scholarly journals Effect of compressive loading on first-year sea-ice permeability

2018 ◽  
Vol 64 (245) ◽  
pp. 443-449 ◽  
Author(s):  
CARL E. RENSHAW ◽  
ALEKSEY MARCHENKO ◽  
ERLAND M. SCHULSON ◽  
EVGENY KARULIN
Keyword(s):  
Sea Ice ◽  
Inelastic Deformation ◽  
Volume Fraction ◽  
Compressive Loading ◽  
First Year ◽  
Brine Volume ◽  
Salinity Water ◽  
Flow Pathways ◽  
The Impact ◽  
Mechanisms Of Deformation

ABSTRACTThe permeability of sea ice can strongly affect the dissipation of wave energy into the ice pack. Sea-ice permeability is known to be impacted by the brine volume fraction and the blockage of flow pathways by the freezing of infiltrating lower salinity water. Here we investigate another process impacting sea-ice permeability, namely, inelastic deformation. We report the results of a first-of-its-kind field-scale deformation experiment to investigate the impact of compressive loading on sea-ice permeability. We observed that deformation decreased permeability by four orders of magnitude or more in some locations, while elsewhere permeability was unaffected or possibly increased. We show that the observed changes in permeability are consistent with expected changes in stress state and, as a result, in the mechanisms of deformation.

scholarly journals Impedance measurements of the complex dielectric permittivity of sea ice at 50 MHz: pore microstructure and potential for salinity monitoring

2009 ◽  
Vol 55 (189) ◽  
pp. 81-94 ◽  
Author(s):  
Daniel Pringle ◽  
Guy Dubuis ◽  
Hajo Eicken
Keyword(s):  
Dielectric Permittivity ◽  
Sea Ice ◽  
Volume Fraction ◽  
Temperature Cycling ◽  
Complex Dielectric Permittivity ◽  
First Year ◽  
Impedance Measurements ◽  
Brine Volume ◽  
Microstructure Measurements ◽  
Inclusion Length

AbstractWe report impedance measurements of the complex dielectric permittivity ε = ε′ − jε″ of sea ice and laboratory-grown NaCl single crystals using 50 MHz Stevens Water Monitoring Systems Hydra Probes. Temperature cycling of the single-crystal samples shows hydrohalite precipitation, and hysteresis in ε′ and ε″ qualitatively consistent with the expected evolution of brine-inclusion microstructure. Measurements parallel and perpendicular to intra-crystalline brine layers show weak (<10%) anisotropy in ε′ and a 20–40% difference in ε″ due to enhanced d.c. conductivity along the layers. Measurements in landfast, first-year ice near Barrow, Alaska, USA, indicate brine motion in warming ice as the brine volume fraction vb increases above 5%. Plots of vb derived from salinity profiles against ε′ and ε″ for these and previous measurements display too much variability between datasets for unguided inversion of vb. Contributing to this variability are intrinsic microstructural dependence, uncertainties in vb, and sub-representative sample volumes. A standard model of sea-ice permittivity is inverted to derive the apparent brine-inclusion aspect ratio and bulk d.c. conductivity at a spatial scale complementary to previous measurements. We assess Hydra Probe performance in high-salinity environments and conclude that they are not generally suited for autonomous sea-ice salinity measurements, partly due to the range of relevant brine pocket inclusion length scales.

scholarly journals Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance

2019 ◽  
Vol 11 (4) ◽  
pp. 417 ◽  
Author(s):  
John Yackel ◽  
Torsten Geldsetzer ◽  
Mallik Mahmud ◽  
Vishnu Nandan ◽  
Stephen Howell ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Winter Season ◽  
Late Winter ◽  
First Year ◽  
Snow Layer ◽  
Independent Case ◽  
Brine Volume ◽  
Snow Thickness

Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness.

Convolutional Neural Networks for Classification of Sea Ice Types in Sentinel-1 SAR Data

2021 ◽  
Author(s):  
Anton Korosov ◽  
Hugo Boulze ◽  
Julien Brajard
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Classification Accuracy ◽  
Thermal Noise ◽  
Noise Removal ◽  
The Arctic ◽  
First Year ◽  
Sar Data ◽  
The Impact

&lt;p&gt;A new algorithm for classification of sea ice types on Sentinel-1 Synthetic Aperture Radar (SAR) data using a convolutional neural network (CNN) is presented.&amp;#160; The CNN is trained on reference ice charts produced by human experts and compared with an existing machine learning algorithm based on texture features and random forest classifier. The CNN is trained on a dataset from winter 2020 for retrieval of four classes: ice free, young ice, first-year ice and old ice. The accuracy of our classification is 91.6%. The error is a bit higher for young ice (76%) and first-year ice (84%). Our algorithm outperforms the existing random forest product for each ice type. It has also proved to be more efficient in computing time and less sensitive to the noise in SAR data.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Our study demonstrates that CNN can be successfully applied for classification of sea ice types in SAR data. The algorithm is applied in small sub-images extracted from a SAR image after preprocessing including thermal noise removal. Validation shows that the errors are mostly attributed to coarse resolution of ice charts or misclassification of training data by human experts.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Several sensitivity experiments were conducted for testing the impact of CNN architecture, hyperparameters, training parameters and data preprocessing on accuracy. It was shown that a CNN with three convolutional layers, two max-pool layers and three hidden dense layers can be applied to a sub-image with size 50 x 50 pixels for achieving the best results. It was also shown that a CNN can be applied to SAR data without thermal noise removal on the preprocessing step. Understandably, the classification accuracy decreases to 89% but remains reasonable.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The main advantages of the new algorithm are the ability to classify several ice types, higher classification accuracy for each ice type and higher speed of processing than in the previous studies. The relative simplicity of the algorithm (both texture analysis and classification are performed by CNN) is also a benefit. In addition to providing ice type labels, the algorithm also derives the probability of belonging to a class. Uncertainty of the method can be derived from these probabilities and used in the assimilation of ice type in numerical models.&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;br&gt;Given the high accuracy and processing speed, the CNN-based algorithm is included in the Copernicus Marine Environment Monitoring Service (CMEMS) for operational sea ice type retrieval for generating ice charts in the Arctic Ocean. It is already released as an open source software and available on Github: https://github.com/nansencenter/s1_icetype_cnn.&lt;/p&gt;

scholarly journals Using under-ice hyperspectral transmittance to determine land-fast sea-ice algal biomass in Saroma-ko Lagoon, Hokkaido, Japan

2020 ◽  
pp. 1-10
Author(s):  
Pat Wongpan ◽  
Daiki Nomura ◽  
Takenobu Toyota ◽  
Tomonori Tanikawa ◽  
Klaus M. Meiners ◽  
...  
Keyword(s):  
Sea Ice ◽  
Algal Biomass ◽  
Volume Fraction ◽  
Ice Core ◽  
Optical Measurements ◽  
The Arctic ◽  
Algal Communities ◽  
Empirical Relations ◽  
Brine Volume ◽  
Biomass Variability

Abstract Sea ice, which forms in polar and nonpolar areas, transmits light to ice-associated (sympagic) algal communities. To noninvasively study the distribution of sea-ice algae, empirical relations to estimate its biomass from under-ice hyperspectral irradiance have been developed in the Arctic and Antarctica but lack for nonpolar regions. This study examines relationships between normalised difference indices (NDI) calculated from hyperspectral transmittance and sympagic algal biomass in the nonpolar Saroma-ko Lagoon. We analysed physico-biogeochemical properties of snow and land-fast sea ice supporting 27 paired bio-optical measurements along three transects covering an area of over 250 m × 250 m in February 2019. Snow depth (0.08 ± 0.01 m) and ice-bottom brine volume fraction (0.21 ± 0.02) showed low (0.06) and high (0.58) correlations with sea-ice core bottom section chlorophyll a (Chl. a), respectively. Spatial analyses unveiled the patch size of sea-ice Chl. a to be ~65 m, which is in the same range reported from previous studies. A selected NDI (669, 596 nm) explained 63% of algal biomass variability. This reflects the bio-optical properties and environmental conditions of the lagoon that favour the wavelength pair in the orange/red part of the spectrum and suggests the necessity of a specific bio-optical relationship for Saroma-ko Lagoon.

scholarly journals Imaging air volume fraction in sea ice using non-destructive X-ray tomography

2016 ◽  
Vol 10 (3) ◽  
pp. 1125-1145 ◽  
Author(s):  
Odile Crabeck ◽  
Ryan Galley ◽  
Bruno Delille ◽  
Brent Else ◽  
Nicolas-Xavier Geilfus ◽  
...  
Keyword(s):  
Sea Ice ◽  
Volume Fraction ◽  
Gas Bubbles ◽  
Internal Layers ◽  
X Ray ◽  
Air Volume ◽  
Air Interface ◽  
Saturation Factor ◽  
Brine Volume ◽  
Non Destructive

Abstract. Although the presence of a gas phase in sea ice creates the potential for gas exchange with the atmosphere, the distribution of gas bubbles and transport of gases within the sea ice are still poorly understood. Currently no straightforward technique exists to measure the vertical distribution of air volume fraction in sea ice. Here, we present a new fast and non-destructive X-ray computed tomography technique to quantify the air volume fraction and produce separate images of air volume inclusions in sea ice. The technique was performed on relatively thin (4–22 cm) sea ice collected from an experimental ice tank. While most of the internal layers showed air volume fractions  <  2 %, the ice–air interface (top 2 cm) systematically showed values up to 5 %. We suggest that the air volume fraction is a function of both the bulk ice gas saturation factor and the brine volume fraction. We differentiate micro bubbles (Ø  <  1 mm), large bubbles (1 mm  <  Ø  <  5 mm) and macro bubbles (Ø  >  5 mm). While micro bubbles were the most abundant type of gas bubbles, most of the air porosity observed resulted from the presence of large and macro bubbles. The ice texture (granular and columnar) as well as the permeability state of ice are important factors controlling the air volume fraction. The technique developed is suited for studies related to gas transport and bubble migration.

scholarly journals Retrieval and parametrisation of sea-ice bulk density from airborne multi-sensor measurements

2021 ◽  
Author(s):  
Arttu Jutila ◽  
Stefan Hendricks ◽  
Robert Ricker ◽  
Luisa von Albedyll ◽  
Thomas Krumpen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Bulk Density ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
First Year ◽  
Exponential Relationship ◽  
Sea Ice Thickness ◽  
Abstract Knowledge ◽  
Negative Exponential ◽  
The Impact

Abstract. Knowledge of sea-ice thickness and volume depends on freeboard observations from satellite altimeters and in turn on information of snow mass and sea-ice density required for the freeboard-to-thickness conversion. These parameters, especially sea-ice density, are usually based on climatologies constructed from in situ observations made in the 1980s and before while contemporary and representative measurements are lacking. Our aim with this paper is to derive updated sea-ice bulk density estimates suitable for the present Arctic sea-ice cover and a range of ice types to reduce uncertainties in sea-ice thickness remote sensing. Our sea-ice density measurements are based on over 3000 km of high-resolution collocated airborne sea-ice and snow thickness and freeboard measurements in 2017 and 2019. Sea-ice bulk density is derived assuming isostatic equilibrium for different ice types. Our results show higher average bulk densities for both first-year ice (FYI) and especially multi-year ice (MYI) compared to previous studies. In addition, we find a small difference between deformed and possibly unconsolidated FYI and younger MYI. We find a negative-exponential relationship between sea-ice bulk density and sea-ice freeboard and apply this parametrisation to one winter of monthly gridded CryoSat-2 sea-ice freeboard data. We discuss the suitability and the impact of the derived FYI and MYI bulk densities for sea-ice thickness retrievals and the uncertainty related to the indirect method of measuring sea-ice bulk density. The results suggest that retrieval algorithms be adapted to changes in sea-ice density and highlight the need of future studies to evaluate the impact of density parametrisation on the full sea-ice thickness data record.

scholarly journals Long-term Time-series of Arctic Tropospheric BrO derived from UV-VIS Satellite Remote Sensing and its Relation to First Year Sea Ice

2020 ◽  
Author(s):  
Ilias Bougoudis ◽  
Anne-Marlene Blechschmidt ◽  
Andreas Richter ◽  
Sora Seo ◽  
John Philip Burrows ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ice Age ◽  
The Arctic ◽  
First Year ◽  
Arctic Amplification ◽  
Vertical Column ◽  
The Impact ◽  
Good Agreement

Abstract. Arctic Amplification describes the rapid increase of the air temperature in the past three decades in the Arctic, which impacts on physicochemical conditions, the ecosystem and biogeochemistry. Every polar spring, the BrO explosion, a series of chemical reactions that release bromine molecules to the troposphere occurs over sea ice covered regions. This autocatalytic mechanism depletes boundary layer and tropospheric ozone, thereby changes the oxidizing capacity of the atmosphere and facilitates the deposition of metals (e.g. Hg). In this study, we present a 22 year consolidated and consistent tropospheric BrO dataset, derived from four different UV-VIS satellite instruments and investigate the BrO evolution under the impact of Arctic Amplification. The retrieval data products from the different sensors are compared during periods of overlap and show good agreement. By studying the sensor merged time-series of tropospheric BrO vertical column densities, we find an increase in the magnitude of BrO explosion events under the impact of Arctic Amplification with an upward trend of about 1.5 % per year. Furthermore, the areas where BrO plumes frequently appear have changed, extending over larger regions in the Arctic during more recent years. Comparison to sea ice age data suggests that the reported changes in tropospheric BrO are linked in a complex way to the increase of first-year ice extent in the Arctic.

scholarly journals Investigations on physical and textural properties of Arctic first-year sea ice in the Amundsen Gulf, Canada, November 2007–June 2008 (IPY-CFL system study)

2013 ◽  
Vol 59 (217) ◽  
pp. 819-837 ◽  
Author(s):  
Gauthier Carnat ◽  
Timothy Papakyriakou ◽  
N.X. Geilfus ◽  
Frédéric Brabant ◽  
B. Delille ◽  
...  
Keyword(s):  
Sea Ice ◽  
Volume Fraction ◽  
Time Window ◽  
Textural Properties ◽  
Small Time ◽  
First Year ◽  
System Study ◽  
International Polar Year ◽  
Amundsen Gulf ◽  
Platelet Ice

AbstractWe report sea-ice temperature and bulk salinity measurements as well as textural analysis from 33 first-year drift- and fast-ice stations sampled between November 2007 and June 2008 in the southern Beaufort Sea–Amundsen Gulf, Canadian Arctic, during the International Polar Year Circumpolar Flaw Lead (IPY-CFL) system study. We use this significant dataset to investigate the halo-thermodynamic evolution of sea ice from growth to melt. A strong desalination phase is observed over a small time window in the spring. Using calculated proxies of sea-ice permeability (brine volume fraction) and of the intensity of brine convection (Rayleigh number) we demonstrate that this phase corresponds to full-depth gravity drainage initiated by a restored connectivity of the brine network with warming in the spring. Most stations had a textural sequence typical of Arctic first-year ice, with granular ice overlying columnar ice. Unusual textural features were observed sporadically: sandwiched granular ice, platelet ice and draped platelet ice. We suggest that turbulence in leads and double diffusion in strong brine plumes following the refreeze of cracks are plausible mechanisms for the formation of these textures.

scholarly journals Non-linear thermal transport and brine convection in first-year sea ice

1998 ◽  
Vol 27 ◽  
pp. 471-476 ◽  
Author(s):  
M.J. Mcguinness ◽  
H.J. Trodahl ◽  
K. Collins ◽  
T. G. Haskell
Keyword(s):  
Thermal Conductivity ◽  
Sea Ice ◽  
First Year ◽  
Antarctic Sea Ice ◽  
Brine Migration ◽  
Non Linear ◽  
First Results ◽  
Higher Temperature ◽  
Set Up ◽  
The Impact

We report the first results from a programme recently set up to directly measure the thermal conductivity of young sea ice. An array of thermistors frozen into first-year Antarctic sea ice provides temperature vs depth data, which is fitted directly with a partial differential equation for heat conduction. Temperatures are recorded every hour at 20 vertical intervals of 100 mm over a period of 5 months, allowing accurate and direct estimation of the thermal conductivity. Preliminary results indicate that the thermal conductivity is in the expected range, with some evidence of non-linear effects deeper in the ice. A larger variance in data is evident at higher temperature gradients and at greater depths in the ice. Preliminary modelling of the impact of brine migration on heat transport through first-year sea ice is presented. Diffusion-driven brine pocket migration is too slow to contribute significantly to heat flow, but the convective instability of inclined brine slots or tubes is a promising mechanism.

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