1Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany
2School of Geosciences, University of Edinburgh, West Mains Road, Edinburgh EH9 3JW, UK
3Max Planck Institute for Solar System Research, Max Planck Strasse 2, 37191 Katlenburg-Lindau, Germany
4KlimaCampus, University of Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
5Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
*now at: Department of Global Ecology, Carnegie Institution of Washington, 260 Panama St., Stanford, CA 94305, USA
**now at: Laboratoire de Physique et Chemie de l'Environment et de l'Espace, CNRS & University of Orleans, 3A Av. De la Recherche Scientifique, 45071 Orléans, France
Abstract. A long-standing task in climate research has been to distinguish between anthropogenic climate change and natural climate variability. A prerequisite for fulfilling this task is the understanding of the relative roles of external drivers and internal variability of climate and the carbon cycle. Here, we present the first ensemble simulations over the last 1200 years with a comprehensive Earth system model including a fully interactive carbon cycle. Applying up-to-date reconstructions of external forcing including the recent low-amplitude estimates of solar variations, the ensemble simulations reproduce temperature evolutions consistent with the range of reconstructions. The 20th-century warming trend stands out against all pre-industrial trends within the ensemble. Volcanic eruptions are necessary to explain variations in pre-industrial climate such as the Little Ice Age; yet only the strongest, repeated eruptions lead to cooling trends that stand out against the internal variability across all ensemble members. The simulated atmospheric CO2 concentrations exhibit a stable carbon cycle over the pre-industrial era with multi-centennial variations somewhat smaller than in the observational records. Early land-cover changes have modulated atmospheric CO2 concentrations only slightly. We provide a model-based quantification of the sensitivity (termed γ) of the global carbon cycle to temperature for a variety of climate and forcing conditions. The magnitude of γ agrees with a recent statistical assessment based on reconstruction data. We diagnose a distinct dependence of γ on the forcing strength and time-scales involved, thus providing an explanation for the systematic difference in the observational estimates for different segments of the last millennium.