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Filed work on färskesjön 2013

Anne Birgitte Nielsen

Senior lecturer

Filed work on färskesjön 2013

Mid-Holocene European climate revisited : New high-resolution regional climate model simulations using pollen-based land-cover


  • Gustav Strandberg
  • Johan Lindström
  • Anneli Poska
  • Qiong Zhang
  • Ralph Fyfe
  • Esther Githumbi
  • Erik Kjellström
  • Florenze Mazier
  • Anne Birgitte Nielsen
  • Shinya Sugita
  • Anna Kari Trondman
  • Jessie Woodbridge
  • Marie José Gaillard

Summary, in English

Land-cover changes have a clear impact on local climates via biophysical effects. European land cover has been affected by human activities for at least 6000 years, but possibly longer. It is thus highly probable that humans altered climate before the industrial revolution (AD1750–1850). In this study, climate and vegetation 6000 years (6 ka) ago is investigated using one global climate model, two regional climate models, one dynamical vegetation model, pollen-based reconstruction of past vegetation cover using a model of the pollen-vegetation relationship and a statistical model for spatial interpolation of the reconstructed land cover. This approach enables us to study 6 ka climate with potential natural and reconstructed land cover, and to determine how differences in land cover impact upon simulated climate. The use of two regional climate models enables us to discuss the robustness of the results. This is the first experiment with two regional climate models of simulated palaeo-climate based on regional climate models. Different estimates of 6 ka vegetation are constructed: simulated potential vegetation and reconstructed vegetation. Potential vegetation is the natural climate-induced vegetation as simulated by a dynamical vegetation model driven by climate conditions from a climate model. Bayesian spatial model interpolated point estimates of pollen-based plant abundances combined with estimates of climate-induced potential un-vegetated land cover were used for reconstructed vegetation. The simulated potential vegetation is heavily dominated by forests: evergreen coniferous forests dominate in northern and eastern Europe, while deciduous broadleaved forests dominate central and western Europe. In contrast, the reconstructed vegetation cover has a large component of open land in most of Europe. The simulated 6 ka climate using reconstructed vegetation was 0–5 °C warmer than the pre-industrial (PI) climate, depending on season and region. The largest differences are seen in north-eastern Europe in winter with about 4–6 °C, and the smallest differences (close to zero) in southwestern Europe in winter. The simulated 6 ka climate had 10–20% more precipitation than PI climate in northern Europe and 10–20% less precipitation in southern Europe in summer. The results are in reasonable agreement with proxy-based climate reconstructions and previous similar climate modelling studies. As expected, the global model and regional models indicate relatively similar climates albeit with regional differences indicating that, models response to land-cover changes differently. The results indicate that the anthropogenic land-cover changes, as given by the reconstructed vegetation, in this study are large enough to have a significant impact on climate. It is likely that anthropogenic impact on European climate via land-use change was already taking place at 6 ka. Our results suggest that anthropogenic land-cover changes at 6 ka lead to around 0.5 °C warmer in southern Europe in summer due to biogeophysical forcing.


  • Mathematical Statistics
  • MERGE: ModElling the Regional and Global Earth system
  • eSSENCE: The e-Science Collaboration
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • Dept of Physical Geography and Ecosystem Science
  • Quaternary Sciences

Publishing year





Quaternary Science Reviews



Document type

Journal article




  • Climate Research


  • Dynamical vegetation model
  • EC-Earth
  • Global climate model
  • Land-use and land-cover change
  • Paleoclimate
  • RCA4
  • Spatial statistical models
  • Vegetation reconstruction




  • PAGES LandCover6k fast track project 2020-2021


  • ISSN: 0277-3791