Consolidated Pack Ice Research Articles

Turbulent Heat Fluxes over Arctic Sea Ice: Measurements and Evaluation of Recent Parameterizations

We present direct eddy covariance measurements of the surface heat flux in sea ice over a wide range of conditions across the Arctic Ocean made during two research cruises. Photographic imagery of the surface around the ship provides a local, in situ estimate of the ice fraction. Aerodynamically rough conditions prevail for the majority of the time in the consolidated pack ice. The results are analyzed in the framework of a recently-developed parameterization scheme in which the exchange coefficients over ice are functions of a roughness Reynolds number, R*, hence account for aerodynamic roughness variability. This parameterization accurately represents the measured fluxes under all conditions, while under aerodynamically rough conditions the existing parameterizations from both the Met Office Unified Model, and ECMWF Integrated Forecast System overestimate the fluxes. The results corroborate those of a previous airborne study over the marginal ice zone, and encompass a wider range of atmospheric stability conditions.

Physical and morphological properties of first-year Antarctic sea ice in the spring marginal ice zone of the Atlantic-Indian sector

AbstractThis study presents the first dataset of physical and textural properties of sea ice collected in the South Atlantic and Indian Ocean sector of the Antarctic marginal ice zone (MIZ). Observations of sea ice from this region in the austral spring 2019, including sea-ice core temperature, salinity, crystal size, texture, oxygen isotopes and stratigraphy, were used in conjunction with a Lagrangian back-tracking algorithm and atmospheric reanalyses. This method relates the reconstructed synoptic conditions to sea-ice growth along the transect. A significant difference was found between the stratigraphy of consolidated pack ice samples collected at the same latitude and spanning over 550 km eastwards. The eastward group was found to have more disturbances in their stratigraphy which is attributed to the highly variable atmospheric and sea-ice conditions together with varying wave penetration through the sea-ice pack, notably during the passage of an intense polar cyclone, while the westward group showed no signs of disturbance or deformation. These results indicate that consolidated Antarctic sea-ice floes of similar thickness and from the same latitude in the MIZ have distinct stratigraphic properties, which will influence their physical and biogeochemical features.

Physical and mechanical properties of winter first-year ice in the Antarctic marginal ice zone along the Good Hope Line

Abstract. As part of the 2019 Southern oCean seAsonal Experiment (SCALE) Winter Cruise of the South African icebreaker SA Agulhas II, first-year ice was sampled at the advancing outer edge of the Antarctic marginal ice zone along a 150 km Good Hope Line transect. Ice cores were extracted from four solitary pancake ice floes of 1.83–2.95 m diameter and 0.37–0.45 m thickness as well as a 12×4 m pancake ice floe of 0.31–0.76 m thickness that was part of a larger consolidated pack ice domain. The ice cores were subsequently analysed for temperature, salinity, texture, anisotropic elastic properties and compressive strength. All ice cores from both solitary pancake ice floes and consolidated pack ice exhibited predominantly granular textures. The vertical distributions of salinity, brine volume and mechanical properties were significantly different for the two ice types. High salinity values of 12.6±4.9 PSU were found at the topmost layer of the solitary pancake ice floes but not for the consolidated pack ice. The uniaxial compressive strengths for pancake ice and consolidated pack ice were determined as 2.3±0.5 and 4.1±0.9 MPa, respectively. Young's and shear moduli in the longitudinal core direction of solitary pancake ice were obtained as 3.7±2.0 and 1.3±0.7 GPa, respectively, and of consolidated pack ice as 6.4±1.6 and 2.3±0.6 GPa, respectively. Comparing Young's and shear moduli measured in longitudinal and transverse core directions, a clear directional dependency was found, in particular for the consolidated pack ice.

Evaluation of summer passive microwave sea ice concentrations in the Chukchi Sea based on KOMPSAT-5 SAR and numerical weather prediction data

Satellite passive microwave (PM) sensors have observed sea ice in Polar Regions and provided sea ice concentration (SIC) data since the 1970s. SIC has been used as a primary data source for climate change prediction and ship navigation. However, the accuracy of PM SIC is typically low and biased in summer. To provide more accurate information for climatic research and ship navigation, it is necessary to evaluate quantitatively the accuracy of PM SIC and to account for its errors. In this research, we evaluated the SIC data derived from PM measurements using four representative sea ice algorithms: NASA Team (NT), Bootstrap (BT), Ocean and Sea Ice Satellite Application Facility (OSISAF) hybrid, and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI). Analyses were performed for the Chukchi Sea in summer using KOrean Multi-Purpose SATellite-5 (KOMPSAT-5) Enhanced Wide-swath synthetic aperture radar (SAR) images. Ice/water maps were generated by binary classification of texture features in the SAR images based on Random Forest, a rule-based machine learning approach. SIC values estimated from the sea ice algorithms showed good correlation with those calculated from the KOMPSAT-5 ice/water maps, but the root mean square error was larger than 10%. SIC values estimated from the algorithms showed different error trends according to the KOMPSAT-5 SIC range. All algorithms overestimated SIC values in open drift ice zones (KOMPSAT-5 SICs ranged from 0% to 15%). In marginal ice zones (SICs ranged from 15% to 80%), the OSISAF SIC values were the least biased compared to those from KOMPSAT-5. The NT algorithm largely underestimated SIC values in marginal ice zones, while the BT and ASI algorithms overestimated them considerably. All algorithms, except for BT, underestimated SIC in consolidated pack ice zones (SICs ranged from 80% to 100%). By analyzing the correlations of biases of SIC from the algorithms with the numerical weather prediction (NWP) data from the European Reanalysis Agency Interim reanalysis, it was found that the overestimation of NT and ASI SICs was largely influenced by atmospheric water vapor content, while the underestimation of NT and OSISAF SICs was owing to ice surface melting. The overestimation of BT SICs was not significantly correlated with the NWP data. The underestimated SIC from the BT and ASI algorithms for high SIC regions might be compensated by the atmospheric water vapor content. The differences in SIC values estimated from each algorithm were due to different sensitivities to atmospheric water vapor content in the regions with KOMPSAT-5 SIC lower than 40% and to ice surface melting in the regions with higher KOMPSAT-5 SIC.

Mapping and assessing variability in the Antarctic marginal ice zone, pack ice and coastal polynyas in two sea ice algorithms with implications on breeding success of snow petrels

Abstract. Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack ice and coastal polynyas in the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent record for assessing the proportion of the sea ice cover that is covered by each of these ice categories. However, estimates of the amount of MIZ, consolidated pack ice and polynyas depend strongly on which sea ice algorithm is used. This study uses two popular passive microwave sea ice algorithms, the NASA Team and Bootstrap, and applies the same thresholds to the sea ice concentrations to evaluate the distribution and variability in the MIZ, the consolidated pack ice and coastal polynyas. Results reveal that the seasonal cycle in the MIZ and pack ice is generally similar between both algorithms, yet the NASA Team algorithm has on average twice the MIZ and half the consolidated pack ice area as the Bootstrap algorithm. Trends also differ, with the Bootstrap algorithm suggesting statistically significant trends towards increased pack ice area and no statistically significant trends in the MIZ. The NASA Team algorithm on the other hand indicates statistically significant positive trends in the MIZ during spring. Potential coastal polynya area and amount of broken ice within the consolidated ice pack are also larger in the NASA Team algorithm. The timing of maximum polynya area may differ by as much as 5 months between algorithms. These differences lead to different relationships between sea ice characteristics and biological processes, as illustrated here with the breeding success of an Antarctic seabird.

Improved mapping of sea ice production in the Arctic Ocean using AMSR‐E thin ice thickness algorithm

AbstractNew and improved estimates of sea ice production in the Arctic Ocean are derived from AMSR‐E satellite and atmospheric reanalysis data for the period 2002–2011, at a spatial resolution of 6.25 km and using a newly developed fast‐ice mask. High ice production in the major coastal polynyas is well demonstrated. The total annual cumulative ice production in the major 10 polynya regions is about . The interannual variability of the ice production for each polynya is presented during 2002–2011. No obvious relationship is noted between the ice production and the recent drastic reduction in the preceding summer Arctic sea ice extent. Most polynya regions exhibit maximum ice production in autumn (October – November), before areas offshore have been covered with consolidated pack ice. Sea ice production from October to November in the marginal ice zone of the Pacific Ocean sector is negatively correlated with summer ice extent there. The ice production from October to November of 2007 (a record minimum summer ice extent) was about twice as large as that in other years. The high ice production area shifted to higher latitudes i.e., toward the deep Canada Basin, due to the retreat of the summer ice edge. We speculate that the resultant increase in brine input could change the oceanic structure in the basin, specifically deepening the winter mixed layer.

Phytoplankton blooms beneath the sea ice in the Chukchi sea

In the Arctic Ocean, phytoplankton blooms on continental shelves are often limited by light availability, and are therefore thought to be restricted to waters free of sea ice. During July 2011 in the Chukchi Sea, a large phytoplankton bloom was observed beneath fully consolidated pack ice and extended from the ice edge to >100km into the pack. The bloom was composed primarily of diatoms, with biomass reaching 1291mg chlorophyll am−2 and rates of carbon fixation as high as 3.7gCm−2d−1. Although the sea ice where the bloom was observed was near 100% concentration and 0.8–1.2m thick, 30–40% of its surface was covered by melt ponds that transmitted 4-fold more light than adjacent areas of bare ice, providing sufficient light for phytoplankton to bloom. Phytoplankton growth rates associated with the under-ice bloom averaged 0.9d−1 and were as high as 1.6d−1. We argue that a thinning sea ice cover with more numerous melt ponds over the past decade has enhanced light penetration through the sea ice into the upper water column, favoring the development of these blooms. These observations, coupled with additional biogeochemical evidence, suggest that phytoplankton blooms are currently widespread on nutrient-rich Arctic continental shelves and that satellite-based estimates of annual primary production in waters where under-ice blooms develop are ~10-fold too low. These massive phytoplankton blooms represent a marked shift in our understanding of Arctic marine ecosystems.

Contrasting inherent optical properties and particle characteristics between an under-ice phytoplankton bloom and open water in the Chukchi Sea

Variability in the inherent optical properties (IOPs) of seawater and characteristics of the particle assemblage were examined along a transect in the Chukchi Sea during July 2011. This transect encompassed samples from open waters of the marginal ice zone exhibiting low concentrations of chlorophyll-a (Chla<1mgm−3), as well as an extensive phytoplankton bloom (Chla>30mgm−3) beneath consolidated pack ice. Measurements included the spectral coefficients for particulate beam attenuation, backscattering, and absorption, bulk indicators of particle concentration and composition, and the particle size distribution. Within the bloom microphytoplankton contributed >95% to the total Chla, and relatively small amounts of nonalgal particles were present. This assemblage exhibited low Chla-specific phytoplankton absorption coefficients (0.006m2mg−1 at 676nm) indicating a strong influence of pigment packaging, and a weak spectral dependence of the particulate backscattering coefficient. In contrast, the phytoplankton community in nutrient-depleted surface waters outside the sea ice had a strong contribution of picoplankton to Chla (54%) and an increased abundance of nonalgal particles. The Chla-specific phytoplankton absorption coefficient approached maximum values at 676nm (0.023m2mg−1) and particle backscattering had much stronger spectral dependence. Additional samples from near the sea floor exhibited characteristics of either mineral-dominated assemblages or a mixture of mineral and organic particles, and also displayed optical differentiation from the surface samples. The marked contrast in absorption, attenuation, and backscattering properties of these ecological regimes suggest that they can be discriminated from optical measurements available on a variety of in situ and remote-sensing platforms.

Temporal variation in distribution and density of ice-obligated seals in western Hudson Bay, Canada

Recent unidirectional climatic trends and changes in top predator population ecology suggest that long-term modifications may be happening in Hudson Bay, Canada. Effects of such changes on ice-obligated seal populations are expected but long-term studies are required to differentiate climate-induced changes from natural variation. We conducted strip-transect surveys in late spring in 1995–1997, 1999–2000 and 2007–2008 to estimate distribution, density and abundance of ice-obligated ringed (Phoca hispida) and bearded (Erignathus barbatus) seals in western Hudson Bay. When hauled out, ringed seals preferred land-fast and consolidated pack ice, whereas bearded seals preferred unconsolidated pack ice. Bearded and ringed seal density estimates varied from 0.0036 to 0.0229 seals/km2 of ice and from 0.46 to 1.60 seals/km2 of ice, respectively. Strong inter-annual variations were recorded in the abundance estimates of both species, with the largest abundance estimates in 1995 (104,162 and 1,494 ringed and bearded seals, respectively) and the lowest in 2008 for ringed seals (33,701) and 1997 for bearded seals (278). A sine function best described seal density estimates in western Hudson Bay and suggested a decadal cycle. Previous studies that reported low ringed seal demographic parameters in the 1990s and a recovery in the 2000s supported our interpretation of the survey results. We discuss our results in the context of climate warming and suggest that a long-term decline in ice-obligated seal density estimates may overlay a possible natural decadal cycle.

A New Algorithm (ECICE) to Estimate Ice Concentration From Remote Sensing Observations: An Application to 85-GHz Passive Microwave Data

A new algorithm, called Environment Canada's Ice Concentration Extractor (ECICE), has been developed to calculate total ice concentration and partial concentration of each ice type from remote-sensing observations. It employs two new concepts. First, it obtains a best estimate of ice concentrations by minimizing the sum of squared difference between observed and estimated radiometric values based on a linear radiometric model for each ice type. Second, instead of employing a single radiometric value (tie point) for each ice type, it utilizes the probability density distribution of the radiometric values for each ice type. Then, in a Monte Carlo simulation, 1000 radiometric values are randomly selected, total and ice-type concentrations are calculated by solving the minimization problem, and finally, median values from the 1000 simulations are chosen. The algorithm was applied to the winter sea ice in the Gulf of St. Lawrence, Canada, using observations from Special Sensor Microwave Imager (SSM/I) 85-GHz channel. Results were evaluated against ice concentration estimates from the operational analysis of Radarsat images at the Canadian Ice Service (CIS). Statistics of the differences between the output concentration and CIS estimates show that ECICE can successfully identify open water and consolidated pack ice pixels better than the Enhanced NASA Team algorithm. However, in areas of ice concentrations between 20% and 70%, the algorithm's performance could not be precisely evaluated because the typical size of the CIS's analysis polygon is much larger than the footprint of the 85-GHz SSM/I channel. Hence, the algorithm captures information at a finer spatial scale. Examples of using one, two, and three radiometric parameters to calculate the concentrations are presented.

The migratory behaviour of narwhals (Monodon monoceros)

Sixteen female narwhals (Monodon monoceros) were tracked by satellite in 2000 and 2001 from their summering ground near Somerset Island in the Canadian High Arctic to their wintering ground in central Baffin Bay. The wintering ground location was spatially discrete from another narwhal wintering ground in southern Baffin Bay. Area extent of the summering ground was approximately 9464 km2and area extent of the wintering ground was 25 846 km2. Two of the narwhals were tracked for more than 12 consecutive months. These whales used three focal areas between their spring and autumn migration: a coastal area in the open-water season in August in the Canadian High Arctic, a wintering area from November through April in the consolidated pack ice of Baffin Bay, and an early summer area in front of the receding fast ice edge in Lancaster Sound. The whales showed remarkable site fidelity to summering grounds and had specific migratory routes that followed sea ice formation and recession.

Evaluation of an Aerial Survey of Pacific Walruses (Odobenus rosmarus divergens)

An aerial survey of Pacific walruses (Odobenus rosmarus divergens) was evaluated to determine the reliability of estimates of population abundance. The probability of detecting groups of walruses on the pack ice remained uniform to at least 0.93 km from the flight line, whereas the probability of detection decreased significantly beyond 0.23 km for walruses in the water. Walruses were more abundant along the ice-edge zone between 162 and 165°W than in other areas of the Chukchi Sea during September 1975. Few walruses were observed in consolidated pack ice north of the ice-edge zone or in ice-free water to the south. More walrus groups and larger mean group size were observed on September 8 than on other days. We estimated abundance for each day and all days combined using methods based on sample area and numbers of strip samples. Estimates varied among days by over an order of magnitude; this variation is attributed to the combined effect of chance sampling of an aggregated population and variation in the fraction of walruses hauled out. The coefficient of variation of the estimates ranged between 0.25 and 0.99. This imprecision was due to the aggregated distribution of walruses and the large variation in group size. Using the survey data as a basis for stratification, we calculated that, due to the high variability within strata, a sample size of 40% of the total area or 56% of the total available strips would be required to obtain 95% confidence limits within 10% of the estimate of total abundance. Variation contributed by observer error in estimating group size also is relatively unimportant to the precision of abundance estimates. Studies of natural history, particularly those oriented toward activity and habitat selection, would help investigators estimate bias due to the variable fraction hauled out and design surveys based on meaningful strata. Estimates of total abundance based on limited survey efforts will provide information of little reliability. Key words: aerial survey, aggregation, Chukchi Sea, estimation, population, stratification, walrus