Geochemical and biogeochemical parameters of bottom sediments from the area of the Spitsbergen (Svalbard) Archipelago

Quantitative characteristics for rates of diagenetic processes in the upper (0-30 cm) layer of sedimentary deposits in the area of the Spitsbergen (Svalbard) Archipelago (78°-80°N) were obtained by lithologo-geochemical, radioisotope (35S, 14C), and stable isotope (d34S, d13C) studies. It was proved that rates of diagenetic processes in polar deposits at 123-395 m depth affected by the East Spitsbergen ''warm'' current are mostly determined by bioproductivity and are commensurate with rates of processes in shelf deposits of temperate latitudes. High contents of migratory methane (up to 263 ml/dm**3) and isotopically-light organic carbon (Corg, d13C = -30 per mil PDB) were found in the 1 m layer of shelf deposits (at 123 m sea depth) with low bacterial in situ production of methane. It was shown that methane is not utilized in the deposits by the methanotrophic bacterial community and it may be supplied to the water mass and, probably, to the atmosphere.

Hydro-sedimentary parameters measurements within the proglacial area of the Bossons glacier (Mont-Blanc massif, France)

This dataset presents hydro-sedimentary data within the Bossons glacier proglacial area. Bossons glacier is rapidly retreating and its proglacial area is deglaciated for ~ 30 years. It is an intriguing location to study periglacial, proglacial and subglacial erosion processes which requires estimating Total Dissolved Solid (TDS) and Total Suspended Solid (TSS) concentrations, and discharge. Measurements were performed at three distinct locations within Bosson glacier watershed : Bossons downstream (BDS), Bossons upstream (BUS) and Crosette (CRO). The latter is located at the glacier termini whereas BDS and BUS stations are farther downstream from the glacier, at 1.5 and 1.15 km, respectively .

Mean dynamic topography and oceanographic parameters estimated from an inverse model and satellite geodesy, with link to model result in one single NetCDF file (392 MB), including the inverse data error covariance

Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.