We present a 1-D enthalpy-based model of sea ice that allows for quantitative studies of sea ice and its interaction with radiative processes, melt ponds, oceanic heat and salt fluxes, internal density changes and surface heat fluxes on a single computational domain. The model provides new insight into the interior structure and the salinity evolution of sea ice. We compare our model results with measurements from laboratory experiments and show for example that no salt is lost from sea ice by brine expulsion.

The flow of liquid through porous sea ice is a fundamental process affecting problems in polar biology, oceanography and geophysics. The geometry and connectedness of the pore microstructure of sea ice determine its fluid permeability, which depends strongly on temperature. Here we analyze a simple pipe network as a basis for modeling fluid flow through the complex porous microstructure, and for numerical approximations of the fluid permeability of sea ice as a function of temperature. For slow flow the fluid system is equivalent to an electrical resistor network, and the network is solved using a fast multi-grid method. The radii of the pipes in the network are chosen randomly from distributions describing measured cross-sectional areas of brine inclusions in sea ice. At this stage, the model reflects only the most general features of brine microstructure and its evolution with temperature. Preliminary results for a basic implementation in two dimensions are presented. They are consistent with theoretical bounds on the vertical fluid permeability of sea ice found recently. Moreover, the results agree roughly with laboratory data for higher porosities. For lower porosities and colder temperatures, the fully connected network of pipes in the model, albeit with smaller radii, overestimates observed values. This finding provides evidence that the brine network becomes more disconnected with lower temperatures, which is consistent with transitional behavior near a percolation threshold.

Salt segregation and isotopic fractionation during sea-ice formation can be parameterized as a function of the ice growth rate. We performed a study to investigate if the salt segregation models derived for saline sea-ice studies are pertinent during the growth of Baltic Sea ice in brackish water. We used a time series of ice-salinity profiles and modeled growth rates to examine the relationship between effective salt segregation and growth rate. The results show that models derived for saline sea water are not directly applicable for use in the brackish waters of the Baltic Sea. We derived a simple model for the effective salt segregation in relation to ice growth rate, for a wide range of growth rates, pertinent for use in low-salinity Baltic Sea conditions and in the future development of a Baltic Sea ice salinity model.

Development of landfast sea ice and its snow cover was monitored in the Gulf of Bothnia, Baltic Sea, for a period of 4 weeks during the early melt season of 2004. During this period, approximately 90% of the snow layer was transformed into superimposed ice, while the rest sublimated. A one-dimensional thermodynamic snow/ice model was used to simulate this process. The modelled snowmelt and superimposed ice growth were consistent with the observations, but the net accumulation of superimposed ice was slightly overestimated. The errors in calculation of temporal variations of the refreezing were probably due to the uncertainties in the external forcing and simplification of snow processes in the model. The modelled snow thickness was sensitive to the atmospheric forcing, and the influence was amplified when the albedo was parameterized as a function of surface temperature. In the sensitivity tests without this feedback, the direct effect of the inaccuracy in the albedo parameterization was minor. Errors in the parameterized longwave radiation were critical for the modelled snow surface temperature during night-time, but did not have a large effect on the mass balance during this spring melt period.

The one-dimensional snow model SNTHERM is validated using field measurements of snow and superimposed ice thickness and surface energy fluxes. These were performed during the spring-to-summer transition in Svalbard and in the Weddell Sea, Antarctica. Both the seasonal snow-thickness decrease and the formation of superimposed ice are well reproduced by the model. During the three observation periods, observed and modeled snow thickness differ only by 13.1–27.1mm on average. In regional studies, the model is forced with atmospheric re-analysis data (European Centre for Medium-Range Weather Forecasts) and applied to several meridional transects across the Arctic and Southern Ocean. These show fundamental regional differences in the onset, duration and magnitude of snow thinning in summer. In the central Arctic, snowmelt onset occurs within a narrow time range of ±11 days and without significant regional differences. In contrast, the snow cover on Antarctic sea ice begins to melt about 25 days earlier and the length of the Antarctic snow-thinning season increases with increasing latitude. The importance of melting and evaporation for the modeled snow-thickness decrease is very different in the two hemispheres. The ratio of evaporated snow mass to melted snow mass per unit area is derived from the model, and amounts to approximately 4.2 in the Antarctic and only 0.75 in the Arctic. This agrees with observations and model results of the surface energy balance, and illustrates the dominance of surface cooling by upward turbulent fluxes in the Antarctic.

Measurements made on first-year ice in the Arctic and sub-Arctic are used to show that ice from both regions decays in a similar manner during the spring/summer melt season. One notable difference is that melt-induced changes in sub-Arctic Labrador occur about 2 months earlier than in the Arctic. In both regions, the temperature and strength of the ice change gradually over the season, whereas the bulk salinity and thickness of the ice do not change substantially until later in the season, when the ice becomes isothermal at a temperature of –1.8˚C. Results show that the seasonal decrease in the strength of first-year sea ice and the temperature-induced increase in brine volume are correlated. Once the ice is devoid of salt in late summer, the air volume continues to increase but has minimal effect on the ice strength.

Based on studies in the Antarctic Oceans, the contribution of the snow cover to sea-ice growth has become of major interest. Snow can result in upward ice growth in contrast with ordinary downward congelation growth at the bottom. A sea-ice study was conducted to verify the upward ice growth found in a previous study and to investigate the relation between sea-ice growth and radar backscattering signature. Sea-ice samples collected at four points in Lützow-Holm Bay, Antarctica, from 1998 to 2003 are analyzed. Analyses of snow-/ice-gauge measurements, snow depth and ice structure reveal an extremely large amount of upward ice growth of up to 1.0 m during one full year compared with a slight amount of downward growth. The upward growth was caused mostly by snow ice and to a lesser extent by superimposed ice. The salinity profile remained unchanged, although the ice survived the summer melt season. Characteristics of superimposed ice such as salinity, δ18O values and structure were obliterated during the summer, implying complete melting or dissolution of the superimposed layer. The ERS-2 backscatter showed a remarkable annual variation: It had a minimum value in midsummer and increased abruptly to a maximum value in late summer, then decreasing gradually in wintertime. The relation of the backscatter coefficient to the growth and properties of the snow cover and sea ice are discussed.

Temperature profiles of first-year landfast sea ice have been recorded continuously over the 2003 winter growth season at McMurdo Sound, Antarctica. The temperature gradients in the ice were used to calculate the growth rate due to conductive heat flux, which is shown to account for only part of the total ice growth. Remaining ice growth must be due to a negative oceanic heat flux. Significantly, this oceanic heat flux is shown to occur episodically, sometimes with sustained daily rates in excess of –30Wm–2. There is no direct correlation between oceanic heat flux and water temperature. Times of increased oceanic heat flux do coincide with the appearance of platelet ice in cores, and appear to account for the growth of 35% of the total platelet ice depth measured in ice cores.

Antarctic fast-ice variation is investigated using satellite images and ship’s ice navigation logs, focusing on break-up phenomena in Lützow-Holm Bay. Although spatio-temporal scales for breakup events vary somewhat for each event, their commencement is generally in autumn and almost always in the same region. Specifically, the 1997/98 break-up event occurred over a wide area and continued for a long time after the initial break-up. Since then, break-ups have recurred until 2004, and a total of 20 annual events have been detected and monitored since 1980. Moreover, information from icebreaker navigation logs shows that unstable fast-ice conditions occurred in the 1980s and after the late 1990s. From the analysis of surface meteorological data and the offshore pack-ice distribution, anomalously shallow snow-cover depths and a peculiar retreat pattern of the ice edge are found to be factors that favour fast-ice break-up. The pack-ice distribution controls the propagation of ocean swell inside the bay; encroaching swells are likely to mechanically disintegrate fast-ice during autumn prior to the annual formation of the protective pack-ice cover to the north. Less snow cover also leads to fast-ice weakening as the melt season progresses and broken floes are then transported offshore by prevailing southerly winds.

Massive tabular icebergs (∽1000km2 surface area, ∽1011 kg mass) arrived in the southwest Ross Sea in early 2001 where they remained relatively immobile for the next 4 years. During the period of their presence, extensive landfast sea ice (fast ice) waxed and waned along the Victoria Land coast, with maximum coverage exceeding typical coverage prior to the arrival of the icebergs by a factor of 5. The purposes of this study are to determine (1) whether the extensive ‘iceberg blockade’ extending from Ross Island to Drygalski Ice Tongue was indeed, as intuition suggests, responsible for the unusual fast-ice conditions, and (2) how storm frequency, intensity and seasonal timing may have mitigated the effects of the icebergs. Our simple analysis of glaciological and atmospheric conditions observed during 2001–05 suggests that iceberg movement alone is not sufficient to explain fast-ice variability; and, in fact, it is the detailed interplay between storms and iceberg location that determine this variability.

The amount of ice growth and ablation are key measures of the thermodynamic state of the ice cover. While ice extent and even ice thickness can be determined using remote-sensing techniques, this is not the case for the mass balance. Mass-balance measurements require an ability to attribute the change, establishing whether a change in the thickness of the ice cover occurs at the top or bottom surface and whether it is a result of growth or ablation. We have developed and implemented a tool that can be used to measure thermodynamic changes in sea-ice mass balance at individual locations: the ice mass-balance buoy (IMB). The primary limitation of the IMB is that it provides a point measurement of the ice mass balance, defined by a particular combination of snow and ice conditions. Determining if, and how, such point measurements can be extrapolated is critical to understanding the large-scale mass balance of the sea-ice cover. We explore the potential for extrapolation using mass-balance observations from the Surface Heat Budget of the Arctic (SHEBA) field experiment. During SHEBA, mass-balance measurements were made at over 100 sites covering a 100 km2 area. Results indicate that individual point measurements can provide reasonable estimates for undeformed and unponded multi-year ice, which represented more than two-thirds of the ice cover at SHEBA and is the dominant ice type in the perennial pack. A key is carefully selecting a representative location for the instrument package. The contribution of these point measurements can be amplified by integrating them with other tools designed to measure ice thickness and assimilating these combined data into sea-ice models.

We present results from a comprehensive field study carried out near Barrow, Alaska, USA, designed to characterize local- to intermediate-scale sea-ice processes in the Arctic coastal zone of central importance to the annual cycle and evolution of the coastal sea ice. Included in this are the behavior of the snow cover of the ice and adjacent tundra and lake system; concurrent studies of mass balance of the sea ice and lake ice; interaction of shortwave radiation with the shore-fast ice and the adjacent land surfaces; evolution of the area coverage and distribution of the various surface types; and the resulting regional albedo values. Maximum snow depths decreased during 2000–02 from 0.38 m to 0.26 m. Ice-melt rates in 2001 were 0.05 and 0.028md–1 at the top and bottom of the sea ice respectively, two to three times larger than observations from the central Arctic. Detailed surface results combined with aircraft photography were used to calculate regional albedos for the late spring and early summer of 2001. Values ranged from 0.8 for all cold snow-covered surfaces to approximately 0.4 for melting sea ice and lake ice vs 0.18 for bare tundra. Regional and surface-based values of cumulative shortwave radiation entering the ice were consistent, indicating that albedo sampling on a scale of 200m can provide a useful representation for regional sea-ice albedo.

In April 2004 the Royal Navy submarine HMS Tireless became the first UK submarine to conduct environmental monitoring in the Arctic Ocean since 1996. As the last US SCICEX (Scientific Ice Expeditions) cruise was in 2000, this has been the only opportunity for a civilian scientist to carry out measurement of ice draft and oceanography over a wide area of the Arctic. This paper presents preliminary results and compares them with similar investigations in the 1970s–90s. The route of Tireless covered a large area of the European sector of the Arctic from 5˚E to 62˚W. Transects were carried out from the marginal ice zone in Fram Strait up to the North Pole and along the 85˚N parallel north of Greenland. As part of work for the European Commission IRIS project, image intensity from the advanced synthetic aperture radar instrument on the European Space Agency’s Envisat satellite has been compared with ice draft from the submarine. The raw data were found to be highly variable, so a moving average was applied, producing a correlation of 0.79. Tireless carried a full oceanographic sensor suite and expendable probes for investigation into changes in the Arctic Ocean. The results from these show further erosion of the Arctic cold halocline layer by advancing Atlantic Water compared to previous climatologies and fieldwork expeditions. Preliminary ice-draft data from 85˚N show deeper ice keels than those encountered by a submarine on the same route in 1987.

Recent observational and modeling studies indicate that the Arctic sea-ice cover is undergoing significant climate-induced changes, affecting both its extent and thickness. The thickness or, more precisely, the mass balance of the ice cover is a key climate-change indicator since it is an integrator of both the surface heat budget and the ocean heat flux. Accordingly, efforts are underway to develop and deploy in situ observing systems which, when combined with satellite remote-sensing information and numerical models, can effectively monitor and attribute changes in the mass balance of the Arctic sea-ice cover. As part of this effort, we have developed an autonomous ice mass-balance buoy (IMB), which is equipped with sensors to measure snow accumulation and ablation, ice growth and melt, and internal ice temperature, plus a satellite transmitter. The IMB is unique in its ability to determine whether changes in the thickness of the ice cover occur at the top or bottom of the ice cover, and hence provide insight into the driving forces behind the change. Since 2000, IMBs have been deployed each spring from the North Pole Environmental Observatory and in several other areas, including a few in the Beaufort Sea and Central Basin. At this point, the collective time series is too short to draw significant and specific conclusions regarding interannual and regional variability in ice mass balance. Comparisons of available data indicate that ice surface ablation is greater in the Beaufort region (67–80 cm), relative to the North Pole (0–30 cm), consistent with a longer period of melt in the more southerly location. Ablation at the bottom of the ice (22 cm), maximum ice thickness (235 cm) and maximum snow depth (28 cm) were comparable in the two regions.

During March 2003, Autosub, an autonomous underwater vehicle (AUV) operated by the UK National Oceanography Centre, Southampton, was deployed under Sea ice north of Thurston Island, Amundsen Sea, Antarctica (at ∽71˚ S, 100˚ W). The vehicle was fitted with an upward-looking 300 kHz acoustic Doppler current profiler (ADCP) to provide current velocity above the AUV. The ADCP also recorded ranges to the ocean–ice interface. Such data can be used to derive Sea-ice draft by using a number of novel processing Steps Such as correcting for the coordinate Systems of the ADCP unit and the vehicle as well as corrections for changes in Sound Speed. This paper outlines the processing Stages required to obtain a probability density function (PDF) of Sea-ice draft and presents PDFs for the region north of Thurston Island. The distribution of ice draft was found to be unimodal, with modes between 2.2 and 2.4 m. Given the uncertainty in Sound Speed, the limit of accuracy was estimated as ∽6 cm.

Airborne, Ship-borne and Surface low-frequency electromagnetic (EM) methods have become widely applied to measure Sea-ice thickness. EM responses measured over Sea ice depend mainly on the Sea-water conductivity and on the height of the Sensor above the Sea-ice–sea-water interface, but may be Sensitive to the Sea-ice conductivity at high excitation frequencies. We have conducted in Situ measurements of direct-current conductivity of Sea ice using Standard geophysical geoelectrical methods. Sea-ice thickness estimated from the geoelectrical Sounding data was found to be consistently underestimated due to the pronounced vertical-to-horizontal conductivity anisotropy present in level Sea ice. At five Sites, it was possible to determine the approximate horizontal and vertical conductivities from the Sounding data. The average horizontal conductivity was found to be 0.017 Sm–1, and that in the vertical direction to be 9–12 times higher. EM measurements over level Sea ice are Sensitive only to the horizontal conductivity. Numerical modelling has Shown that the assumption of zero Sea-ice conductivity in interpretation of airborne EM data results in a negligible error in interpreted thickness for typical level Antarctic Sea ice.

Statistics of Arctic Sea-ice Surface roughness have been investigated in order to improve classification of ice-thickness regimes. The data consist of Surface roughness and thickness profiles, acquired Simultaneously by helicopter-borne laser altimetry and electromagnetic induction Sounding. Five thickness classes were identified using the modal thickness as a criterion. For each class, the Statistical properties of the Surface roughness profiles were analyzed. A classification algorithm was designed, which assigns profiles to the thickness classes on the basis of a Set of Selected Statistical roughness parameters. The algorithm was applied to profiles of different lengths. Best results were obtained for 2 km long profiles, for which it was possible to discriminate well between thick first-year and multi-year ice, and to distinguish these classes from thinner ice. The classification rule was tested on data obtained under winter and Summer conditions. The results Suggest that Statistical Surface roughness properties are different for thinner and thicker ice classes. However, individual thin-ice classes cannot be discriminated on the basis of the Selected roughness parameters.

Detailed measurements of Sea-ice thickness and Snow on Sea ice were recorded at different locations in fjords along the western coast of Spitsbergen, the largest island in the Svalbard archipelago, in 2004. Data corresponding to the ice Situation before and after melt onset were collected for Kongsfjorden and Van Mijenfjorden, while Hornsund was investigated once during early Spring. Profiles of total thickness (snow plus ice thickness) were measured, together with Some Snow-thickness measurements. Total thicknesses were measured with a portable electromagnetic instrument and at Selected Sites by drilling. The three fjords Show Some differences in measured thicknesses, connected to individual conditions. However, total thickness does not differ Substantially between the three fjords before melt onset. The modal total thickness for all three fjords before melt onset was 1.075 m, and the corresponding modal Snow thickness was 0.225 m (bin width 0.05 m). Long-term Kongsfjorden ice-thickness data Since 1997 Show that the maximum ice thickness varies Significantly interannually, as observed at other Arctic Sites. The average maximum ice thickness for Kongsfjorden was 0.71 m (years 1997–98, 2000 and 2002–05), and the respective average maximum Snow thickness was 0.22 m. In Kongsfjorden, 2004 was the year with highest maximum total thickness and Snow thickness relative to the other years.

Electromagnetic–induction (EM) instruments can be used to estimate Sea-ice thickness because of the large contrast in the conductivities of Sea ice and Sea water, and are currently used in investigations of Sea-ice thickness. In this Study we analyze Several Snow, ice and Sea-water Samples and attempt to derive an appropriate formula to transform the apparent conductivity obtained from EM measurements to the total thickness of Snow and ice for all regions and Seasons. This was done to Simplify the EM tuning procedure. Surface EM measurement transects with the instrument at varying heights above the ice were made in the Chukchi Sea, off East Antarctica, in the Sea of Okhotsk and in Saroma-ko (lagoon). A Standardized transformation formula based on a one-dimensional multi-layer model was developed that also considers the effects of water-filled gaps between deformed ice, a Saline Snow Slush layer, and the increase in the footprint Size caused by increasing the instrument height. The overall average error in ice thickness determined with the Standardized transform was <7%, and the regional average errors were 2.2% for the Arctic, 7.0% for the Antarctic, 6.5% for the Sea of Okhotsk and 4.4% for Saroma-ko.

Results of helicopter-borne electromagnetic measurements of total (ice plus Snow) Sea-ice thickness performed in May 2004 and 2005 in the Lincoln Sea and adjacent Arctic Ocean up to 86˚N are presented. Thickness distributions South of 84˚N are dominated by multi-year ice with modal thicknesses of 3.9 m in 2004 and 4.2 m in 2005 (mean thicknesses 4.67 and 5.18 m, respectively). Modal and mean Snow thickness on multi-year ice amounted to 0.18 and 0.30 m in 2004, and 0.28 and 0.35 m in 2005. There are also considerable amounts of 0.9–2.2m thick first-year ice (modal thickness), mostly representing ice formed in the recurring, refrozen Lincoln Polynya. Results are in good agreement with ground-based electromagnetic thickness measurements and with ice types demarcated in Satellite Synthetic aperture radar imagery. Four drifting buoys deployed in 2004 between 86˚N and 84.5˚N Show a Similar pattern of a mean Southward drift of the ice pack of 83 ±18km between May 2004 and April 2005, towards the coast of Ellesmere Island and Nares Strait. The resulting area decrease of 26% between the buoys and the coast is larger than the observed thickness increase South of 84˚ N. This points to the importance of Shear in a narrow band along the coast, and of ice export through Nares Strait in removing ice from the Study region.