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  • Räisänen, J., and J.S. Ylhäisi, 2011: Can model weighting improve probabilistic projections of climate change?. Climate Dynamics, 10.1007/s00382-011-1217-8.

Recently, Ra¨isa¨nen and co-authors proposed a
weighting scheme in which the relationship between
observable climate and climate change within a multimodel
ensemble determines to what extent agreement with
observations affects model weights in climate change
projection. Within the Third Coupled Model Intercomparison
Project (CMIP3) dataset, this scheme slightly
improved the cross-validated accuracy of deterministic
projections of temperature change. Here the same scheme
is applied to probabilistic temperature change projection,
under the strong limiting assumption that the CMIP3
ensemble spans the actual modeling uncertainty. Crossvalidation
suggests that probabilistic temperature change
projections may also be improved by this weighting
scheme. However, the improvement relative to uniform
weighting is smaller in the tail-sensitive logarithmic score
than in the continuous ranked probability score. The impact
of the weighting on projection of real-world twenty-first
century temperature change is modest in most parts of the
world. However, in some areas mainly over the high-latitude
oceans, the mean of the distribution is substantially
changed and/or the distribution is considerably narrowed.
The weights of individual models vary strongly with
location, so that a model that receives nearly zero weight in
some area may still get a large weight elsewhere. Although
the details of this variation are method-specific, it suggests
that the relative strengths of different models may be
difficult to harness by weighting schemes that use spatially
uniform model weights.


Full Article: http://www.springerlink.com/content/yu786q6t26328434/

Last Updated: 2011-11-20

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