| 1. |
- Strandberg, G., et al.
(author)
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Regional climate model simulations for Europe at 6 k and 0.2 k yr BP: sensitivity to changes in anthropogenic deforestation.
- 2013
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In: Climate of the Past Discussions. - : Copernicus GmbH. - 1814-9340 .- 1814-9359. ; 9:5, s. 5785-5836
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Journal article (peer-reviewed)abstract
- This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, ~6 k BP and ~0.2 k BP in Europe. We apply RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land cover (deforestation) as simulated by the HYDE model (V + H), and (iii) potential vegetation with anthropogenic land cover as simulated by the KK model (V + K). The KK model estimates are closer to a set of pollen-based reconstructions of vegetation cover than the HYDE model estimates. The climate-model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At ~6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5–1 °C. At ~0.2 k BP, simulated deforestation is much more extensive than previously assumed, in particular according to the KK model. This leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe since evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from −1 °C in south-western Europe to +1 °C in eastern Europe. The choice of anthropogenic land cover estimate has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a thorough comparison with climate model results.
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| 3. |
- Salonen, J. Sakari, et al.
(author)
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The effect of calibration data set selection on quantitative palaeoclimatic reconstructions
- 2013
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In: The Holocene. - : SAGE Publications. - 0959-6836 .- 1477-0911. ; 23:11, s. 1650-1654
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Journal article (peer-reviewed)abstract
- Quantitative palaeoclimatic reconstructions based on biological fossils are a major source of information on long-term climatic variability. Such reconstructions typically use some kind of a modern calibration data set describing the variation of the studied biological group in present-day climate space. Here, we explore the effect of calibration data set selection on palaeoclimatic reconstructions, by creating alternate calibration data sets via stratified random sampling to reconstruct mean July temperature (T-jul) for four fossil pollen sequences from northern Europe. We show that palaeoclimatic reconstructions using methods based on taxon-response models can be highly sensitive to the calibration data set used. In particular, the absolute reconstructed temperatures show great sensitivity to calibration data selection, which suggests that the absolute values of palaeoclimatic reconstructions may not be robust. By contrast, we find the relative shapes of the reconstructed curves to be more robust to calibration data selection because taxa tend to occupy similar relative locations along the sampled gradient regardless of calibration data set location. Based on this robustness of relative palaeoclimate curves, we suggest a debiasing procedure in which palaeoclimate values are estimated by fixing the relative curve with the modern observed value, thus correcting biases resulting from calibration data selection.
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