Impact of spectral nudging and domain size in studies of RCM response to parameter modification

The paper aims at finding an RCM configuration that facilitates studies devoted to quantifying RCM response to parameter modification. When using short integration times, the response of the time-averaged variables to RCM modification tend to be blurred by the noise originating in the lack of predictability of the instantaneous atmospheric states. Two ways of enhancing the signal-to-noise ratio are studied in this work: spectral nudging and reduction of the computational domain size. The approach followed consists in the analysis of the sensitivity of RCM-simulated seasonal averages to perturbations of two parameters controlling deep convection and stratiform condensation, perturbed one at a time. Sensitivity is analyzed within different simulation configurations obtained by varying domain size and using the spectral nudging option. For each combination of these factors multiple members of identical simulations that differ exclusively in initial conditions are also generated to provide robust estimates of the sensitivities (the signal) and sample the noise. Results show that the noise magnitude is decreased both by reduction of domain size and the spectral nudging. However, the reduction of domain size alters some sensitivity signals. When spectral nudging is used significant alterations of the signal are not found.