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

High temporal resolution (three hours) records of temperature, wind speed and sea level pressure recorded at Antarctic research station Neumayer (70°S, 8°W) during 1982-2011 are analysed to identify oscillations from daily to intraseasonal timescales. The diurnal cycle dominates the three-hourly time series of temperature during the Antarctic summer and is almost absent during winter. In contrast, the three-hourly time series of wind speed and sea level pressure show a weak diurnal cycle. The dominant pattern of the intraseasonal variability of these quantities, which captures the out-of-phase variation of temperature and wind speed with sea level pressure, shows enhanced variability at timescales of ~ 40 days and ~ 80 days, respectively. Correlation and composite analysis reveal that these oscillations may be related to tropical intraseasonal oscillations via large-scale eastward propagating atmospheric circulation wave-trains. The second pattern of intraseasonal variability, which captures in-phase variations of temperature, wind and sea level pressure, shows enhanced variability at timescales of ~ 35, ~ 60 and ~ 120 days. These oscillations are attributed to the Southern Annular Mode/Antarctic Oscillation (SAM/AAO) which shows enhanced variability at these timescales. We argue that intraseasonal oscillations of tropical climate and SAM/AAO are related to distinct patterns of climate variables measured at Neumayer.

Miocene strontium isotope record of DSDP Hole 30-289

A composite strontium isotopic seawater curve was constructed for the Miocene between 24 and 6 Ma by combining 87Sr/86Sr measurements of planktonic foraminifera from Deep Sea Drilling Project sites 289 and 588. Site 289, with its virtually continuous sedimentary record and high sedimentation rates (26 m/m.y.), was used for constructing the Oligocene to mid-Miocene part of the record, which included the calibration of 63 biostratigraphic datums to the Sr seawater curve using the timescale of Cande and Kent (1992 doi:10.1029/92JB01202). Across the Oligocene/Miocene boundary, a brief plateau occurred in the Sr seawater curve (87Sr/86Sr values averaged 0.70824) which is coincident with a carbon isotopic maximum (CM-O/M) from 24.3 to 22.6 Ma. During the early Miocene, the strontium isotopic curve was marked by a steep rise in 87Sr/86Sr that included a break in slope near 19 Ma. The rate of growth was about 60 ppm/m.y. between 22.5 and 19.0 Ma and increased to over 80 ppm/m.y. between 19.0 and 16 Ma. Beginning at ~16 Ma (between carbon isotopic maxima CM3 and CM4 of Woodruff and Savin (1991 doi:10.1029/91PA02561)), the rate of 87Sr/86Sr growth slowed and 87Sr/86Sr values were near constant from 15 to 13 Ma. After 13 Ma, growth in 87Sr/86Sr resumed and continued until ~9 Ma, when the rate of 87Sr/86Sr growth decreased to zero once again. The entire Miocene seawater curve can be described by a high-order function, and the first derivative (d87Sr/86Sr/dt) of this function reveals two periods of increased slope. The greatest rate of 87Sr/86Sr change occurred during the early Miocene between ~20 and 16 Ma, and a smaller, but distinct, period of increased slope also occurred during the late Miocene between ~12 and 9 Ma. These periods of steepened slope coincide with major phases of uplift and denudation of the Himalayan-Tibetan Plateau region, supporting previous interpretations that the primary control on seawater 87Sr/86Sr during the Miocene was related to the collision of India and Asia. The rapid increase in 87Sr/86Sr values during the early Miocene from 20 to 16 Ma imply high rates of chemical weathering and dissolved riverine fluxes to the oceans. In the absence of another source of CO2, these high rates of chemical weathering should have quickly resulted in a drawdown of atmospheric CO2 and climatic cooling through a reversed greenhouse effect. The paleoclimatic record, however, indicates a warming trend during the early Miocene, culminating in a climatic optimum between 17 and 14.5 Ma. We suggest that the high rates of chemical erosion and warm temperatures during the climatic optimum were caused by an increase in the contribution of volcanic CO2 from the eruption of the Columbia River Flood Basalts (CRFB) between 17 and 15 Ma. The decrease in the rate of CRFB eruptions at 15 Ma and the removal of atmospheric carbon dioxide by increased organic carbon burial in Monterey deposits eventually led to cooling and increased glaciation between ~14.5 and 13 Ma. The CRFB hypothesis helps to explain the significant time lag between the onset of increased rates of organic carbon burial in the Monterey at 17.5 Ma (as marked by increased delta13C values) and the climatic cooling and glaciation during the middle Miocene (as marked by the increase in delta18O values), which did not begin until ~14.5 Ma.

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.