Evaluation of uncertainties in the CRCM-simulated North American climate |
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| Authors: | Ramón de Elía Daniel Caya Hélène Côté Anne Frigon Sébastien Biner Michel Giguère Dominique Paquin Richard Harvey David Plummer |
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| Institution: | (1) Climate Simulations Team, Consortium Ouranos, 550 Sherbrooke street West, 19th floor, West tower, Montreal, QC, Canada, H3A 1B9;(2) Canadian Centre for Climate Modelling and Analysis, Meteorological Service of Canada, Victoria, BC, Canada |
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| Abstract: | This work is a first step in the analysis of uncertainty sources in the RCM-simulated climate over North America. Three main
sets of sensitivity studies were carried out: the first estimates the magnitude of internal variability, which is needed to
evaluate the significance of changes in the simulated climate induced by any model modification. The second is devoted to
the role of CRCM configuration as a source of uncertainty, in particular the sensitivity to nesting technique, domain size,
and driving reanalysis. The third study aims to assess the relative importance of the previously estimated sensitivities by
performing two additional sensitivity experiments: one, in which the reanalysis driving data is replaced by data generated
by the second generation Coupled Global Climate Model (CGCM2), and another, in which a different CRCM version is used. Results
show that the internal variability, triggered by differences in initial conditions, is much smaller than the sensitivity to
any other source. Results also show that levels of uncertainty originating from liberty of choices in the definition of configuration
parameters are comparable among themselves and are smaller than those due to the choice of CGCM or CRCM version used. These
results suggest that uncertainty originated by the CRCM configuration latitude (freedom of choice among domain sizes, nesting
techniques and reanalysis dataset), although important, does not seem to be a major obstacle to climate downscaling. Finally,
with the aim of evaluating the combined effect of the different uncertainties, the ensemble spread is estimated for a subset
of the analysed simulations. Results show that downscaled surface temperature is in general more uncertain in the northern
regions, while precipitation is more uncertain in the central and eastern US. |
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