Sensitivity Study of Regional Climate Model Simulations to Large-Scale Nudging Parameters

Abstract

Abstract Previous studies with nested regional climate models (RCMs) have shown that large-scale spectral nudging (SN) seems to be a powerful method to correct RCMs’ weaknesses such as internal variability, intermittent divergence in phase space (IDPS), and simulated climate dependence on domain size and geometry. Despite its initial success, SN is not yet in widespread use because of disagreement regarding the main premises—the unconfirmed advantages of removing freedom from RCMs’ large scales—and lingering doubts regarding its potentially negative side effects. This research addresses the latter issue. Five experiments have been carried out with the Canadian RCM (CRCM) over North America. Each experiment, performed under a given SN configuration, consists of four ensembles of simulations integrated on four different domain sizes for a summer season. In each experiment, the effects of SN on internal variability, time means, extremes, and power spectra are discussed. As anticipated from previous investigations, the present study confirms that internal variability, as well as simulated-climate dependence on domain size, decreases with increased SN strength. Our results further indicate a noticeable reduction of precipitation extremes as well as low-level vorticity amplitude in almost all length scales, as a side effect of SN; these effects are mostly perceived when SN is the most intense. Overall results indicate that the use of a weak to mild SN may constitute a reasonable compromise between the risk of decoupling of the RCM internal solution from the lateral boundary conditions (when using large domains without SN) and an excessive control of the large scales (with strong SN).