Summary: | Palaeoclimatic reconstructions from fossil proxies have provided important insights into the natural variability of climate in the late Quaternary. However, major challenges remain in ensuring the robustness of these reconstructions. Multiple factors may introduce variability and biases into the palaeoclimatic estimates. For example, quantitative reconstructions use diverse modern calibration data-sets, and a wide variety of numerical calibration methods. While the choice of calibration data-set and calibration method may significantly influence the reconstructions, the comparison and analysis of these data-sets and methods have received relatively little attention. Further challenges are presented by the validation of the prepared reconstructions and the identification of climatic variables which can be robustly reconstructed from a given proxy. In this work, summer temperature reconstructions are prepared based on late-Quaternary pollen sequences from northern Finland and northern Russia, covering the Holocene and the early part of the last glacial period (Marine Isotope Stages 5d c). The major aim of this work is to validate these reconstructions and to identify sources of bias in them. Reconstructions are prepared using a number of different calibration methods and calibration sets, to analyse the between-reconstruction variability introduced by the choice of calibration method and calibration set. In addition, novel regression tree methods are used to test the ecological significance of different climatic factors, with the aim of identifying parameters which could feasibly be reconstructed. In the results, it is found that the choice of calibration method, calibration data-set, and fossil pollen sequence can all significantly affect the reconstruction. The problems in choosing calibration data are especially acute in pre-Holocene reconstructions, as it is difficult to find representative calibration data for reconstructions from non-analogue palaeoclimates which become increasingly common in the more ...
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