Angelika Renner

Surface circulation at the tip of the Antarctic Peninsula from drifters

An array of 40 surface drifters, drogued at 15-m depth, was deployed in February 2007 to the east of the tip of the Antarctic Peninsula as part of the Antarctic Drifter Experiment: Links to Isobaths and Ecosystems (ADELIE) project. Data obtained from these drifters and from a select number of local historical drifters provide the most detailed observations to date of the surface circulation in the northwestern Weddell Sea. The Antarctic Slope Front (ASF), characterized by a ~20 cm s^(−1) current following the 1000-m isobath, is the dominant feature east of the peninsula. The slope front bifurcates when it encounters the South Scotia Ridge with the drifters following one of three paths. Drifters (i) are carried westward into Bransfield Strait; (ii) follow the 1000-m isobath to the east along the southern edge of the South Scotia Ridge; or (iii) become entrained in a large-standing eddy over the South Scotia Ridge. Drifters are strongly steered by contours of f /h (Coriolis frequency/depth) as shown by calculations of the first two moments of displacement in both geographic coordinates and coordinates locally aligned with contours of f /h. An eddy-mean decomposition of the drifter velocities indicates that shear in the mean flow makes the dominant contribution to dispersion in the along-f /h direction, but eddy processes are more important in dispersing particles across contours of f /h. The results of the ADELIE study suggest that the circulation near the tip of the Antarctic Peninsula may influence ecosystem dynamics in the Southern Ocean through Antarctic krill transport and the export of nutrients.

Evidence of Arctic sea ice thinning from direct observations

The Arctic sea ice cover is rapidly shrinking, but a direct, longer-term assessment of the ice thinning remains challenging. A new time series constructed from in situ measurements of sea ice thickness at the end of the melt season in Fram Strait shows a thinning by over 50% during 2003-2012. The modal and mean ice thickness along 79 degrees N decreased at a rate of 0.3 and 0.2 m yr(-1), respectively, with long-term averages of 2.5 and 3 m. Airborne observations reveal an east-west thickness gradient across the strait in spring but not in summer due to advection from more different source regions. There is no clear relationship between interannual ice thickness variability and the source regions of the ice. The observed thinning is therefore likely a result of Arctic-wide reduction in ice thickness with a potential shift in exported ice types playing a minor role.

Sea-ice mass-balance monitoring in an Arctic fjord

Abstract A sea-ice mass-balance monitoring study including ice extent and thickness observations was started at Kongsfjorden (79˚N, 12˚E), Svalbard, in 2003. The inner part of Kongsfjorden is usually covered by seasonal fast ice <1m thick, initially forming between December and March and persisting until June. Ice extent is visually observed from the mountain Zeppelinfjellet, and documented by ice maps and photographs several times a week. Ice and snow thickness is measured regularly at four sites from drillholes. Time series of ice extent in four areas east of Ny-Ålesund (total area 120 km2) were calculated for 2003–05. By combining extent with thickness data, ice-mass time series were calculated. As also observed earlier than 2003 in other studies, the fast ice varies interannually in extent and thickness. Among the factors which control the fast-ice evolution are physical and meteorological parameters, and the geographical setting of Kongsfjorden, with its coastline and a group of islands in its inner part having a protective effect. This study is ongoing and a major aim is to identify and quantify connections between the Kongsfjorden fast-ice evolution and climate parameters.

Floating ice-algal aggregates below melting arctic sea ice.

During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year.

Large-scale ice thickness distribution of first-year sea ice in spring and summer north of Svalbard

Abstract The large-scale thickness distribution of sea ice was measured during several campaigns in the European Arctic north of Svalbard from 2007 using an airborne electromagnetic induction device. In August 2010 and April-May 2011, this was complemented by extensive on-ice work including measurements of snow thickness and freeboard. Ice thicknesses show a clear difference between the seasons, with thicker ice during spring than in summer. In spring 2011, negative freeboard and flooding were observed as a result of the extensive snow cover. We find that the characteristics of the first-year sea ice allow combining observations from different years. The ice thickness in the marginal ice zone increases with increasing latitude and increasing distance to the ice edge; however, in the inner ice pack from ∼100 km from the ice edge the thickness remains almost constant. Modal ice thickness in spring reaches 2.4 m whereas in summer it is 1.0–1.4 m. Our study provides new insight into ice thickness distributions of a typical ice cover consisting of mainly first- and second-year ice, which may become the dominant ice type in the Arctic in the future.

Small-scale horizontal variability of snow, sea-ice thickness and freeboard in the first-year ice region north of Svalbard

Abstract Variability of sea-ice and snow conditions on the scale of a few hundred meters is examined using in situ measurements collected in first-year pack ice in the European Arctic north of Svalbard. Snow thickness and surface elevation measurements were performed in the standard manner using a snow stick and a rotating laser. Altogether, 4109 m of measurement lines were surveyed. The snow loading was large, and in many locations the ice freeboard was negative (38.8% of snowline measurements), although the modal ice and snow thickness was 1.8 m. The mean of all the snow thickness measurements was 36 cm, with a standard deviation of 26 cm. The mean freeboard was only 3 cm, with a standard deviation of 23 cm. There were noticeable differences in snow thickness among the measurement sites. Over the undeformed ice areas, the mean snow thickness and freeboard were 23 and 2.4 cm, respectively. Over the ridged ice areas, the mean freeboard was only –0.3 cm due to snow accumulation on the sails of ridges (average thickness 54 cm). These findings imply that retrieval algorithms for converting freeboard to ice thickness should take account of spatial variability of snow cover.

Sea-ice surface roughness estimates from airborne laser scanner and laser altimeter observations in Fram Strait and north of Svalbard

Abstract We present sea-ice surface roughness estimates, i.e. the standard deviation of relative surface elevation, in the Arctic regions of Fram Strait and the Nansen Basin north of Svalbard acquired by an airborne laser scanner and a single-beam laser altimeter in 2010. We compare the scanner to the altimeter and compare the differences between the two survey regions. We estimate and correct sensor roll from the scanner data using the hyperbolic response of the scanner over a flat surface. Measurement surveys had to be longer than 5 km north of Svalbard and longer than 15 km in Fram Strait before the statistical distribution in surface roughness from the scanner and altimeter became similar. The shape of the surface roughness probability distributions agrees with those of airborne electromagnetic induction measurements of ice thickness. The ice in Fram Strait had a greater mean surface roughness, 0.16 m vs 0.09 m, and a wider distribution in roughness values than the ice in the Nansen Basin. An increase in surface roughness with increasing ice thickness was observed over fast ice found in Fram Strait near the coast of Greenland but not for the drift ice.

Assessing polarimetric SAR sea-ice classifications using consecutive day images

Abstract This paper investigates automatic segmentation and classification of C-band, polarimetric synthetic aperture radar (SAR) satellite images of Arctic sea ice under freezing conditions prior to melt. The objective is to investigate the robustness of the results obtained under slightly varying environmental conditions and different viewing geometries. Initially, three geographically overlapping SAR images from consecutive days are incidence-angle corrected and segmented into unknown classes. The segmentation is performed by an unsupervised mixture-of-Gaussian segmentation algorithm utilizing six features extracted from the polarimetric data. After segmentation, the segments are contextually smoothed. One segmented image is manually labelled based on in situ data and expert knowledge. Using this scene as reference, we consider two strategies for class labelling of the other scenes. The first manually labels the classes based on visual inspection of the reference; the second utilizes various statistical distance measures to automatically assign each unknown class to the statistically nearest reference class. These two scenes are also classified pixel-wise by a supervised classification algorithm based on the reference data. Poor classification results are obtained when the incidence angle is very different from the reference scene. Similar viewing geometries reveal good classification and labelling results, the latter regardless of the distance measure used.

Effects of a Shallow Pycnocline and Surface Meltwater on Sea Ice-Ocean Drag and Turbulent Heat Flux

AbstractComprehensive boundary layer measurements from a drift station on first-year ice in the late summer of 2012 in the Nansen basin, when stable stratification in the upper ocean extended all the way to the surface, are analyzed. Observed quadratic ice–ocean drag coefficients, based on measurements of wind stress, are roughly 3.6 × 10−3, consistent with neutral-stability Rossby similarity scaling. The turning angles of 32°–39° between surface velocity and stress are larger than Rossby similarity predicts and obey a different scaling. This can be explained by the shallow pycnocline forcing the Ekman transport into a thin layer and modeled roughly employing a simple first-order correction to Rossby similarity. Turbulent shear stress in the ice–ocean boundary layer is on average 3 times smaller than the estimate based on wind stress, possibly because internal wave drag was significant. This lowers vertical scalar fluxes by 38% compared to a scenario where turbulent stress accounts for the total drag. The...

Spring sea-ice evolution in Rijpfjorden (80° N), Svalbard, from in situ measurements and ice mass-balance buoy (IMB) data

Abstract Rijpfjorden (808 N, 22° E) is a high-Arctic fjord on Nordaustlandet in the Svalbard archipelago. To monitor the thermodynamic change of sea ice in spring, an ice mass-balance buoy (IMB) was deployed for 2.5 months (10 April–26 June 2011), with accompanying in situ measurements, sea-ice sampling on three occasions and ice-core analysis. Uncertainties and sources of error in in situ measurements and IMB data are discussed. The in situ measurements, ice-core analysis and IMB data together depict the development of snow and ice in spring. Snow and ice thickness exhibited large spatial and temporal variability. After relatively stable conditions with only little change in ice thickness and accumulation of snow, a layer of superimposed ice ∼0.06 m thick formed at the snow-ice interface due to refreezing of snow meltwater in late spring. Ice thickness (except for growth of superimposed ice) did not change significantly based on in situ observations. In contrast, the under-ice sonar data from the IMB show reflections from a layer deeper than the underside of the ice during the melting phase. This can be explained as a reflection of the sonar pulses from an interface between a freshwater layer under the ice and more saline water below, or as a false-bottom formation.