Introduction

Background Numerical models provide a powerful tool for atmospheric research. One of the most common ways of utilizing a model is by performing sensitivity experiments. Their purpose is to isolate the effects of different factors on certain atmospheric fields in one or more case studies. Factors that have been tested in sensitivity studies include, for example, surface sensible and latent heat fluxes, latent heat release, horizontal and vertical resolution, sea surface temperatures, horizontal diffusion, surface stress, initial and boundary conditions, topography, surface moisture, atmospheric stability, and radiation. Sensitivity studies are performed either with real-data case studies or with idealized atmospheric situations. Sensitivity studies often evaluate the influence of only one factor such as topography (Tibaldi et al., 1980; Dell'Osso, 1984, McGinley and Goerss, 1986), but many investigations test several factors, and try to estimate their relative importance. One common method of evaluating the contribution of a specific factor is by analyzing the difference in fields between a control run and a simulation where this factor is switched off. The difference map is, in general, more illustrative than the presentation of the two individual simulations, and therefore has often been used (e.g., Tibaldi et al., 1980; Mesinger and Strickler, 1982; Lannici et al., 1987; Leslie et al., 1987; Uccellini et al., 1987; Mullen and Baumhafner, 1988; Kuo and Low-Nam, 1990).