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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
Stockholm University, Faculty of Science, Department of Physical Geography.
Stockholm University, Faculty of Science, Department of Mathematics.
Stockholm University, Faculty of Science, Department of Physical Geography.
Stockholm University, Faculty of Science, Department of Physical Geography. Stockholm University, Faculty of Science, Department of Mathematics.
2015 (English)In: Climate of the Past, ISSN 1814-9324, E-ISSN 1814-9332, Vol. 11, no 3, 425-448 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2015. Vol. 11, no 3, 425-448 p.
National Category
Climate Research
Research subject
Physical Geography; Mathematical Statistics
Identifiers
URN: urn:nbn:se:su:diva-117053DOI: 10.5194/cp-11-425-2015ISI: 000352159900005OAI: oai:DiVA.org:su-117053DiVA: diva2:811287
Funder
Swedish Research Council, 90751501Swedish Research Council, B0334901Swedish Research Council, C0592401
Note

AuthorCount:4;

Available from: 2015-05-11 Created: 2015-05-06 Last updated: 2017-12-04Bibliographically approved

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Moberg, AndersSundberg, RolfGrudd, HåkanHind, Alistair
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