Surface velocity fields, digital elevation models and ice front positions derived from multi-mission SAR remote sensing data at Sjögren Inlet glaciers, Antarctic Peninsula

Substantial retreat or disintegration of numerous ice shelves have been observed on the Antarctic Peninsula. The ice shelf in the Prince Gustav Channel retreated gradually since the late 1980's and broke-up in 1995. Tributary glaciers reacted with speed-up, surface lowering and increased ice discharge, consequently contributing to sea level rise. We present a detailed long-term study (1993-2014) on the dynamic response of Sjögren Inlet glaciers to the disintegration of Prince Gustav Ice Shelf. We analyzed various remote sensing datasets to observe the reactions of the glaciers to the loss of the buttressing ice shelf. A strong increase in ice surface velocities was observed with maximum flow speeds reaching 2.82±0.48 m/d in 2007 and 1.50±0.32 m/d in 2004 at Sjögren and Boydell glaciers respectively. Subsequently, the flow velocities decelerated, however in late 2014, we still measured about two times the values of our first measurements in 1996. The tributary glaciers retreated 61.7±3.1 km² behind the former grounding line of the ice shelf. In regions below 1000 m a.s.l., a mean surface lowering of -68±10 m (-3.1 m/a) was observed in the period 1993-2014. The lowering rate decreased to -2.2 m/a in recent years. Based on the surface lowering rates, geodetic mass balances of the glaciers were derived for different time steps. High mass loss rate of -1.21±0.36 Gt/a was found in the earliest period (1993-2001). Due to the dynamic adjustments of the glaciers to the new boundary conditions the ice mass loss reduced to -0.59±0.11 Gt/a in the period 2012-2014, resulting in an average mass loss rate of -0.89±0.16 Gt/a (1993-2014). Including the retreat of the ice front and grounding line, a total mass change of -38.5±7.7 Gt and a contribution to sea level rise of 0.061±0.013 mm were computed. Analysis of the ice flux revealed that available bedrock elevation estimates at Sjögren Inlet are too shallow and are the major uncertainty in ice flux computations. This temporally dense time series analysis of Sjögren Inlet glaciers shows that the adjustments of tributary glaciers to ice shelf disintegration are still going on and provides detailed information of the changes in glacier dynamics.

Inventory of thermo-erosional valleys and streams in three ice-rich permafrost lowlands adjacent to the Laptev Sea, with links to maps in ArcGIS format

This dataset provides an inventory of thermo-erosional landforms and streams in three lowland areas underlain by ice-rich permafrost of the Yedoma-type Ice Complex at the Siberian Laptev Sea coast. It consists of two shapefiles per study region: one shapefile for the digitized thermo-erosional landforms and streams, one for the study area extent. Thermo-erosional landforms were manually digitized from topographic maps and satellite data as line features and subsequently analyzed in a Geographic Information System (GIS) using ArcGIS 10.0. The mapping included in particular thermo-erosional gullies and valleys as well as streams and rivers, since development of all of these features potentially involved thermo-erosional processes. For the Cape Mamontov Klyk site, data from Grosse et al. [2006], which had been digitized from 1:100000 topographic map sheets, were clipped to the Ice Complex extent of Cape Mamontov Klyk, which excludes the hill range in the southwest with outcropping bedrock and rocky slope debris, coastal barrens, and a large sandy floodplain area in the southeast. The mapped features (streams, intermittent streams) were then visually compared with panchromatic Landsat-7 ETM+ satellite data (4 August 2000, 15 m spatial resolution) and panchromatic Hexagon data (14 July 1975, 10 m spatial resolution). Smaller valleys and gullies not captured in the maps were subsequently digitized from the satellite data. The criterion for the mapping of linear features as thermo-erosional valleys and gullies was their clear incision into the surface with visible slopes. Thermo-erosional features of the Lena Delta site were mapped on the basis of a Landsat-7 ETM+ image mosaic (2000 and 2001, 30 m ground resolution) [Schneider et al., 2009] and a Hexagon satellite image mosaic (1975, 10 m ground resolution) [G. Grosse, unpublished data] of the Lena River Delta within the extent of the Lena Delta Ice Complex [Morgenstern et al., 2011]. For the Buor Khaya Peninsula, data from Arcos [2012], which had been digitized based on RapidEye satellite data (8 August 2010, 6.5 m ground resolution), were completed for smaller thermo-erosional features using the same RapidEye scene as a mapping basis. The spatial resolution, acquisition date, time of the day, and viewing geometry of the satellite data used may have influenced the identification of thermo-erosional landforms in the images. For Cape Mamontov Klyk and the Lena Delta, thermo-erosional features were digitized using both Hexagon and Landsat data; Hexagon provided higher resolution and Landsat provided the modern extent of features. Allowance of up to decameters was made for the lateral expansion of features between Hexagon and Landsat acquisitions (between 1975 and 2000).

Surface velocity fields, digital elevation models, ice front positions and grounding line derived from remote sensing data at Dinsmoor-Bombardier-Edgeworth glacier system, Antarctic Peninsula (1992-2014)

The northern Antarctic Peninsula is one of the fastest changing regions on Earth. The disintegration of the Larsen-A Ice Shelf in 1995 caused tributary glaciers to adjust by speeding up, surface lowering, and overall increased ice-mass discharge. In this study, we investigate the temporal variation of these changes at the Dinsmoor-Bombardier-Edgeworth glacier system by analyzing dense time series from various spaceborne and airborne Earth observation missions. Precollapse ice shelf conditions and subsequent adjustments through 2014 were covered. Our results show a response of the glacier system some months after the breakup, reaching maximum surface velocities at the glacier front of up to 8.8 m/d in 1999 and a subsequent decrease to ~1.5 m/d in 2014. Using a dense time series of interferometrically derived TanDEM-X digital elevation models and photogrammetric data, an exponential function was fitted for the decrease in surface elevation. Elevation changes in areas below 1000 m a.s.l. amounted to at least 130±15 m130±15 m between 1995 and 2014, with change rates of ~3.15 m/a between 2003 and 2008. Current change rates (2010-2014) are in the range of 1.7 m/a. Mass imbalances were computed with different scenarios of boundary conditions. The most plausible results amount to -40.7±3.9 Gt-40.7±3.9 Gt. The contribution to sea level rise was estimated to be 18.8±1.8 Gt18.8±1.8 Gt, corresponding to a 0.052±0.005 mm0.052±0.005 mm sea level equivalent, for the period 1995-2014. Our analysis and scenario considerations revealed that major uncertainties still exist due to insufficiently accurate ice-thickness information. The second largest uncertainty in the computations was the glacier surface mass balance, which is still poorly known. Our time series analysis facilitates an improved comparison with GRACE data and as input to modeling of glacio-isostatic uplift in this region. The study contributed to a better understanding of how glacier systems adjust to ice shelf disintegration.

Downwelling spectral irradiance as measured in different depths, remote sensing reflectance and phytoplankton pigment concentration during POLARSTERN cruises ANT-XXIV/1, ANT-XXIV/4, ANT-XXVI/4 and Maria S. Merian cruise MSM18/3

The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

Horizontal profiles of longwave and shortwave radiation components over sea ice near Barrow, Alaska during the 2011 melt

An integrated instrument package for measuring and understanding the surface radiation budget of sea ice is presented, along with results from its first deployment. The setup simultaneously measures broadband fluxes of upwelling and downwelling terrestrial and solar radiation (four components separately), spectral fluxes of incident and reflected solar radiation, and supporting data such as air temperature and humidity, surface temperature, and location (GPS), in addition to photographing the sky and observed surface during each measurement. The instruments are mounted on a small sled, allowing measurements of the radiation budget to be made at many locations in the study area to see the effect of small-scale surface processes on the large-scale radiation budget. Such observations have many applications, from calibration and validation of remote sensing products to improving our understanding of surface processes that affect atmosphere-snow-ice interactions and drive feedbacks, ultimately leading to the potential to improve climate modelling of ice-covered regions of the ocean. The photographs, spectral data, and other observations allow for improved analysis of the broadband data. An example of this is shown by using the observations made during a partly cloudy day, which show erratic variations due to passing clouds, and creating a careful estimate of what the radiation budget along the observed line would have been under uniform sky conditions, clear or overcast. Other data from the setup's first deployment, in June 2011 on fast ice near Point Barrow, Alaska, are also shown; these illustrate the rapid changes of the radiation budget during a cold period that led to refreezing and new snow well into the melt season.

Abundance of Cnidaria and Ctenophora in the North Atlantic sampled during the G. O. Sars Cruise in May 2013

In recent years a global increase in jellyfish (i.e. Cnidarians and Ctenophores) abundance and a rise in the recurrence of jellyfish outbreak events have been largely debated, but a general consensus on this matter has not been achieved yet. Within this debate, it has been generally recognized that there is a lack of reliable data that could be analyzed and compared to clarify whether indeed jellyfish are increasing throughout the world ocean as a consequence of anthropogenic impact and hydroclimatic variability. During the G.O. Sars cruise jellyfish were collected at different depths in the 0-1000m layer using a standard 1 m**2 Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS) (quantitative data), Harstad and macroplankton trawls (qualitative data). The comparison of records collected with different nets during the G.O. Sars transatlantic cruise shows that different sampling gears might provide very different information on jellyfish diversity. Indeed, the big trawls mostly collect relatively large scyphozoan and hydrozoan species such as Atolla, Pelagia, Praya, Vogtia, while small hydrozoans (e.g. Clytia, Gilia, Muggiaea) and early stages of ctenophora are only caught by the smaller nets.

Physical properties of different sea ice types at ArcticNet, CFL and CASES ice stations, eastern Beaufort Sea

A study of the polarimetric backscattering response of newly formed sea ice types under a large assortment of surface coverage was conducted using a ship-based C-band polarimetric radar system. Polarimetric backscattering results and physical data for 40 stations during the fall freeze-up of 2003, 2006, and 2007 are presented. Analysis of the copolarized correlation coefficient showed its sensitivity to both sea ice thickness and surface coverage and resulted in a statistically significant separation of ice thickness into two regimes: ice less than 6 cm thick and ice greater than 8 cm thick. A case study quantified the backscatter of a layer of snow infiltrated frost flowers on new sea ice, showing that the presence of the old frost flowers can enhance the backscatter by more than 6 dB. Finally, a statistical analysis of a series of temporal-spatial measurements over a visually homogeneous frost-flower-covered ice floe identified temperature as a significant, but not exclusive, factor in the backscattering measurements.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) and Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic (2004-2012)

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2007

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Benthic carbon turnover, sediment pigment concentrations and sinking fluxes of POC in the southeastern Beaufort Sea during CCGS Amundsen cruise 2008

The effects of changing ice and atmospheric conditions on the upwelling of deep nutrient-laden waters and biological productivity in the coastal Beaufort Sea were quantified using a unique combination of in situ and remote-sensing approaches. Repeated instances of ice ablation and upwelling during fall 2007 and summer 2008 multiplied the production of ice algae, phytoplankton, zooplankton and benthos by 2 to 6 fold. Strong wind forcing failed to induce upward shifts in the biological productivity of stratified waters off the shelf.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2008

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.