Sebastian Gerland

The physical environment of Kongsfjorden–Krossfjorden, an Arctic fjord system in Svalbard

Kongsfjorden-Krossfjorden and the adjacent West Spitsbergen Shelf meet at the common mouth of the two fjord arms. This paper presents our most up-to-date information about the physical environment of this fjord system and identifies important gaps in knowledge. Particular attention is given to the steep physical gradients along the main fjord axis, as well as to seasonal environmental changes. Physical processes on different scales control the large-scale circulation and small-scale (irreversible) mixing of water and its constituents. It is shown that, in addition to the tide, run-off (glacier ablation, snowmelt, summer rainfall and ice calving) and local winds are the main driving forces acting on the upper water masses in the fjord system. The tide is dominated by the semi-diurnal component and the freshwater supply shows a marked seasonal variation pattern and also varies interannually. The wind conditions are characterized by prevailing katabatic winds, which at times are strengthened by the geostrophic wind field over Svalbard. Rotational dynamics have a considerable influence on the circulation patterns within the fjord system and give rise to a strong interaction between the fjord arms. Such dynamics are also the main reason why variations in the shelf water density field, caused by remote forces (tide and coastal winds), propagate as a Kelvin wave into the fjord system. This exchange affects mainly the intermediate and deep water, which is also affected by vertical convection processes driven by cooling of the surface and brine release during ice formation in the inner reaches of the fjord arms. Further aspects covered by this paper include the geological and geomorphological characteristics of the Kongsfjorden area, climate and meteorology, the influence of glaciers, freshwater supply, sea ice conditions, sedimentation processes as well as underwater radiation conditions. The fjord system is assumed to be vulnerable to possible climate changes, and thus is very suitable as a site for the demonstration and investigation of phenomena related to climate change.

Comparison of sea-ice thickness measurements under summer and winter conditions in the Arctic using a small electromagnetic induction device

Drillhole-determined sea-ice thickness was compared with values derived remotely using a portable smalloffset loop-loop steady state electromagnetic (EM) induction device during expeditions to Fram Strait and the Siberian Arctic, under typical winter and summer conditions. Simple empirical transformation equations are derived to convert measured apparent conductivity into ice thickness. Despite the extreme seasonal differences in sea-ice properties as revealed by ice core analysis, the transformation equations vary little for winter and summer. Thus, the EM induction technique operated on the ice surface in the horizontal dipole mode yields accurate results within 5 to 10% of the drillhole determined thickness over level ice in both seasons. The robustness of the induction method with respect to seasonal extremes is attributed to the low salinity of brine or meltwater filling the extensive pore space in summer. Thus, the average bulk ice conductivity for summer multiyear sea ice derived according to Archie’s law amounts to 23 mS/m compared to 3 mS/m for winter conditions. These mean conductivities cause only minor differences in the EM response, as is shown by means of 1-D modeling. However, under summer conditions the range of ice conductivities is wider. Along with the widespread occurrence of surface melt ponds and freshwater lenses underneath the ice, this causes greater scatter in the apparent conductivity/ice thickness relation. This can result in higher deviations between EM-derived and drillhole determined thicknesses in summer than in winter.

Exploring Arctic Transpolar Drift During Dramatic Sea Ice Retreat

The Arctic is undergoing significant environmental changes due to climate warming. The most evident signal of this warming is the shrinking and thinning of the ice cover of the Arctic Ocean. If the warming continues, as global climate models predict, the Arctic Ocean will change from a perennially ice-covered to a seasonally ice-free ocean. Estimates as to when this will occur vary from the 2030s to the end of this century. One reason for this huge uncertainty is the lack of systematic observations describing the state, variability, and changes in the Arctic Ocean.

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.

Leads in Arctic pack ice enable early phytoplankton blooms below snow-covered sea ice

The Arctic icescape is rapidly transforming from a thicker multiyear ice cover to a thinner and largely seasonal first-year ice cover with significant consequences for Arctic primary production. One critical challenge is to understand how productivity will change within the next decades. Recent studies have reported extensive phytoplankton blooms beneath ponded sea ice during summer, indicating that satellite-based Arctic annual primary production estimates may be significantly underestimated. Here we present a unique time-series of a phytoplankton spring bloom observed beneath snow-covered Arctic pack ice. The bloom, dominated by the haptophyte algae Phaeocystis pouchetii, caused near depletion of the surface nitrate inventory and a decline in dissolved inorganic carbon by 16 ± 6 g C m−2. Ocean circulation characteristics in the area indicated that the bloom developed in situ despite the snow-covered sea ice. Leads in the dynamic ice cover provided added sunlight necessary to initiate and sustain the bloom. Phytoplankton blooms beneath snow-covered ice might become more common and widespread in the future Arctic Ocean with frequent lead formation due to thinner and more dynamic sea ice despite projected increases in high-Arctic snowfall. This could alter productivity, marine food webs and carbon sequestration in the Arctic Ocean.

Spectral reflectance of melting snow in a high Arctic watershed on Svalbard: some implications for optical satellite remote sensing studies

Field campaigns were undertaken in May and June of 1992 and 1997 in order to study spectral reflectance characteristics of snow during melt-off. The investigations were performed on snow-covered tundra at Ny-Alesund, Svalbard (79°N). Spectral measurements were acquired with spectroradiometers covering wavelengths from 350 to 2500 nm. Supporting measurements such as snow thickness, density, content of liquid water, grain size and shape, stratification of snowpack, as well as cloud observations and air temperature, were monitored throughout the field campaigns. Spectral measurements demonstrate that the near-infrared albedo is most affected by the ongoing snow metamorphism while the albedo in the visible wavelength range is more strongly affected by surface pollution. Comparisons of spectral measurements and spectrally integrated measurements emphasize the need for narrow-band to broad-band conversion when applying satellite-derived albedo to surface energy-balance calculations. As an example, Landsat TM Band 4 albedo is shown to produce slightly high albedo values compared to the spectrally integrated albedo (285–2800 nm). Daily albedo measurements from 1981–1997 show that the albedo normally drops from 80% to bare ground levels (∽10%) within two to four weeks and the date when the tundra becomes snow-free varies from early June to early July. Thus, the changing spectral characteristics of snow during melt-off combined with a general rapid decrease in albedo call for cautious use of satellite-derived albedo, especially when used as absolute numbers. Our data also illustrate the effect of cloud cover on surface albedo for an event in which the integrated albedo increased by 7% under cloudy conditions compared to clear skies without changes of surface properties. Finally, the reflectance of snow increases relative to nadir for measurements facing the sun and at azimuths 90° and 180° by 8, 15, 19, and 26% for viewing angles 15°, 30°, 45°, and 60°, respectively, due to anisotropic reflection. Copyright

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.

Snow research in Svalbard–an overview

This paper summarizes the most significant snow-related research that has been conducted in Svalbard. Most of the research has been performed during the 1990s and includes investigations of snow distribution, snow-melt, snow pack characteristics, remote sensing of snow and biological studies where snow conditions play an important role. For example, studies have shown regional trends with about 50% higher amounts of snow accumulation at the east coast of Spitsbergen compared to the west coast. Further, the accumulation rates are about twice as high in the south compared to the north. On average, the increase in accumulation with elevation is 97 mm water equivalents per 100 m increase in elevation. Several researchers reported melt rates, which are primarily driven by incoming short-wave radiation, in the range of 10-20 mm/day during spring. Maximum melt rates close to 70 mm/day have been measured. In addition to presenting an overview of research activities, we discuss new, unpublished results in areas where considerable progress is being made. These are i) modelling of snow distribution, ii) modelling of snowmelt runoff and iii) monitoring of snow coverage by satellite imagery. We also identify some weaknesses in current research activities. They are lacks of i) integration between various studies, ii) comparative studies with other Arctic regions, iii) applying local field studies in models that can be used to study larger areas of Svalbard and, finally, iv) using satellite remote sensing data for operational monitoring purposes.

Thickness and density of snow-covered sea ice and hydrostatic equilibrium assumption from in situ measurements in Fram Strait, the Barents Sea and the Svalbard coast

Abstract 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.

Surface albedo in Ny-Ålesund, Svalbard: variability and trends during 1981–1997

Abstract Since 1981, hourly values of albedo have been measured routinely at Norwegian Polar Institutes research station in Ny-Alesund, Svalbard. We have undertaken statistical analysis of the time series 1981–1997 to investigate potential long-term variability and trends in the albedo data set. The following questions have been raised and answered by regression analysis: (i) Has the time of beginning of snow melt changed? (ii) Have melt rates changed? (iii) Has the time of snow arrival in fall changed? (iv) Has the period without snow cover changed? The period without snow on the ground is studied because of its importance for tundra characteristics as a habitat for biota, e.g. length of the growth season. Our data show that albedo varies seasonally, with large variations in spring and autumn and much smaller variations in winter and summer. The variability is reasonably constant within each season. Density estimates of the albedo data suggest that the dates with highest likelihood for (i) start of snow melt and (ii) start of snow formation are 5th of June and 17th of September, respectively. Highest probability for the length of snow-free season is 94 days. None of the tests indicated any significant trends (or indications of climate change) in the 17-year record of albedo, that means that the four questions above were all answered by “no.” Correlation with the North Atlantic Oscillation (NAO) index is also investigated. No correlation between the NAO index and albedo nor temperature or precipitation was found. Even so, because of the short duration that our data set spans, we cannot rule out that such a correlation exists on decadal time scales.