Regional climate models (RCMs) are usually initialized and driven through the boundaries of their limited area domain by data provided by global models (GCMs). The mismatch between the low‐resolution GCM initial conditions and RCM's high resolution introduces physical inconsistencies between the various components of the RCM. These inconsistencies can be resolved by running the RCM during a period that is considered unreliable: the spin‐up period. There is no deterministic definition of the length that the spin‐up period should have. Here we try to provide general guidelines that can be used to the advantage of the community. We base our analysis on Weather Research and Forecasting (WRF) simulations over a Euro‐Cordex compliant domain and find that for 2‐m temperature and precipitation, rather short spin‐up periods (1 week) can be sufficient. Nevertheless, longer periods (6 months) are advisable, and start dates in non‐winter months should be pursued, as this ensures a more realistic representation of the snow cover. Thus, the issue is not only about the spin‐up length. As the soil subsystem evolves slowly and requires longer periods to reach equilibrium than the longest considered here (1 year), seasonality plays an important role in minimizing the impact of the unreliability of the soil initialization. Fortunately, except for goals where the deep soil‐atmosphere feedback are critical, the lack of equilibrium between them can be ignored, as it seems to have little effect on the simulation of the atmospheric variables most frequently used in RCM studies. Plain Language Summary High‐resolution climate simulations performed with the so‐called regional climate models (RCMs) are usually initialized from coarser databases that provide an inconsistent picture at the higher resolution of the RCM. To overcome it and obtain reliable RCM simulations, RCMs should run over a time span to reach physical equilibrium. During this “trash” period (called spin‐up period), the RCM outputs should be discarded for later analysis, for example, for assessing climate change impacts. In order to guarantee the reliability of RCM simulations and minimize their high computational cost, determining an optimal length of the spin‐up period is critical. For a European domain with ~50‐km resolution and for a particular, but widely used, RCM, the WRF model, here we find that half a year of spin‐up would be enough for atmospheric variables (temperature and precipitation), always that the RCM initialization occurs in summer months; otherwise, the snow cover initial state is misrepresented, making it inadvisable longer spin‐up periods implying winter start dates. However, soil variables (especially water content) cannot be trusted even after up to one full year of spin‐up. Fortunately, the negligible impact of this issue for most RCM applications involving only atmospheric variables emerges also from our analysis.
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