A Subice Suction Corer for Sampling Epontic Ice Algae

1988 ◽  
Vol 45 (3) ◽  
pp. 562-568 ◽  
Author(s):  
Harold E. Welch ◽  
Martin A. Bergmann ◽  
John K. Jorgenson ◽  
William Burton
Keyword(s):  
Sea Ice ◽  
Quantitative Assessment ◽  
Early Spring ◽  
Late Winter ◽  
First Year ◽  
Ice Algae ◽  
Sources Of Error

Standard SIPRE coring was compared with a new Subice Suction Corer and cores taken by diver for the quantitative assessment of epontic (subice) algae on first-year congelation sea ice at Resolute, N.W.T., Canada (≈75°N). The diver cores were probably most accurate but were slow and costly. SIPRE coring was as good as other techniques in late winter and early spring but gave progressively poorer (under) estimates as the season progressed, with up to 90% of the ice algae being lost from SIPRE cores by June. The Subice Suction Corer was fast, easy to operate, cheap, and gave results comparable with samples obtained by diving. Sources of error are discussed.

scholarly journals A Comparison of Decimeter Scale Variations of Physical and Photobiological Parameters in a Late Winter First-Year Sea Ice in Southwest Greenland

2021 ◽  
Vol 9 (1) ◽  
pp. 60
Author(s):  
Lars Chresten Lund-Hansen ◽  
Clara Marie Petersen ◽  
Dorte Haubjerg Søgaard ◽  
Brian Keith Sorrell
Keyword(s):  
Sea Ice ◽  
Ice Cores ◽  
Biological Properties ◽  
Early Spring ◽  
Small Scale ◽  
Late Winter ◽  
First Year ◽  
Chl A ◽  
Bulk Salinity ◽  
Southwest Greenland

Small-scale variation in the physical and biological properties of sea ice was examined by collecting nine sea ice cores within 1 m2 in a land-fast first-year ice in southwest Greenland in late winter. Cores were sectioned in four segments and sea ice physical, biological, and photobiological parameters were measured. The main purpose was to explore the decimeter-scale horizontal and vertical variations in common sea ice parameters. ANOVA analyses revealed significant within-core variations for bulk salinity, brine salinity, brine volume, gas volume, chlorophyll a (Chl a), and the maximum light-limited photosynthetic efficiency (α). Only temperature and bulk salinity variations were significant between cores, and no significant variations were found within or between cores for other photobiological parameters. Power analyses were applied to determine the number of replicates needed to achieve a significance at p < 0.05 with sufficient power, and showed a minimum of four and preferably five replicate cores to detect the observed variability in this first-year ice. It is emphasized that these results only apply to this type of first-year ice in late winter/early spring, and that different variations may apply to other types of ice.

scholarly journals Arctic sea-ice albedo derived from RGPS-based ice-thickness estimates

2001 ◽  
Vol 33 ◽  
pp. 225-229 ◽  
Author(s):  
R.W. Lindsay
Keyword(s):  
Sea Ice ◽  
Empirical Relationship ◽  
Early Spring ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
First Year ◽  
Large Set ◽  
Radar Images ◽  
Arctic Sea

AbstractThe RADARSAT geophysical processor system (RGPS) uses sequential synthetic aperture radar images of Arctic sea ice taken every 3 days to track a large set of Lagrangian points over the winter and spring seasons. The points are the vertices of cells, which are initially square and 10 km on a side, and the changes in the area of these cells due to opening and closing of the ice are used to estimate the fractional area of a set of first-year ice categories. The thickness of each category is estimated by the RGPS from an empirical relationship between ice thickness and the freezing degree-days since the formation of the ice. With a parameterization of the albedo based on the ice thickness, the albedo may be estimated from the first-year ice distribution. We compute the albedo for the first spring processed by the RGPS, the early spring of 1997. The data include most of the Beaufort and Chukchi Seas. We find that the mean albedo is 0.79 with a standard deviation of 0.04, with lower albedo values near the edge of the perennial ice zone. The biggest source of error is likely the assumed rate of snow accumulation on new ice.

scholarly journals Predicting Melt Pond Fraction on Landfast Snow Covered First Year Sea Ice from Winter C-Band SAR Backscatter Utilizing Linear, Polarimetric and Texture Parameters

2018 ◽  
Vol 10 (10) ◽  
pp. 1603 ◽  
Author(s):  
Saroat Ramjan ◽  
Torsten Geldsetzer ◽  
Randall Scharien ◽  
John Yackel
Keyword(s):  
Sea Ice ◽  
Regression Models ◽  
Incidence Angle ◽  
Early Summer ◽  
Aerial Photographs ◽  
Late Winter ◽  
First Year ◽  
Melt Pond ◽  
Texture Parameters ◽  
Snow Thickness

Early-summer melt pond fraction is predicted using late-winter C-band backscatter of snow-covered first-year sea ice. Aerial photographs were acquired during an early-summer 2012 field campaign in Resolute Passage, Nunavut, Canada, on smooth first-year sea ice to estimate the melt pond fraction. RADARSAT-2 Synthetic Aperture Radar (SAR) data were acquired over the study area in late winter prior to melt onset. Correlations between the melt pond fractions and late-winter linear and polarimetric SAR parameters and texture measures derived from the SAR parameters are utilized to develop multivariate regression models that predict melt pond fractions. The results demonstrate substantial capability of the regression models to predict melt pond fractions for all SAR incidence angle ranges. The combination of the most significant linear, polarimetric and texture parameters provide the best model at far-range incidence angles, with an R 2 of 0.62 and a pond fraction RMSE of 0.09. Near- and mid- range incidence angle models provide R 2 values of 0.57 and 0.61, respectively, with an RMSE of 0.11. The strength of the regression models improves when SAR parameters are combined with texture parameters. These predictions also serve as a proxy to estimate snow thickness distributions during late winter as higher pond fractions evolve from thinner snow cover.

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.

scholarly journals An intercomparison between AMSR-E snow-depth and satellite C- and Ku-band radar backscatter data for Antarctic sea ice

2011 ◽  
Vol 52 (57) ◽  
pp. 279-290 ◽  
Author(s):  
Stefan Kern ◽  
Burcu Ozsoy-Cicek ◽  
Sascha Willmes ◽  
Marcel Nicolaus ◽  
Christian Haas ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Weddell Sea ◽  
Late Winter ◽  
First Year ◽  
Radar Backscatter ◽  
Antarctic Sea Ice ◽  
Ridged Ice ◽  
Ice Fraction ◽  
Ku Band

AbstractAdvanced Microwave Scanning Radiometer (AMSR-E) snow-depth data for Antarctic sea ice are compared with ship-based visual observations of snow depth, ice type and ridged-ice fraction, and with satellite C-band and Ku-band radar backscatter observations for two ship cruises into the Weddell Sea (ISPOL 2004–05,WWOS 2006) and one cruise into the Bellingshausen Sea (SIMBA 2007) during late winter/spring. Most (>75%) AMSR-E and ship-based snow-depth observations agree within 0.2 m during WWOS and SIMBA. Remaining observations indicate substantial underestimations of snow depths by AMSR-E data. These underestimations tend to increase with the ridged-ice fraction for WWOS and SIMBA. In areas with large snow depths, a combination of relatively stable low C-band radar backscatter and variable Ku-band radar backscatter is associated with undeformed first-year ice and may indicate snow metamorphism at this time of year during SIMBA. In areas with small snow depths, a combination of relatively stable low Ku-band radar backscatter, high C-band radar backscatter and low C-band radar backscatter standard deviations is associated with rough first-year ice during SIMBA. This information can help to better understand causes of the observed AMSR-E snow-depth bias during late-winter/spring conditions with decreasing average snow depth and to delineate areas where this bias occurs.

Distribution and movements of white foxes in northern and western Alaska

1968 ◽  
Vol 46 (5) ◽  
pp. 849-854 ◽  
Author(s):  
David L. Chesemore
Keyword(s):  
Sea Ice ◽  
Bering Sea ◽  
Early Spring ◽  
Aleutian Islands ◽  
Late Winter ◽  
Seasonal Movements ◽  
Alaskan Arctic ◽  
Northern Alaska ◽  
The Bering Sea

White foxes occur on the tundra of northern and western Alaska and predominate on St. Lawrence, St. Matthew, Hall, and Diomede Islands in the Bering Sea. Few white foxes are found on the Pribilof and Aleutian Islands where blue foxes dominate the local fox population. On the Alaskan Arctic Slope, two seasonal movements, the first in the fall when foxes move seaward towards the coast and sea ice, and the second in late winter and early spring when they return inland to occupy summer den sites, occur. Although reported in other arctic areas, no definite records of fox migrations in northern Alaska exist. Distribution records for white foxes in Alaska are summarized.

scholarly journals Brief Communication: Capturing scales of spatial heterogeneity of Antarctic sea ice algae communities

2016 ◽  
Author(s):  
Alexander L. Forrest ◽  
Lars C. Lund-Hansen ◽  
Brian K. Sorrell ◽  
Isak Bowden-Floyd ◽  
Vanessa Lucieer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Spatial Heterogeneity ◽  
First Year ◽  
Ice Algae ◽  
Ecosystem Response ◽  
Algae Biomass ◽  
Sea Ice Algae ◽  
Antarctic Sea Ice ◽  
Spectral Bands ◽  
Antarctic Waters

Abstract. Identifying spatial heterogeneity of sea ice algae communities is critical to predicting ecosystem response under future climate scenarios. Using an autonomous robotic sampling platform beneath sea ice in McMurdo Sound, Antarctica, we measured irradiance in spectral bands expected to describe the spatial heterogeneity. Derived estimates of ice algae biomass identified patchiness at length scales varying from 50–70 m under first-year sea ice. These results demonstrate that a step-change in how these communities can be assessed and monitored. The developed methodologies could be subsequently refined to further categorize different ice algae communities and their associated productivity in both Arctic and Antarctic waters.

scholarly journals A New Retracking Algorithm for Retrieving Sea Ice Freeboard from CryoSat-2 Radar Altimeter Data during Winter–Spring Transition

2019 ◽  
Vol 11 (10) ◽  
pp. 1194 ◽  
Author(s):  
Xiaoyi Shen ◽  
Markku Similä ◽  
Wolfgang Dierking ◽  
Xi Zhang ◽  
Changqing Ke ◽  
...  
Keyword(s):  
Sea Ice ◽  
European Space Agency ◽  
Early Spring ◽  
Bézier Curve ◽  
Altimeter Data ◽  
Bezier Curve ◽  
Late Winter ◽  
Radar Altimeter ◽  
Depth Level ◽  
Space Agency

A new method called Bézier curve fitting (BCF) for approximating CryoSat-2 (CS-2) SAR-mode waveform is developed to optimize the retrieval of surface elevation of both sea ice and leads for the period of late winter/early spring. We found that the best results are achieved when the retracking points are fixed on positions at which the rise of the fitted Bézier curve reaches 70% of its peak in case of leads, and 50% in case of sea ice. In order to evaluate the proposed retracking algorithm, we compare it to other empirically-based methods currently reported in the literature, namely the threshold first-maximum retracker algorithm (TFMRA) and the European Space Agency (ESA) CS-2 in-depth Level-2 algorithm (L2I). The results of the retracking procedure for the different algorithms are validated using data of the Operation Ice Bridge (OIB) airborne mission. For two OIB campaign periods in March 2015 and April 2016, the mean absolute differences between freeboard values retrieved from CS-2 and OIB data were 9.22 and 7.79 cm when using the BCF method, 10.41 cm and 8.16 cm for TFMRA, and 10.01 cm and 8.42 cm for L2I. This suggests that the sea ice freeboard data can be obtained with a higher accuracy when using the proposed BCF method instead of the TFMRA or the CS-2 L2I algorithm.

scholarly journals Contrasting Ice Algae and Snow‐Dependent Irradiance Relationships Between First‐Year and Multiyear Sea Ice

2019 ◽  
Vol 46 (19) ◽  
pp. 10834-10843 ◽  
Author(s):  
Benjamin A. Lange ◽  
Christian Haas ◽  
Joannie Charette ◽  
Christian Katlein ◽  
Karley Campbell ◽  
...  
Keyword(s):  
Sea Ice ◽  
First Year ◽  
Ice Algae

scholarly journals Sources of anions in aerosols in northeast Greenland during late winter

2012 ◽  
Vol 12 (6) ◽  
pp. 14813-14836 ◽  
Author(s):  
M. Fenger ◽  
L. L. Sørensen ◽  
K. Kristensen ◽  
B. Jensen ◽  
Q. T. Nquyen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Long Range ◽  
Atmospheric Aerosols ◽  
Fine Particles ◽  
Chemical Properties ◽  
High Arctic ◽  
Early Spring ◽  
Water Soluble ◽  
The Arctic ◽  
Late Winter

Abstract. The knowledge of climate effects of atmospheric aerosols is associated with large uncertainty, and a better understanding of their physical and chemical properties is needed, especially in the Arctic environment. The objective of the present study is to improve our understanding of the processes affecting the composition of the aerosols in the high Arctic. Therefore size-segregated aerosols were sampled at a high Arctic site, Station Nord (Northeast Greenland), in March 2009 using a Micro Orifice Uniform Deposit Impactor. The aerosol samples were extracted in order to analyze the three water-soluble anions: chloride, nitrate and sulphate. The results are discussed based on possible chemical and physical transformations as well as transport patterns. The total concentrations of the ions at Station Nord were 53–507 ng m−3, 2–298 ng m−3 and 535–1087 ng m−3 for chloride (Cl−), nitrate (NO3-) and sulphate (SO42−), respectively. The aerosols in late winter/early spring, after polar sunrise, are found to be a mixture of long-range transported and regional to local originating aerosols. Fine particles, smaller than 1 μm, containing SO42−, Cl− and NO3−, are hypothesized to originate from long-range transport, where SO42− is by far the dominating anion accounting for 50–85% of the analyzed mass. The analysis suggests that Cl− and NO3− in coarser particles (>1.5 μm) originate from local/regional sources. Under conditions where the air mass is transported over sea-ice at high wind speeds, very coarse particles (>18 μm) are observed and it is hypothesized that frost flowers on the sea ice is a source of very coarse chloride particles in the Arctic.

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