Dinoflagellate cyst assemblages, oxygen isotope records of foraminifera, and alkenone and Mg/Ca-based SST estimates for the time interval 3.40-3.18 Ma (Late Pliocene) from five North Atlantic and Caribbean sediment cores

The early Late Pliocene (3.6 to ~3.0 million years ago) is the last extended interval in Earth's history when atmospheric CO2 concentrations were comparable to today's and global climate was warmer. Yet a severe global glaciation during marine isotope stage (MIS) M2 interrupted this phase of global warmth ~3.30 million years ago, and is seen as a premature attempt of the climate system to establish an ice-age world. Our geochemical and palynological records from five marine sediment cores along a Caribbean to eastern North Atlantic transect show that increased Pacific-to-Atlantic flow via the Central American Seaway weakened the North Atlantic Current (NAC) and attendant northward heat transport prior to MIS M2. The consequent cooling of the northern high latitude oceans permitted expansion of the Greenland ice sheet during MIS M2, despite near-modern atmospheric CO2 concentrations. Before and after MIS M2, heat transport via the NAC was crucial in maintaining warm climates comparable to those predicted for the end of this century.

Part of the global DOC versus AOU (dissolved organic carbon/apparent oxygen utilization) data compilation, Azores-I

Temperate, transitional and subtropical waters of the remote Azores Front region east of Azores (24-40°N, 22-32°W) were sampled during three cruises conducted under increasing stratification conditions (April 1999, May 1997 and August 1998). Despite the temporal increase of surface temperature (by 5 °C) and stratification (by 2.1 1/min**2), as well as the thermocline shoaling (by ~15 m), dissolved organic carbon (DOC) and nitrogen (DON) in the surface layer were not significantly different for the early spring, late spring and summer periods, with average concentrations of 69±2 µM-C and 5.2±0.4 µM-N, respectively. The surface excess of semi-labile DOC, compared with the baseline DOC concentration in the deep ocean (47±2 µM-C), represents 33% of the bulk DOC concentration and as much as 85% of the TOC (=POC+DOC) excess. When compared with the winter baseline (56±2 µM-C), the seasonal surface DOC excess is 20% of the bulk DOC concentration and 87% of the seasonal TOC excess. These results confirm the major role played by DOC in the carbon cycle of surface waters of the Azores Front region. The total amount of bioreactive DOC transported from the temperate to the subtropical North Atlantic by the Ekman flux between March and December represents only ~15% of the average annual primary production, and ~15% and ~30% of the measured sinking POC flux+vertical DOC eddy diffusion during early spring and summer, respectively. Vertical eddy diffusion is 35% and 2% of the spring and summer sinking POC flux, respectively. On the other hand, DOC only contributes 13% to the local oxidation of organic matter in subsurface waters (between the pycnocline and 500 m) of the study region.

30 years of synoptic observations from Neumayer Station with links to datasets

The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.