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Long-range temporal correlation exponents in models compared to observations

PI: Dmitry Vyushin
Institution: University of Toronto
A fundamental test of the realism of coupled General Circulation Models (GCMs) is to examine their ability to realistically represent variability of the climate system on a wide range of timescales. A useful method to test this aspect of GCM performance is to estimate the models' long-range temporal correlation exponents (Govindan et al., Phys. Rev. Lett. 89, 2002) of surface temperature and other fields, and to compare these to estimates for the observations. Recently we performed this kind of analysis on several NCAR PCM simulations that used various anthropogenic and natural forcings over the past century. We found that the long-range temporal correlations were sensitive to the types of forcings included, and in particular that it is necessary to include volcanic forcing to reproduce the observed correlations (Vyushin et al., Geophys. Res. Lett. 31, 2004).

We propose to use the opportunity of the release of the IPCC datasets to 1) apply robust methods of estimating long-range correlation exponents to several models and 2) apply these methods globally rather than at individual sites as has been done in the cited references. The objective of the analysis is to infer the influence of different forcings and of internal variability on long-range correlations, with reference to the observations.
  • Vyushin, D.I., P.J. Kushner, J. Mayer, 2009: On the origins of temporal power-law behavior in the global atmospheric circulation. Geophys. Res. Lett., 36, L14706, doi:10.1029/2009GL038771. Abstract. Full Article. Edit.

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