Abstract
Short regional climate model simulations are routinely compared with observations, though because of extremely small sample sizes (often only a single season or year is simulated) it is generally difficult to establish whether any model‐reality differences are statistically significant. In the following, a permutation technique is proposed to estimate the statistical significance of similarities between spatial fields as simulated by a regional climate model, and observations, when the climate model is nested within operational analyses (i.e. “perfect” lateral boundary conditions). To illustrate the technique, we consider a short simulation over the Mackenzie River Basin of northwestern Canada made using the Canadian Regional Climate Model, and focus our attention on accumulated monthly precipitation and monthly average screen temperature. For comparison we have a 45 year gridded, monthly climate dataset produced by the Meteorological Service of Canada over the same region, based on adjusted operational climate station data.
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