate bottom communities. There is overlap between landfast and pack-ice communities, which supports the hypothesis that sympagic microalgae originate from the pelagic environment. Distribution in the Arctic is sometimes quite different compared to the Antarctic. This difference may be related to the time of sampling or lack of dedicated studies. Seasonality has a significant impact on species distribution, with a potentially greater role for flagellates and centric diatoms in early spring. The role of sea-ice algae in seeding pelagic blooms remains uncertain. Photosynthesis in sea ice is mainly controlled by environmental factors on a small scale and therefore cannot be linked to specific ice types. Overall, sea-ice communities show a high capacity for photoacclimation but low maximum productivity compared to pelagic phytoplankton. Low carbon assimilation rates probably result from adaptation to extreme conditions of reduced light and temperature in winter. We hypothesize that in the near future, bottom communities will develop earlier in the season and develop more biomass over a shorter period of time as light penetration increases due to the thinning of sea ice. The Arctic is already witnessing changes. The shift forward in time of the algal bloom can result in a mismatch in trophic relations, but the biogeochemical consequences are still hard to predict. With this paper we provide a number of parameters required to improve the reliability of sea-ice biogeochemical models.

scholarly journals Frost flower chemical signature in winter snow on Vestfonna ice cap, Nordaustlandet, Svalbard

2009 ◽  
Vol 3 (2) ◽  
pp. 147-154 ◽  
Author(s):  
E. Beaudon ◽  
J. Moore
Keyword(s):  
Sea Ice ◽  
Sea Water ◽  
Ice Cores ◽  
The Arctic ◽  
Small Scale ◽  
Snow Pack ◽  
Sulphate Content ◽  
Ice Cap ◽  
Winter Snow ◽  
Frost Flowers

Abstract. The chemistry of snow and ice cores from Svalbard is influenced by variations in local sea ice margin and distance to open water. Snow pits sampled at two summits of Vestfonna ice cap (Nordaustlandet, Svalbard), exhibit spatially heterogeneous soluble ions concentrations despite similar accumulation rates, reflecting the importance of small-scale weather patterns on this island ice cap. The snow pack on the western summit shows higher average values of marine ions and a winter snow layer that is relatively depleted in sulphate. One part of the winter snow pack exhibits a [SO42-/Na+] ratio reduced by two thirds compared with its ratio in sea water. This low sulphate content in winter snow is interpreted as the signature of frost flowers, which are formed on young sea ice when offshore winds predominate. Frost flowers have been described as the dominant source of sea salt to aerosol and precipitation in ice cores in coastal Antarctica but this is the first time their chemical signal has been described in the Arctic. The eastern summit does not show any frost flower signature and we interpret the unusually dynamic ice transport and rapid formation of thin ice on the Hinlopen Strait as the source of the frost flowers.

scholarly journals Frost flower chemical signature in winter snow on Vestfonna ice cap (Nordaustlandet, Svalbard)

2009 ◽  
Vol 3 (1) ◽  
pp. 159-180 ◽  
Author(s):  
E. Beaudon ◽  
J. Moore
Keyword(s):  
Sea Ice ◽  
Sea Water ◽  
Ice Cores ◽  
The Arctic ◽  
Small Scale ◽  
Snow Pack ◽  
Sulphate Content ◽  
Ice Cap ◽  
Winter Snow ◽  
Frost Flowers

Abstract. The chemistry of snow and ice cores from Svalbard is influenced by variations in local sea ice margin and distance to open water. Snow pits sampled at two summits of Vestfonna ice cap (Nordaustlandet, Svalbard), exhibit spatially heterogeneous soluble ions concentrations despite similar accumulation rates, reflecting the importance of small-scale weather patterns on this island ice cap. The snow pack on the western summit shows higher average values of marine species and a winter snow layer that is relatively depleted in sulphate. One part of the winter snow pack exhibits [SO42-/Na+] ratio reduced by two thirds compared with its ratio in sea water. This low sulphate content in winter snow is interpreted as the signature of frost flowers, which are formed on young sea ice when offshore winds predominate. Frost flowers have been described as the dominant source of sea salt to aerosol and precipitation in ice cores in coastal Antarctica but this is the first time their chemical signal has been described in the Arctic. The eastern summit does not show any frost flower signature and we interpret the unusually dynamic ice transport and rapid formation of thin ice on the Hinlopen Strait as the source of the frost flowers.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

scholarly journals Deep Learning Convolutional Neural Network Applying for the Arctic Acoustic Tomography Current Inversion Accuracy Improvement

2021 ◽  
Vol 9 (7) ◽  
pp. 755
Author(s):  
Kangkang Jin ◽  
Jian Xu ◽  
Zichen Wang ◽  
Can Lu ◽  
Long Fan ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Sea Ice ◽  
Convolutional Neural Network ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Small Scale ◽  
Acoustic Tomography ◽  
Arctic Sea ◽  
Current Inversion

Warm current has a strong impact on the melting of sea ice, so clarifying the current features plays a very important role in the Arctic sea ice coverage forecasting study field. Currently, Arctic acoustic tomography is the only feasible method for the large-range current measurement under the Arctic sea ice. Furthermore, affected by the high latitudes Coriolis force, small-scale variability greatly affects the accuracy of Arctic acoustic tomography. However, small-scale variability could not be measured by empirical parameters and resolved by Regularized Least Squares (RLS) in the inverse problem of Arctic acoustic tomography. In this paper, the convolutional neural network (CNN) is proposed to enhance the prediction accuracy in the Arctic, and especially, Gaussian noise is added to reflect the disturbance of the Arctic environment. First, we use the finite element method to build the background ocean model. Then, the deep learning CNN method constructs the non-linear mapping relationship between the acoustic data and the corresponding flow velocity. Finally, the simulation result shows that the deep learning convolutional neural network method being applied to Arctic acoustic tomography could achieve 45.87% accurate improvement than the common RLS method in the current inversion.

scholarly journals Genesis and Decay of Mesoscale Baroclinic Eddies in the Seasonally Ice-Covered Interior Arctic Ocean

2021 ◽  
Vol 51 (1) ◽  
pp. 115-129
Author(s):  
Gianluca Meneghello ◽  
John Marshall ◽  
Camille Lique ◽  
Pål Erik Isachsen ◽  
Edward Doddridge ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Seasonal Cycle ◽  
Climate Models ◽  
Baroclinic Instability ◽  
Temporal Distribution ◽  
Arctic Basin ◽  
Ocean Model ◽  
The Arctic ◽  
Origin And Evolution

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.

scholarly journals Clouds damp the radiative impacts of polar sea ice loss

2020 ◽  
Vol 14 (8) ◽  
pp. 2673-2686 ◽  
Author(s):  
Ramdane Alkama ◽  
Patrick C. Taylor ◽  
Lorea Garcia-San Martin ◽  
Herve Douville ◽  
Gregory Duveiller ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Surface Radiation ◽  
Radiation Budget ◽  
The Arctic ◽  
Cloud Properties ◽  
Surface Radiation Budget ◽  
Cloud Radiative Effect ◽  
Radiative Impact ◽  
The Impact

Abstract. Clouds play an important role in the climate system: (1) cooling Earth by reflecting incoming sunlight to space and (2) warming Earth by reducing thermal energy loss to space. Cloud radiative effects are especially important in polar regions and have the potential to significantly alter the impact of sea ice decline on the surface radiation budget. Using CERES (Clouds and the Earth's Radiant Energy System) data and 32 CMIP5 (Coupled Model Intercomparison Project) climate models, we quantify the influence of polar clouds on the radiative impact of polar sea ice variability. Our results show that the cloud short-wave cooling effect strongly influences the impact of sea ice variability on the surface radiation budget and does so in a counter-intuitive manner over the polar seas: years with less sea ice and a larger net surface radiative flux show a more negative cloud radiative effect. Our results indicate that 66±2% of this change in the net cloud radiative effect is due to the reduction in surface albedo and that the remaining 34±1 % is due to an increase in cloud cover and optical thickness. The overall cloud radiative damping effect is 56±2 % over the Antarctic and 47±3 % over the Arctic. Thus, present-day cloud properties significantly reduce the net radiative impact of sea ice loss on the Arctic and Antarctic surface radiation budgets. As a result, climate models must accurately represent present-day polar cloud properties in order to capture the surface radiation budget impact of polar sea ice loss and thus the surface albedo feedback.

scholarly journals Climate changes modulated the history of Arctic iodine during the Last Glacial Cycle

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Juan Pablo Corella ◽  
Niccolo Maffezzoli ◽  
Andrea Spolaor ◽  
Paul Vallelonga ◽  
Carlos A. Cuevas ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Radiative Forcing ◽  
Climate Changes ◽  
Ice Cores ◽  
The Arctic ◽  
Glacial Cycle ◽  
Ice Dynamics ◽  
Sea Ice Dynamics ◽  
Ultrafine Aerosol

AbstractIodine has a significant impact on promoting the formation of new ultrafine aerosol particles and accelerating tropospheric ozone loss, thereby affecting radiative forcing and climate. Therefore, understanding the long-term natural evolution of iodine, and its coupling with climate variability, is key to adequately assess its effect on climate on centennial to millennial timescales. Here, using two Greenland ice cores (NEEM and RECAP), we report the Arctic iodine variability during the last 127,000 years. We find the highest and lowest iodine levels recorded during interglacial and glacial periods, respectively, modulated by ocean bioproductivity and sea ice dynamics. Our sub-decadal resolution measurements reveal that high frequency iodine emission variability occurred in pace with Dansgaard/Oeschger events, highlighting the rapid Arctic ocean-ice-atmosphere iodine exchange response to abrupt climate changes. Finally, we discuss if iodine levels during past warmer-than-present climate phases can serve as analogues of future scenarios under an expected ice-free Arctic Ocean. We argue that the combination of natural biogenic ocean iodine release (boosted by ongoing Arctic warming and sea ice retreat) and anthropogenic ozone-induced iodine emissions may lead to a near future scenario with the highest iodine levels of the last 127,000 years.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

The role of sea ice for plastic pollution in the Arctic

2021 ◽  
Author(s):  
Ilka Peeken ◽  
Elisa Bergami ◽  
Ilaria Corsi ◽  
Benedikt Hufnagl ◽  
Christian Katlein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Long Range ◽  
Environmental Concern ◽  
Ice Cores ◽  
Atlantic Water ◽  
The Arctic ◽  
Polar Regions ◽  
Plastic Pollution ◽  
The Arctic Ocean

<p>Marine plastic pollution is a growing worldwide environmental concern as recent reports indicate that increasing quantities of litter disperse into secluded environments, including Polar Regions. Plastic degrades into smaller fragments under the influence of sunlight, temperature changes, mechanic abrasion and wave action resulting in small particles < 5mm called microplastics (MP). Sea ice cores, collected in the Arctic Ocean have so far revealed extremely high concentrations of very small microplastic particles, which might be transferred in the ecosystem with so far unknown consequences for the ice dependant marine food chain.  Sea ice has long been recognised as a transport vehicle for any contaminates entering the Arctic Ocean from various long range and local sources. The Fram Strait is hereby both, a major inflow gateway of warm Atlantic water, with any anthropogenic imprints and the major outflow region of sea ice originating from the Siberian shelves and carried via the Transpolar Drift. The studied sea ice revealed a unique footprint of microplastic pollution, which were related to different water masses and indicating different source regions. Climate change in the Arctic include loss of sea ice, therefore, large fractions of the embedded plastic particles might be released and have an impact on living systems. By combining modeling of sea ice origin and growth, MP particle trajectories in the water column as well as MPs long-range transport via particle tracking and transport models we get first insights  about the sources and pathways of MP in the Arctic Ocean and beyond and how this might affect the Arctic ecosystem.</p>

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