Gridded climate data from 5 Global Climate Models (GCM) of the Last Glacial Maximum (LGM) downscaled to 30 arc seconds for Europe, with links to NetCDF files

Studies on the impact of historical, current and future global change require very high-resolution climate data (less or equal 1km) as a basis for modelled responses, meaning that data from digital climate models generally require substantial rescaling. Another shortcoming of available datasets on past climate is that the effects of sea level rise and fall are not considered. Without such information, the study of glacial refugia or early Holocene plant and animal migration are incomplete if not impossible. Sea level at the last glacial maximum (LGM) was approximately 125m lower, creating substantial additional terrestrial area for which no current baseline data exist. Here, we introduce the development of a novel, gridded climate dataset for LGM that is both very high resolution (1km) and extends to the LGM sea and land mask. We developed two methods to extend current terrestrial precipitation and temperature data to areas between the current and LGM coastlines. The absolute interpolation error is less than 1°C and 0.5 °C for 98.9% and 87.8% of all pixels for the first two 1 arc degree distance zones. We use the change factor method with these newly assembled baseline data to downscale five global circulation models of LGM climate to a resolution of 1km for Europe. As additional variables we calculate 19 'bioclimatic' variables, which are often used in climate change impact studies on biological diversity. The new LGM climate maps are well suited for analysing refugia and migration during Holocene warming following the LGM.

Reference list of sources used for two experimental data files dataBSRN and dataMixed

Increasing amounts of data is collected in most areas of research and application. The degree to which this data can be accessed, analyzed, and retrieved, is a decisive in obtaining progress in fields such as scientific research or industrial production. We present a novel methodology supporting content-based retrieval and exploratory search in repositories of multivariate research data. In particular, our methods are able to describe two-dimensional functional dependencies in research data, e.g. the relationship between ination and unemployment in economics. Our basic idea is to use feature vectors based on the goodness-of-fit of a set of regression models to describe the data mathematically. We denote this approach Regressional Features and use it for content-based search and, since our approach motivates an intuitive definition of interestingness, for exploring the most interesting data. We apply our method on considerable real-world research datasets, showing the usefulness of our approach for user-centered access to research data in a Digital Library system.

Grain size distribution and sea level changes in Gåsfjärden fjord

We analysed long-term variations in grain-size distribution in sediments from Gåsfjärden, a fjord-like inlet on the south-west Baltic Sea, and explored potential drivers of the recorded changes in sediment grain-size data. Over the last 5.4 thousand years (ka), the relative sea level decreased 17 m in the study region, caused by isostatic land uplift. As a consequence, Gåsfjärden has been transformed from an open coastal setting into a semi-closed inlet surrounded on the east by numerous small islands. To quantitatively estimate the morphological changes in Gåsfjärden over the last 5.4 ka and to further link the changes to our grain-size data, a digital elevation model (DEM)-based openness index was calculated. In the period between 5.4 and 4.4 ka BP, the inlet was characterised by the largest openness index. During this interval, the highest sand contents (~0.4 %) and silt/clay ratios (~0. 3) in the sediment sequence were recorded, indicating relatively high bottom water energy. After 4.4 ka BP, the average sand content was halved to ~0.2 % and the silt/clay ratios showed a significant decreasing trend over the last 4 ka. These changes are found to be associated with the gradual embayment of Gåsfjärden as represented in the openness index. The silt/clay ratios exhibited a delayed and slower change compared with the sand contents, which further suggest that finer particles are less sensitive to changes in hydrodynamic energy. Our DEM-based coastal openness index has proved to be a useful tool for interpreting the sedimentary grain-size record.