The CLIMATE data base of monthly normals for globally gridded climatic variables (version 2.1)

This database (Leemans & Cramer 1991) contains monthly averages of mean temperature, temperature range, precipitation, rain days and sunshine hours for the terrestrial surface of the globe, gridded at 0.5 degree longitude/latitude resolution. All grd-files contain the same 62483 pixels in the same order, with 30' latitude and longitude resolution. The coordinates are in degree-decimals and indicate the SW corner of each pixel. Topography is from ETOPO5 and indicates modal elevation. Data were generated from a large data base, using the partial thin-plate splining algorithm (Hutchinson & Bischof 1983). This version is widely used around the globe, notably by all groups participating in the IGBP NPP model intercomparison.

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

Age and isotopes in bottom sediments from Core VER-99-1-St2, Baikal Lake

A simple, reliable, and efficient method has been elaborated for direct determination of isotopic composition of authigenic uranium in siliceous lacustrine sediments. The method is based on studying kinetics of selective extraction of authigenic uranium from sediments by weak solutions of ammonium hydrocarbonate followed by ICP-MS analysis of nuclides. To estimate contamination of authigenic uranium by terrigenous one contents of 232Th and some other clastogenic elements in the extracts were measured simultaneously. Selectivity of extraction of authigenic uranium from the sediments treated with 1% NH4HCO3 solution appeared to be no worse than 99%. The method was applied to analysis of isotopic composition of authigenic uranium at several key horizons of the earlier dated core from the Baikal Lake. Measurements directly show that 234U/238U values in Baikal water varied depending on climate, which contradicts existing hypotheses. Measured 234U/238U ratios in water of the paleo-Baikal match corresponding values reconstructed from isotopic data for total uranium in the sediments on supposition that U/Th ratio is constant in terrigenous fraction of the sediments. Direct experimental determination of total and authigenic nuclides in sediments enhances potentiality of the method for 234U-230Th dating of non-carbonate lacustrine sediments including those from the Baikal Lake within intervals corresponding to periods of glaciation, when sediments were rich in terrigenous components. Portions of terrigenous and authigenic uranium are well separated and we can study variability of sources of terrigenous matter and refine the earlier model for reconstructing climate humidity in the East Siberia.