Polyaromatic hydrocarbons in sediments from the Barents and White Seas

Polycyclic aromatic hydrocarbons (PAHs) are common environmental contaminants which can be derived from anthropogenic sources, such as combustion and discharges from extraction and transport, and natural processes, including leakage and erosion of fossil carbon. Natural PAH sources contribute, along with biological activities and terrestrial run-off, to the organic carbon content in sediments.The Barents Sea region is far from many anthropogenic sources of PAH, but production and trans-shipment of hydrocarbons is increasing. We present data for polycyclic aromatic hydrocarbon (PAH) concentrations in bottom sediments from 510 stations in the Barents and White Seas, and along the northern coast of Norway.

(Table 1) Annual melt rates of the South Branch of Jacobshavn Isbrae between July 1984-1985

Photogrammetric reanalysis of 1985 aerial photos has revealed substantial submarine melting of the floating ice tongue of Jakobshavn Isbrae, west Greenland. The thickness of the floating tongue determined from hydrostatic equilibrium tapers from ~940 m near the grounding zone to ~600 m near the terminus. Feature tracking on orthophotos shows speeds on the July 1985 ice tongue to be nearly constant (~18.5 m/d), indicating negligible dynamic thinning. The thinning of the ice tongue is mostly due to submarine melting with average rates of 228 ± 49 m/yr (0.62 ± 0.13 m/d) between the summers of 1984 and 1985. The cause of the high melt rate is the circulation of warm seawater (thermal forcing of up to 4.2°C) beneath the tongue with convection driven by the substantial discharge of subglacial freshwater from the grounding zone. We believe that this buoyancy-driven convection is responsible for a deep channel incised into the sole of the floating tongue. A dramatic thinning, retreat, and speedup began in 1998 and continues today. The timing of the change is coincident with a 1.1°C warming of deep ocean waters entering the fjord after 1997. Assuming a linear relationship between thermal forcing and submarine melt rate, average melt rates should have increased by ~25% (~57 m/yr), sufficient to destabilize the ice tongue and initiate the ice thinning and the retreat that followed.

Greenland and Antarctic ice sheet topography, cavity geometry, and global bathymetry (RTopo-2), links to NetCDF files

The ocean plays an important role in modulating the mass balance of the polar ice sheets by interacting with the ice shelves in Antarctica and with the marine-terminating outlet glaciers in Greenland. Given that the flux of warm water onto the continental shelf and into the sub-ice cavities is steered by complex bathymetry, a detailed topography data set is an essential ingredient for models that address ice-ocean interaction. We followed the spirit of the global RTopo-1 data set and compiled consistent maps of global ocean bathymetry, upper and lower ice surface topographies and global surface height on a spherical grid with now 30-arc seconds resolution. We used the General Bathymetric Chart of the Oceans (GEBCO, 2014) as the backbone and added the International Bathymetric Chart of the Arctic Ocean version 3 (IBCAOv3) and the Interna- tional Bathymetric Chart of the Southern Ocean (IBCSO) version 1. While RTopo-1 primarily aimed at a good and consistent representation of the Antarctic ice sheet, ice shelves and sub-ice cavities, RTopo-2 now also contains ice topographies of the Greenland ice sheet and outlet glaciers. In particular, we aimed at a good representation of the fjord and shelf bathymetry sur- rounding the Greenland continent. We corrected data from earlier gridded products in the areas of Petermann Glacier, Hagen Bræ and Sermilik Fjord assuming that sub-ice and fjord bathymetries roughly follow plausible Last Glacial Maximum ice flow patterns. For the continental shelf off northeast Greenland and the floating ice tongue of Nioghalvfjerdsfjorden Glacier at about 79°N, we incorporated a high-resolution digital bathymetry model considering original multibeam survey data for the region. Radar data for surface topographies of the floating ice tongues of Nioghalvfjerdsfjorden Glacier and Zachariæ Isstrøm have been obtained from the data centers of Technical University of Denmark (DTU), Operation Icebridge (NASA/NSF) and Alfred Wegener Institute (AWI). For the Antarctic ice sheet/ice shelves, RTopo-2 largely relies on the Bedmap-2 product but applies corrections for the geometry of Getz, Abbot and Fimbul ice shelf cavities.

Ensemble prediction distribution maps of macroalgae for current conditions and four climate change scenarios and high resultion bathymetry for Potter Cove, WAP, Antarctica

Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.