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Climate of the Past An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 4
Clim. Past, 8, 1339–1353, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Clim. Past, 8, 1339–1353, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 27 Aug 2012

Research article | 27 Aug 2012

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 1: Theory

R. Sundberg1, A. Moberg2, and A. Hind2 R. Sundberg et al.
  • 1Department of Mathematics, Division of Mathematical Statistics, Stockholm University, 106 91 Stockholm, Sweden
  • 2Department of Physical Geography and Quaternary Geology, Bert Bolin Centre for Climate Research, Stockholm University, 106 91 Stockholm, Sweden

Abstract. A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

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