Digital elevation model (DEM) of the ice sheet in western Dronning Maud Land, Antarctica

In this paper, a new digital elevation model (DEM) is derived for the ice sheet in western Dronning Maud Land, Antarctica. It is based on differential interferometric synthetic aperture radar (SAR) from the European Remote Sensing 1/2 (ERS-1/2) satellites, in combination with ICESat's Geoscience Laser Altimeter System (GLAS). A DEM mosaic is compiled out of 116 scenes from the ERS-1 ice phase in 1994 and the ERS-1/2 tandem mission between 1996 and 1997 with the GLAS data acquired in 2003 that served as ground control. Using three different SAR processors, uncertainties in phase stability and baseline model, resulting in height errors of up to 20 m, are exemplified. Atmospheric influences at the same order of magnitude are demonstrated, and corresponding scenes are excluded. For validation of the DEM mosaic, covering an area of about 130,000 km**2 on a 50-m grid, independent ICESat heights (2004-2007), ground-based kinematic GPS (2005), and airborne laser scanner data (ALS, 2007) are used. Excluding small areas with low phase coherence, the DEM differs in mean and standard deviation by 0.5 +/- 10.1, 1.1 +/- 6.4, and 3.1 +/- 4.0 m from ICESat, GPS, and ALS, respectively. The excluded data points may deviate by more than 50 m. In order to suppress the spatially variable noise below a 5-m threshold, 18% of the DEM area is selectively averaged to a final product at varying horizontal spatial resolution. Apart from mountainous areas, the new DEM outperforms other currently available DEMs and may serve as a benchmark for future elevation models such as from the TanDEM-X mission to spatially monitor ice sheet elevation.

Three time-slice simulations of the Eemian (eem), the mid-Holocene (hol), and a pre-industrial (pri) control run with the coupled atmosphere-ocean-model ECHAM5/MPI-OM

Orbital forcing does not only exert direct insolation effects, but also alters climate indirectly through feedback mechanisms that modify atmosphere and ocean dynamics and meridional heat and moisture transfers. We investigate the regional effects of these changes by detailed analysis of atmosphere and ocean circulation and heat transports in a coupled atmosphere-ocean-sea ice-biosphere general circulation model (ECHAM5/JSBACH/MPI-OM). We perform long term quasi equilibrium simulations under pre-industrial, mid-Holocene (6000 years before present - yBP), and Eemian (125 000 yBP) orbital boundary conditions. Compared to pre-industrial climate, Eemian and Holocene temperatures show generally warmer conditions at higher and cooler conditions at lower latitudes. Changes in sea-ice cover, ocean heat transports, and atmospheric circulation patterns lead to pronounced regional heterogeneity. Over Europe, the warming is most pronounced over the north-eastern part in accordance with recent reconstructions for the Holocene. We attribute this warming to enhanced ocean circulation in the Nordic Seas and enhanced ocean-atmosphere heat flux over the Barents Shelf in conduction with retreat of sea ice and intensified winter storm tracks over northern Europe.

Ice and chlorophyll a concentration and mesozooplankton characteristics during two 'On Thin Ice' cruises, northern Svalbard waters

The spatial variation in mesozooplankton biomass, abundance and species composition in relation to oceanography was studied in different climatic regimes (warm Atlantic vs. cold Arctic) in northern Svalbard waters. Relationships between the zooplankton community and various environmental factors (salinity, temperature, sampling depth, bottom depth, sea-ice concentrations, algal biomass and bloom stage) were established using multivariate statistics. Our study demonstrated that variability in the physical environment around Svalbard had measurable effect on the pelagic ecosystem. Differences in bottom depth and temperature-salinity best explained more than 40% of the horizontal variability in mesozooplankton biomass (DM/m**2) after adjusting for seasonal variability. Salinity and temperature also explained much (21% and 15%, respectively) of the variability in mesozooplankton vertical distribution (ind./m**3) in August. Algal bloom stage, chlorophyll-a biomass, and depth stratum accounted for additional 17% of the overall variability structuring vertical zooplankton distribution. Three main zooplankton communities were identified, including Atlantic species Fritillaria borealis, Oithona atlantica, Calanus finmarchicus, Themisto abyssorum and Aglantha digitale; Arctic species Calanus glacialis, Gammarus wilkitzkii, Mertensia ovum and Sagitta elegans; and deeper-water inhabitants Paraeuchaeta spp., Spinocalanus spp., Aetideopsis minor, Mormonilla minor, Scolecithricella minor, Gaetanus (Gaidius) tenuispinus, Ostracoda, Scaphocalanus brevicornis and Triconia borealis. Zooplankton biomasses in Atlantic- and Arctic-dominated water masses were similar, but biological ''hot-spots'' were associated with Arctic communities.

Sea ice draft measured by upward looking sonars in the Weddell Sea (Antarctica)

The presented database contains time-referenced sea ice draft values from upward looking sonar (ULS) measurements in the Weddell Sea, Antarctica. The sea ice draft data can be used to infer the thickness of the ice. They were collected during the period 1990-2008. In total, the database includes measurements from 13 locations in the Weddell Sea and was generated from more than 3.7 million measurements of sea ice draft. The files contain uncorrected raw drafts, corrected drafts and the basic parameters measured by the ULS. The measurement principle, the data processing procedure and the quality control are described in detail. To account for the unknown speed of sound in the water column above the ULS, two correction methods were applied to the draft data. The first method is based on defining a reference level from the identification of open water leads. The second method uses a model of sound speed in the oceanic mixed layer and is applied to ice draft in austral winter. Both methods are discussed and their accuracy is estimated. Finally, selected results of the processing are presented.