Characterization of biases and uncertainty in quantitative estimates of precipitation is a critical step in developing useful hydrologic predictions. This is particularly true in warm season convective regimes where the spatial scale of precipitation events often lies below that of in-situ observing networks or where the intensity structures of convective storms are inadequately resolved. While providing spatially and temporally continuous estimates of precipitation remotely sensed products, from both satellites and surface radar networks, each possess error structures which must be accounted for and corrected prior to ingest by a hydrologic model. In this study, we compare the influence of using several in-situ, remotely sensed and model forecasted precipitation products on hydrological simulations from the core region of the North American Monsoon in the complex terrain region of western Mexico. Emphasis is placed on intercomparing the variations in precipitation character between the TRMM multi-satellite precipitation analysis (3B42), the NOAA CMORPH microwave product, an infra-red based product (NESDIS Hydro-Estimator), a ground-based dual polarization radar, rain gauges and the WRF numerical weather prediction model. Spatially-distributed and watershed integrated timeseries of precipitation will be compared as will model simulated streamflow and soil moisture. The impact of the error structures of key precipitation characteristics (duration, intensity and frequency) from the various products on surface hydrologic variables will be assessed and recommendations on future precipitation monitoring for the North American Monsoon system will be made.