Petra Heil

The pattern and variability of Antarctic sea-ice drift in the Indian Ocean and western Pacific sectors

Sea-ice drift physically redistributes pack ice and changes ice extent, concentration, and, through deformation, the ice-thickness distribution. In this paper, data are presented from 39 satellite-tracked buoys, deployed during various seasons from 1985 to 1996 in the sea ice of the Southern Ocean off East Antarctica between 20° and 160°E longitude. The dominant features of the ice motion in the region are a westward drift parallel to the bathymetry near the Antarctic continent, a cyclonic circulation cell in Prydz Bay, and eastward drift of the ice to the north of the zonal shear zone. The oceanic circulation along the coast is generally barotropic and the ice drift is well correlated with bottom topography. Northward outflows, the locations of which are determined by both bottom topography and the seasonally varying position of the zonal shear zone, allow the discharge of sea ice from the westward drift in the south into the northerly belt of eastward flow, but with considerable variability in the net northward ice transport. The ice translation monitored by the buoys is used to derive the spatial pattern of the ice-velocity field. The daily average ice-drift speed in the westward flow is 0.23 m s−1 (19.8 km d−1), with considerable spatial and temporal variability, and in the eastward flow the average is 0.17 m s−1 (15.1 km d−1). Seasonal and interannual ice-drift variabilities are analyzed. The results are compared with satellite data of sea-ice extent and concentration over the same time, as well as with hydrographic observation of the position of the Antarctic Divergence.

Modeling the High-Frequency Component of Arctic Sea Ice Drift and Deformation

Abstract Buoy observations of sea ice drift show that sea ice motion and deformation contain substantial high-frequency variability at subdaily timescales. However, numerical simulations of the sea ice dynamics normally do not include processes on such short timescales. Instead, by applying traditional water-drag formulations for the ocean–sea ice boundary layer, the inertial frequencies tend to be omitted in the spectra of modeled sea ice motion and deformation due to fictitious ocean damping. Here a dynamic–thermodynamic sea ice model is presented that includes “inertial embedding” of the sea ice into the oceanic boundary layer to reproduce sea ice motion and deformation not only at daily and lower frequencies but also at subdaily frequencies up to 2 cycles per day and higher. Comparison with buoy data shows that the embedded model much more successfully simulates the observed sea ice motion in regard to the high-frequency component. The results demonstrate that both inertial embedding of the sea ice–oc...

Seasonal and interannual variations of the oceanic heat flux under a landfast Antarctic sea ice cover

A multilayer thermodynamic model is used to simulate sea ice growth for 12 years between 1958 and 1986 in the vicinity of the Australian station Mawson on the coast of East Antarctica. The atmospheric forcing data for the model are derived from radiosonde profiles and from surface measurements. Global radiation data are available for 4 years, and we use these measurements for comparison with the results of a Zillman-type model for global radiation. Combining the thermodynamic model with sea ice thickness measurements for 12 years, we solve the energy balance equation for the oceanic heat flux. The oceanic heat flux is not constant but changes with time within the year and from year to year. The oceanic heat flux averages 7.9 W/m2, and the yearly means vary between 5 and 12 W/m2. Seasonal values of the oceanic heat flux range from 0 to 18 W/m2. From the yearly averaged values a decadal trend is evident: During the first years that were analyzed the yearly average lies well above 10 W/m2; then in the mid-1970s a decrease to 9 W/m2 occurs, while for all later years the values are ∼6–8 W/m2. In general, the oceanic heat flux increases from the start of the fast ice formation season in early April until it breaks out in December or January. To compare the calculated oceanic heat fluxes for different years, we divide the total ice season into three characteristic time regimes of the sea ice growth and calculate the averaged oceanic heat fluxes for each regime. For the first regime (through August) the mean flux is 2.7 W/m2, for the middle regime (September) it is 8.4 W/m2, and for the final regime (October–January) it is 17 W/m2. We discuss the results of our model calculations in conjunction with current meter observations, which give evidence of seasonally varying intrusions of relatively warm Circumpolar Deep Water into Prydz Bay. Comparison of passive microwave data of sea ice extent and concentration (from the scanning multichannel microwave radiometer sensor) with the model results reveals a correlation between the magnitude of the oceanic heat flux and local features such as polynyas.

Modeling Linear Kinematic Features in Sea Ice

Abstract Sea ice deformation is localized in narrow zones of high strain rate that extend hundreds of kilometers, for example, across the Arctic Basin. This paper demonstrates that these failure zones may be modeled with a viscous–plastic sea ice model, using an isotropic rheology. If the ice is assumed to be heterogeneous at the grid scale, and allowed to weaken in time, intersecting failure zones propagate across the region. The direction of failure propagation depends upon the stress applied to the ice (wind stress and boundary conditions) and the rheological model describing plastic failure of the ice. The spacing between failure zones is controlled by the magnitude of the wind stress and the distribution describing spatial variability of ice strength. Sea ice motion and deformation oscillate at close to a 12-h period throughout the Arctic and Antarctic pack ice. This oscillation is found at all spatial scales from hundreds of kilometers to the lead scale. It is shown that with an inertial embedded mo...

Beyond point measurements: sea ice floes characterized in 3-D

A new methodology for coincident floe-scale measurements of the surface elevation, snow depth, and ice draft (the thickness below the water line) of Antarctic sea ice has been demonstrated during two recent research voyages: the Australian-led Sea Ice Physics and Ecosystem Experiment II (SIPEX II) to East Antarctica in September–November 2012 and the United Kingdom–led Ice Mass Balance in the Bellingshausen Sea (ICEBell) voyage to the Weddell and Bellingshausen Seas in November 2010

Multiyear sea ice thermal regimes and oceanic heat flux derived from an ice mass balance buoy in the Arctic Ocean

The conductive and oceanic heat fluxes and the mass balance of sea ice were investigated utilizing an ice mass balance buoy (IMB) deployed in the Arctic Ocean. After IMB deployment, the ice thinned from 1.95 m in late August to 1.46 m by mid-October 2008. From then on, ice growth until mid-June 2009 increased the ice thickness to 3.12 m. The ice temperature and consequently the conductive heat flux at the ice surface exhibited persistent high-frequency variations due to diurnal and synoptic-scale atmospheric forcing. These signals propagated downward with damped magnitude and temporal lag. The competition of oceanic and conductive heat flux dominated the low-frequency variations of ice growth. However, high-frequency variations in ice growth were controlled largely by the oceanic heat flux. From mid-November 2008 to mid-June 2009, the average oceanic heat flux along a track from 86.2° N, 115.2° W to 84.6° N, 33.9° W was 7.1 W/m2. This was in agreement with that derived from an IMB deployed in 2005, about 1.5° to the north of our buoy. We attributed the relatively high oceanic heat flux (10-15 W/m2) observed during autumn and early winter to summer warming of the surface ocean. Upward mixing of warm deep water, as observed when our buoy drifted over the shallow region of the Lomonosov Ridge (85.4°-85.9° N, 52.2°-66.4° W), demonstrated the impact of bathymetry on the oceanic heat flux under ice cover, and consequently on the basal ice mass balance. ©2013. American Geophysical Union. All Rights Reserved.

Characterization of sea-ice kinematic in the Arctic outflow region using buoy data

Data from four ice-tethered buoys deployed in 2010 were used to investigate sea-ice motion and deformation from the Central Arctic to Fram Strait. Seasonal and long-term changes in ice kinematics of the Arctic outflow region were further quantified using 42 ice-tethered buoys deployed between 1979 and 2011. Our results confirmed that the dynamic setting of the transpolar drift stream (TDS) and Fram Strait shaped the motion of the sea ice. Ice drift was closely aligned with surface winds, except during quiescent conditions, or during short-term reversal of the wind direction opposing the TDS. Meridional ice velocity south of 85°N showed a distinct seasonal cycle, peaking between late autumn and early spring in agreement with the seasonality of surface winds. Inertia-induced ice motion was strengthened as ice concentration decreased in summer. As ice drifted southward into the Fram Strait, the meridional ice speed increased dramatically, while associated zonal ice convergence dominated the ice-field deformation. The Arctic atmospheric Dipole Anomaly (DA) influenced ice drift by accelerating the meridional ice velocity. Ice trajectories exhibited less meandering during the positive phase of DA and vice versa. From 2005 onwards, the buoy data exhibit high Arctic sea-ice outflow rates, closely related to persistent positive DA anomaly. However, the long-term data from 1979 to 2011 do not show any statistically significant trend for sea-ice outflow, but exhibit high year-to-year variability, associated with the change in the polarity of DA.

Seasonal evolution of an ice‐shelf influenced fast‐ice regime, derived from an autonomous thermistor chain

Ice shelves strongly interact with coastal Antarctic sea ice and the associated ecosystem by creating conditions favorable to the formation of a sub-ice platelet layer. The close investigation of this phenomenon and its seasonal evolution remains a challenge due to logistical constraints and a lack of suitable methodology. In this study, we characterize the seasonal cycle of Antarctic fast ice adjacent to the Ekstrom Ice Shelf in the eastern Weddell Sea. We used a thermistor chain with the additional ability to record the temperature response induced by cyclic heating of resistors embedded in the chain. Vertical sea-ice temperature and heating profiles obtained daily between November 2012 and February 2014 were analyzed to determine sea-ice and snow evolution, and to calculate the basal energy budget. The residual heat flux translated into an ice-volume fraction in the platelet layer of 0.18 ± 0.09, which we reproduced by a independent model simulation and agrees with earlier results. Manual drillings revealed an average annual platelet-layer thickness increase of at least 4 m, and an annual maximum thickness of 10 m beneath second-year sea ice. The oceanic contribution dominated the total sea-ice production during the study, effectively accounting for up to 70% of second-year sea-ice growth. In summer, an oceanic heat flux of 21 W m−2 led to a partial thinning of the platelet layer. Our results further show that the active heating method, in contrast to the acoustic sounding approach, is well suited to derive the fast-ice mass balance in regions influenced by ocean/ice-shelf interaction, as it allows subdiurnal monitoring of the platelet-layer thickness.

Sea-ice conditions in the Adélie Depression, Antarctica, during besetment of the icebreaker RV Xuelong

Abstract During the 30th Chinese Antarctic Expedition in 2013/14, the Chinese icebreaker RV Xuelong answered a rescue call from the Russian RV Akademik Shokalskiy. While assisting the repatriation of personnel from the Russian vessel to the Australian RV Aurora Australis, RV Xuelong itself became entrapped within the compacted ice in the Adélie Depression region. Analysis of MODIS and SAR imagery provides a detailed description of the regional sea-ice conditions which led to the 6 day long besetment of RV Xuelong. The remotely sensed imagery revealed four stages of sea-ice characteristics during the entrapment: the gathering, compaction, dispersion and calving stages. Four factors characterizing the local sea-ice conditions during late December 2013 and early January 2014 were identified: surface component of the coastal current; near-surface wind; ocean tides; and surface air temperature. This study demonstrates that shipping activity in ice-invested waters should be underpinned by general knowledge of the ice situation. In addition, during such activity high spatiotemporal resolution remotely sensed data should be acquired regularly to monitor local and regional sea-ice changes with a view to avoiding the besetment of vessels.

Satellite-Based Sea Ice Navigation for Prydz Bay, East Antarctica

Sea ice adversely impacts nautical, logistical and scientific missions in polar regions. Ship navigation benefits from up-to-date sea ice analyses at both regional and local scales. This study presents a satellite-based sea ice navigation system (SatSINS) that integrates observations and scientific output from remote sensing and meteorological data to develop optimum marine navigational routes in sea ice-covered waters, especially in areas where operational ice information is usually scarce. The system and its applications are presented in the context of a decision-making process to optimize the routing of the RV Xuelong during her passage through Prydz Bay, East Antarctica during three trips in the austral spring of 2011–2013. The study assesses scientifically-generated remote sensing ice parameters for their operational use in marine navigation. Evaluation criteria involve identification of priority parameters, their spatio-temporal requirements in relation to navigational needs, and their level of accuracy in conjunction with the severity of ice conditions. Coarse-resolution ice concentration maps are sufficient to delineate ice edge and develop a safe route when ice concentration is less than 70%, provided that ice dynamics, estimated from examining the cyclonic pattern, is not severe. Otherwise, fine-resolution radar data should be used to identify and avoid deformed ice. Satellite data lagging one day behind the actual location of the ship was sufficient in most cases although the proposed route may have to be adjusted. To evaluate the utility of SatSINS, deviation of the actual route from the proposed route was calculated and found to range between 165 m to about 16.0 km with standard deviations of 2.8–6.1 km. Growth of land-fast ice has proven to be an essential component of the system as it was estimated using a thermodynamic model with input from a meteorological station.