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Climate of the Past An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 3
Clim. Past, 11, 425–448, 2015
https://doi.org/10.5194/cp-11-425-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Clim. Past, 11, 425–448, 2015
https://doi.org/10.5194/cp-11-425-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Mar 2015

Research article | 12 Mar 2015

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 3: Practical considerations, relaxed assumptions, and using tree-ring data to address the amplitude of solar forcing

A. Moberg1,3, R. Sundberg2,3, H. Grudd1,3, and A. Hind1,2,3 A. Moberg et al.
  • 1Department of Physical Geography, Stockholm University, Stockholm, Sweden
  • 2Division of Mathematical Statistics, Department of Mathematics, Stockholm University, Stockholm, Sweden
  • 3Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden

Abstract. A statistical framework for evaluation of climate model simulations by comparison with climate observations from instrumental and proxy data (part 1 in this series) is improved by the relaxation of two assumptions. This allows autocorrelation in the statistical model for simulated internal climate variability and enables direct comparison of two alternative forced simulations to test whether one fits the observations significantly better than the other. The extended framework is applied to a set of simulations driven with forcings for the pre-industrial period 1000–1849 CE and 15 tree-ring-based temperature proxy series. Simulations run with only one external forcing (land use, volcanic, small-amplitude solar, or large-amplitude solar) do not significantly capture the variability in the tree-ring data – although the simulation with volcanic forcing does so for some experiment settings. When all forcings are combined (using either the small- or large-amplitude solar forcing), including also orbital, greenhouse-gas and non-volcanic aerosol forcing, and additionally used to produce small simulation ensembles starting from slightly different initial ocean conditions, the resulting simulations are highly capable of capturing some observed variability. Nevertheless, for some choices in the experiment design, they are not significantly closer to the observations than when unforced simulations are used, due to highly variable results between regions. It is also not possible to tell whether the small-amplitude or large-amplitude solar forcing causes the multiple-forcing simulations to be closer to the reconstructed temperature variability. Proxy data from more regions and of more types, or representing larger regions and complementary seasons, are apparently needed for more conclusive results from model–data comparisons in the last millennium.

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Experiments with climate models can help to understand causes of past climate changes. We develop a statistical framework for comparing data from simulation experiments with temperature reconstructions for the last millennium. A combination of several external factors is found to explain a significant part of the observed variations, but our selection of data cannot tell which of two alternative choices of past solar forcing gives the best fit between simulations and reconstructions.
Experiments with climate models can help to understand causes of past climate changes. We...
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