We evaluate the results of dynamically downscaled winter precipitation over Western Montana using the weather research and forecasting (WRF) model through comparison with estimates from the observationally based parameter-elevation regressions on independent slopes model (PRISM). Seven years (six winters) from 2000 to 2006 are simulated at 4 km resolution to assess the similarities and differences between the two models as well as the implications for hydrologic modeling. Inherent biases in both approaches are apparent, highlighting the difficulty in climate model validation. Results show general agreement between the two models in the spatial distribution of winter precipitation. A principal component analysis shows similar spatial patterns between models in the leading six components suggesting that the main processes that drive the spatial distribution of precipitation were properly captured. The first component explains almost 70% of total variance, and the first three components explain more than 85% in both data sets. The largest differences between the two data sets exist in areas at high elevation and upstream of the continental divide where observations are sparse. In these areas, WRF consistently predicts higher amounts of precipitation and larger interannual variability than PRISM. We suggest that these results are realistic for impingement of moist air masses on topography and, if correct, could have significant implications in flood forecasting, water resource management, and climate change studies.