The uncertainty of hydrologic predictions is closely related to the uncertainty of the inputs of which precipitation is the most important. Emplacement of the WSR-88D radar network and the development of automated adjustment algorithms are examples of the significant enhancements in an attempt to improve the measurement of precipitation. In addition to finding the appropriate Z-R relationship, there are several other challenges that need to be addressed in order to adjust radar estimates to bring them as close as possible to the observed truth. One such challenge is how to use available rain gauge observations to adjust radar-estimated precipitation. Simulation studies and data-based analyses demonstrate that radar range has significant influence on the accuracy of the radar-estimated precipitation. An important question is “Is it possible to detect range effects by analyzing a single or a few events?”. The WSR-88D PPS rainfall adjustment algorithm is based on a well-established algorithm; can simpler approaches of radar-rain gauge adjustments perform better? Radar and rain gauge precipitation estimate from several experiments, PRECIP98, CASES97, IHOP2002, were analyzed to address these and other questions. High quality data sets from NEXRAD, NCAR S-Pol, and rain gauge networks were used to conduct a comprehensive comparison among the radar systems and rain gauge estimates. Instantaneous and storm accumulated precipitation estimates were compared at different spatial and temporal scales. Issues such as accuracy of interpolation, grid size and shape, and distance from the radar were emphasized. Moreover, the S-Pol has higher spatial and temporal resolutions than the NEXRAD. The effects of higher spatial and temporal resolution on radar-rain gauge comparisons were also investigated.