Extreme precipitation events in Central Alberta have overwhelmed hydraulic structures several times in recent years, and it is generally expected that rainfall intensity in this region will continue to increase over the next several decades. Accurate rainfall projections are thus needed to assess future flood risks and to mitigate the possible impacts of these changes. Such data may be obtained through the use of regional climate models (RCMs), and one in particular, the fifth-generation NCAR/Penn State mesoscale atmospheric model (MM5), is investigated here. MM5 is used to dynamically downscale European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data to evaluate its ability to accurately simulate rainfall in Central Alberta over two consecutive summers that represent contrasting precipitation regimes. It is determined that in complex terrain, different RCM preprocessing settings can result in vastly different input data which are used for the model simulation. After optimal preprocessing settings are identified, precipitation data from the resulting simulations are compared with data from Edmonton's local rain gauge network and a High Resolution Precipitation Product (HRPP), Climate Prediction Center (CPC) MORPHing technique (CMORPH). Precipitation data generated by MM5 reveal that this RCM can indeed distinguish between wet (2010) and dry (2009) years, but that simulated rainfall totals tend to be too high during May of both precipitation regimes, particularly during the dry year. This bias is partially attributed to the RCM's inaccurate simulation of available moisture in the presence of local terrain effects, and should be taken into consideration when making projections regarding possible changes to future precipitation conditions in Central Alberta and in other regions with similar climatology.