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.

Compilation of scientific results of the OASIS project

Seamounts are of great interest to science, industry and conservation because of their potential role as 'stirring rods' of the oceans, their enhanced productivity, their high local biodiversity, and the growing exploitation of their natural resources. This is accompanied by rising concern about the threats to seamount ecosystems, e.g. through over-fishing and the impact of trawling. OASIS described the functioning characteristics of seamount ecosystems. OASIS' integrated hydrographic, biogeochemical and biological information. Based on two case studies. The scientific results, condensed in conceptual and mass balanced ecosystem models, were applied to outline a model management plan as well as site-specific management plans for the seamounts investigated. OASIS addressed five main objectives: Objective 1: To identify and describe the physical forcing mechanisms effecting seamount systems Objective 2: To assess the origin, quality and dynamics of particulate organic material within the water column and surface sediment at seamounts. Objective 3: To describe aspects of the biodiversity and the ecology of seamount biota, to assess their dynamics and the maintenance of their production. Objective 4: Modelling the trophic ecology of seamount ecosystems. Objective 5: Application of scientific knowledge to practical conservation.