As an inhomogeneous mixture of pure ice, brine, air and solid salts the physical properties of sea ice depend on its highly temperature-dependent microstructure. Understanding the microstructure and the way it responds to variations in temperature and salinity is crucial in developing an improved understanding of the interaction between sea ice and the environment. However, measurements monitoring the internal structure of sea ice are difficult to obtain without disturbing its natural state. We have recently developed an application of cross-borehole d.c. resistivity tomography to make in situ measurements that resolve the anisotropic resistivity structure of first-year sea ice. We present results from measurements made in 2008 off Barrow, Alaska, and in 2009 off Ross Island, Antarctica. the sea ice in these two regions forms in different environments: at Barrow, relatively quiescent conditions typically lead to a predominance of columnar ice, while more turbulent conditions and underwater ice formation in McMurdo Sound tend to produce a larger component of frazil or platelet ice. Interpretation of the resistivity measurements carried out in association with temperature and salinity data collected simultaneously allows both observation of the temporal evolution of the ice structure and, in the case of the Antarctic measurements, the identification of different ice types.

Although satellite data are useful for obtaining ice-thickness distribution for perennial sea ice or in stable thin-sea-ice areas, they are still largely an unresolved issue for the seasonal ice zone (SIZ). We address this problem using L-band synthetic aperture radar (SAR). In the SIZ, ice-thickness growth is closely related to deformation, so surface roughness is expected to correlate with ice thickness. L-band SAR, suitable for detecting such surface roughness, is a promising tool for obtaining thickness distribution. This idea was supported by an airborne polarimetric and interferometric SAR (Pi-SAR) validation. To extend this result to spaceborne L-band SAR with coarser resolution, we conducted in situ measurements of ice thickness and surface roughness in February 2008 in the southern Sea of Okhotsk with an icebreaker in coordination with the Advanced Land Observing Satellite (ALOS)/Phased Array-type L-band SAR (PALSAR) orbit. A helicopter-borne laser profiler was used to improve the estimation of surface roughness. It was found that backscatter coefficients (HH) correlated well with ice thickness (R = 0.86) and surface roughness (R = 0.70), which confirms the possibility of determining ice-thickness distribution in the SIZ. the interannual variation of PALSAR-derived ice-thickness distribution in the southern Sea of Okhotsk is also discussed.

Melt ponds are regularly observed on the surface of Arctic sea ice in late spring and summer. They strongly reduce the surface albedo and accelerate the decay of Actic sea ice. Until now, only a few studies have looked at the spatial extent of melt ponds on Arctic sea ice. Knowledge of the melt-pond distribution on the entire Arctic sea ice would provide a solid basis for the parameterization of melt ponds in existing sea-ice models. Due to the different spectral properties of snow, ice and water, a multispectral sensor such as Landsat 7 ETM+ is generally applicable for the analysis of distribution. an additional advantage of the ETM+ sensor is the very high spatial resolution (30 m). an algorithm based on a principal component analysis (PCA) of two spectral channels has been developed in order to determine the melt-pond fraction. PCA allows differentiation of melt ponds and other surface types such as snow, ice or water. Spectral bands 1 and 4 with central wavelengths at 480 and 770 nm, respectively, are used as they represent the differences in the spectral albedo of melt ponds. A Landsat 7 ETM+ scene from 19 July 2001 was analysed using PCA. the melt-pond fraction determined by the PCA method yields a different spatial distribution of the ponded areas from that developed by others. A MODIS subset from the same date and area is also analysed. the classification of MODIS data results in a higher melt-pond fraction than both Landsat classifications.

The summer extent of the Arctic sea-ice cover has decreased in recent decades and there have been alterations in the timing and duration of the summer melt season. These changes in ice conditions have affected the partitioning of solar radiation in the Arctic atmosphere–ice–ocean system. the impact of sea-ice changes on solar partitioning is examined on a pan-Arctic scale using a 25 km × 25 km Equal-Area Scalable Earth Grid for the years 1979–2007. Daily values of incident solar irradiance are obtained from NCEP reanalysis products adjusted by ERA-40, and ice concentrations are determined from passive microwave satellite data. the albedo of the ice is parameterized by a five-stage process that includes dry snow, melting snow, melt pond formation, melt pond evolution, and freeze-up. the timing of these stages is governed by the onset dates of summer melt and fall freeze-up, which are determined from satellite observations. Trends of solar heat input to the ice were mixed, with increases due to longer melt seasons and decreases due to reduced ice concentration. Results indicate a general trend of increasing solar heat input to the Arctic ice–ocean system due to declines in albedo induced by decreases in ice concentration and longer melt seasons. the evolution of sea-ice albedo, and hence the total solar heating of the ice–ocean system, is more sensitive to the date of melt onset than the date of fall freeze-up. the largest increases in total annual solar heat input from 1979 to 2007, averaging as much as 4%a–1, occurred in the Chukchi Sea region. the contribution of solar heat to the ocean is increasing faster than the contribution to the ice due to the loss of sea ice.

Satellite radar altimetry provides data to monitor winter Arctic sea-ice thickness variability on interannual, basin-wide scales. When using this technique an assumption is made that the peak of the radar return originates from the snow/ice interface. This has been shown to be true in the laboratory for cold, dry snow as is the case on Arctic sea ice during winter. However, this assumption has not been tested in the field. We use data from an airborne normal-incidence Ku-band radar altimeter and in situ field measurements, collected during the CryoSat Validation Experiment (CryoVEx) Bay of Bothnia, 2006 and 2008 field campaigns, to determine the dominant scattering surface for Arctic snow-covered sea ice. In 2006, when the snow temperatures were close to freezing, the dominant scattering surface in 25% of the radar returns appeared closer to the snow/ice interface than the air/snow interface. However, in 2008, when temperatures were lower, the dominant scattering surface appeared closer to the snow/ice interface than the air/snow interface in 80% of the returns.

We present results from a laboratory tank study of ice growing from saline water in a wave field, focusing on the transition from a predominantly frazil/grease-ice cover to a pancake-ice cover. Combining surface temperature observations with direct and indirect determinations of ice salinity and solid fraction, we describe the evolution of frazil- and pancake-ice area fraction, salinity and solid-ice volume fraction over the course of 1 day. In the investigated stage of transition, frazil ice surrounding the pancakes was found to have rather constant properties: a surface temperature 0.4–0.6 K below the freezing point of the underlying sea water, a salinity of 24–26 g kg–1 and a solid volume fraction of 0.25–0.29. the average salinity of young pancake ice, estimated from heat and salt budgets, decreased from 18 to 15 g kg–1, while average solid volume fractions increased from 0.6 to 0.7. the transition from frazil to pancake is estimated to take place when solid fractions reach 0.37–0.40 and surface temperatures are 0.7–0.9 K below the freezing point. We find that, for proper modelling of the grease–pancake system, it is important to distinguish between a surface and volumetric fraction of pancakes and grease ice.

Springtime measurements of CO2 exchange over seasonal sea ice in the Canadian Arctic Archipelago using eddy covariance show that CO2 was generally released to the atmosphere during the cold (ice surface temperatures less than about –6˚C) early part of the season, but was absorbed from the atmosphere as warming advanced. Hourly maximum efflux and uptake rates approached 1.0 and –3.0 μmol m–2 s–1, respectively. These CO2 flux rates are far greater than previously reported over sea ice and are comparable in magnitude to exchanges observed within other systems (terrestrial and marine). Uptake generally occurred for wind speeds in excess of 6 m s–1 and corresponded to local maxima in temperature at the snow–ice interface and net radiation. Efflux, on the other hand, occurred under weaker wind speeds and periods of local minima in temperature and net radiation. the wind speeds associated with uptake are above a critical threshold for drifting and blowing snow, suggesting that ventilation of the snowpack and turbulent exchange with the brine-wetted grains are an important part of the process. Both the uptake and release fluxes may be at least partially driven by the temperature sensitivity of the carbonate system speciation in the brine-wetted snow base and upper sea ice. the period of maximum springtime CO2 uptake occurred as the sea-ice permeability increased, passing a critical threshold allowing vertical brine movement throughout the sea-ice sheet. At this point, atmospheric CO2 would have been available to the under-ice sea-water carbonate system, with ramifications for carbon cycling in sea-ice-dominated polar waters.

Three ice type regimes at Ice Station Belgica (ISB), during the 2007 International Polar Year SIMBA (Sea Ice Mass Balance in Antarctica) expedition, were characterized and assessed for elevation, snow depth, ice freeboard and thickness. Analyses of the probability distribution functions showed great potential for satellite-based altimetry for estimating ice thickness. In question is the required altimeter sampling density for reasonably accurate estimation of snow surface elevation given inherent spatial averaging. This study assesses an effort to determine the number of laser altimeter ‘hits’ of the ISB floe, as a representative Antarctic floe of mixed first- and multi-year ice types, for the purpose of statistically recreating the in situ-determined ice-thickness and snow depth distribution based on the fractional coverage of each ice type. Estimates of the fractional coverage and spatial distribution of the ice types, referred to as ice ‘towns’, for the 5 km2 floe were assessed by in situ mapping and photo-visual documentation. Simulated ICESat altimeter tracks, with spot size ~70m and spacing ~170 m, sampled the floe’s towns, generating a buoyancy-derived ice thickness distribution. 115 altimeter hits were required to statistically recreate the regional thickness mean and distribution for a three-town assemblage of mixed first- and multi-year ice, and 85 hits for a two-town assemblage of first-year ice only: equivalent to 19.5 and 14.5 km respectively of continuous altimeter track over a floe region of similar structure. Results have significant implications toward model development of sea-ice sampling performance of the ICESat laser altimeter record as well as maximizing sampling characteristics of satellite/airborne laser and radar altimetry missions for sea-ice thickness.

During sea-ice formation, the dissolved constituents of water are rejected from ice crystals. the initial fractionation of dissolved organic matter (DOM) in the Baltic Sea ice was studied through two freezing experiments and by sampling natural sea ice. DOM was characterized by the spectral absorption of chromophoric DOM (CDOM) and the parallel factor analysis of DOM fluorescence. Molecular weight measurements of DOM were applied to assess changes in the molecular size distribution of DOM in new sea ice relative to parent sea water. Both in the newly formed artificial and the natural sea ice, CDOM was enriched by 34–39% relative to salinity. the same three identified DOM fluorophores were present both in sea water and ice but enriched by 15–54% relative to salinity in ice. After the incorporation of DOM into ice, the ageing of ice decreased the spectral slope coefficient and the molecular weight of DOM. This study shows that physical processes during freezing of brackish water enrich chromo- and fluorophoric DOM relative to salts in sea ice.

In October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km × 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50–500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. the results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.

Sea-ice melting processes were inferred from in situ sea-ice and ocean condition data obtained in the Arctic in summer 2006 and 2007. the relationship between ice concentration observed by on-board ice watches and water temperature showed negative correlations. This implies that as ice concentration decreases, the upper ocean becomes warmer due to greater absorption of solar radiation into open water, which promotes ice melting. However, heating of surface water is significant even in regions that were almost completely ice-covered, suggesting that transmitted solar radiation through the ice is also effective at melting sea ice. A simplified ice–upper-ocean coupled model was applied to examine the effect of heat input from open water, thick ice and thin ice. the ponded thin ice is estimated to transmit approximately three times more solar radiation than ponded thick ice. Model results suggest that transmission of solar radiation through ponded ice amplified the ice-albedo feedback mechanism, particularly in thin ice regions. Recently, the extent of old and thick multi-year ice in the Arctic Ocean has been rapidly reduced. As a result, heat input to the upper ocean through the ice is enhanced and ice melt is further accelerated.

Modern satellite measurements of sea-ice thickness are based on altimeter measurements of the difference in elevation between the snow or ice surface and the local sea surface. For retrieval of sea-ice thickness, it is assumed that the ice is in hydrostatic equilibrium, and that the snow load on the ice and the density of the sea ice and sea water are known. This study presents data from in situ sea-ice thickness drillings and snow and ice density measurements from Fram Strait, the Barents Sea and the Svalbard coast, in the European Arctic. the error in the altimetry ice thickness products is assessed based on the spatial variability of snow and ice density and snow thickness data. Ice thickness uncertainty related to snow depth was found to be ∼40 cm (radar altimeter) and ∼90 cm (laser altimeter), while uncertainty related to ice density is 25 cm for both techniques. the assumption of hydrostatic equilibrium at the scales of the measurements (10–100 m) was found to hold better in the case of level landfast ice near Svalbard than for Fram Strait drift ice, which consists of mixed ice types, where the deviation between the calculated and measured ice thicknesses was on average ∼0.5 m.

Snow distribution is a dominating factor in sea-ice mass balance in the Bellingshausen Sea, Antarctica, through its roles in insulating the ice and contributing to snow-ice production. the wind has long been qualitatively recognized to influence the distribution of snow accumulation on sea ice, but the relative importance of drifting and blowing snow has not been quantified over Antarctic sea ice prior to this study. the presence and magnitude of drifting snow were monitored continuously along with wind speeds at two sites on an ice floe in the Bellingshausen Sea during the October 2007 Sea Ice Mass Balance in the Antarctic (SIMBA) experiment. Contemporaneous precipitation measurements collected on board the RVIB Nathaniel B. Palmer and accumulation measurements by automated ice mass-balance buoys (IMBs) allow us to document the proportion of snowfall that accumulated on level ice surfaces in the presence of high winds and blowing-snow conditions. Accumulation on the sea ice during the experiment averaged <0.01 m w.e. at both IMB sites, during a period when European Centre for Medium-Range Weather Forecasts analyses predicted >0.03 m w.e. of precipitation on the ice floe. Accumulation changes on the ice floe were clearly associated with drifting snow and high winds. Drifting-snow transport during the SIMBA experiment was supply-limited. Using these results to inform a preliminary study using a blowing-snow model, we show that over the entire Southern Ocean approximately half of the precipitation over sea ice could be lost to leads.

Advanced 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.

Wintertime (April–September) area estimates of the Terra Nova Bay polynya (TNBP), Antarctica, based on satellite microwave radiometry are compared with in situ observations of water salinity, temperature and currents at a mooring in Terra Nova Bay in 1996 and 1997. In 1996, polynya area anomalies and associated anomalies in polynya ice production are significantly correlated with salinity anomalies at the mooring. Salinity anomalies lag area and/or ice production anomalies by about 3 days. Up to 50% of the variability in the salinity at the mooring position can be explained by area and/or ice production anomalies in the TNBP for April–September 1996. This value increases to about 70% when considering shorter periods like April–June or May–July, but reduces to 30% later, for example July–September, together with a slight increase in time lag. In 1997, correlations are smaller, less significant and occur at a different time lag. Analysis of ocean currents at the mooring suggests that in 1996 conditions were more favourable than in 1997 for observing the impact of descending plumes of salt-enriched water formed in the polynya during ice formation on the water masses at the mooring depth.

The fractionation of major sea-water ions, or deviation in their relative concentrations from Standard Mean Ocean Water ratios, has been frequently observed in sea ice. It is generally thought to be associated with precipitation of solid salts at certain eutectic temperatures. the variability found in bulk sea-ice samples indicates that the fractionation of ions depends on the often unknown thermal history of sea ice, which affects the structure of pore networks and fate of solid salts within them. Here we investigate the distribution of ions in Arctic sea ice that is a few weeks old with a reconstructible thermal history. We separate the centrifugable (interconnected) and entrapped (likely disconnected) contributions to the ice salinity and determine their ion fractionation signatures. the results indicate that differential diffusion of ions, rather than eutectic precipitation of cryohydrates, has led to significant ion fractionation. the finding emphasizes the role of coupled diffusive–convective salt transport through complex pore networks in shaping the biogeochemistry of sea ice.

Sea-ice drift fields were obtained from sequences of synthetic aperture radar (SAR) images using a method based on pattern recognition. the accuracy of the method was estimated for two image products of the Envisat Advanced SAR (ASAR) with 25 m and 150 m pixel size. For data from the winter season it was found that 99% of the south–north and west–east components of the determined displacement vector are within ±3–5 pixels of a manually derived reference dataset, independent of the image resolution. For an image pair with 25 m resolution acquired during summer, the corresponding value is 12 pixels. Using the same resolution cell dimensions for the displacement fields in both image types, the estimated displacement components differed by 150–300 m. the use of different texture parameters for predicting the performance of the algorithm dependent on ice conditions and image characteristics was studied. It was found that high entropy values indicate a good performance.

Antarctic Sea Ice Processes and Climate (ASPeCt) ship-based ice observations, conducted during the Sea Ice Mass Balance in the Antarctic (SIMBA) and Sea Ice Physics and Ecosystem eXperiment (SIPEX) International Polar Year (IPY) cruises (September–October 2007), are used to validate remote-sensing measurements of ice extent and concentration. Observations include varied sea-ice types at and inside the ice edge of West (~90˚ W) and East (~120˚ E) Antarctica. Time series of Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) ice extents and US National Ice Center (NIC) ice edges were obtained for the 2007–08 periods bracketing the period these cruises were conducted. A comparison between passive microwave satellite imagery and ASPeCt observations of sea-ice concentration during two cruises was also performed. In 90˚W regions, the concentrated pack ice indicated good correlation between ship observations and passive microwave estimates of the ice concentration (R2 = 0.80). In the marginal zone of West Antarctica and over nearly the entire sea-ice zone of East Antarctica, correlation dropped to R2 < 0.60. These findings are consistent with other studies comparing passive microwave and ship observations and further verify that the East Antarctic sea-ice zone is more marginal in character. There are significant ice-edge differences between AMSR-E and NIC between late November 2007 and early March 2008 such that the AMSR-E sea-ice extent estimate is 1–2 × 106 km2 less than the NIC estimate.

Envisat Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) images are used to derive C-band HH-polarization normalized radar cross sections (NRCS). These are compared with ice-core analysis and visual ship-based observations of snow and ice properties observed according to the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol during two International Polar Year summer cruises (Oden 2008 and Palmer 2009) in West Antarctica. Thick first-year (TFY) and multi-year (MY) ice were the dominant ice types. the NRCS value ranges between –16.3 ± 1.1 and –7.6 ± 1.0 dB for TFY ice, and is –12.6 ± 1.3 dB for MY ice; for TFY ice, NRCS values increase from –~15 dB to –9 dB from December/January to mid-February. In situ and ASPeCt observations are not, however, detailed enough to interpret the observed NRCS change over time. Co-located Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) vertically polarized 37 GHz brightness temperatures (TB37V), 7 day and 1 day averages as well as the TB37V difference between ascending and descending AMSR-E overpasses suggest the low NRCS values (–15 dB) are associated with snowmelt being still in progress, while the change towards higher NRCS values (–9 dB) is caused by commencement of melt– refreeze cycles after about mid-January.