Accurate, long-term records of precipitation are required for the development of climate-informed decision support tools for agriculture. But rain gauges are too sparsely located to meet this need, and radar-derived precipitation measurements are too recent in duration. Using all readily available station records, spatiotemporally continuous estimates of precipitation were created by the PRISM Climate Group to address this problem. As with all interpolated data, the validity of the gridded PRISM product requires validation, and given the extreme spatiotemporal variability of precipitation, such validation is essential. Previous work comparing the monthly precipitation product against contributing rain gauge data revealed inconsistencies that prompted the analysis reported herein. As a basis for checking the accuracy of the PRISM product, independent precipitation data gathered at a USDA research laboratory in central Oklahoma were quality controlled, including comparison to a co-located automated rain gauge operated by the Oklahoma Mesonet. Results indicate that the independent USDA gauge data are of sufficient quality to use in the evaluation of the PRISM product. The area average of the independent USDA data over a matching size area was then used to validate colocated gridded PRISM estimates. The validation results indicate that the monthly gridded PRISM precipitation estimates are close to the independent observed data in terms of means (smaller by 3% to 4.5%) and cumulative probability distributions (within ~4%), but with variances too small by 7% to 11%. From the point of view of agricultural decision support, these results indicate that PRISM estimates might be useful for probabilistic applications, such as downscaling climate forecasts or driving weather generators, assuming appropriate corrections to the higher-order statistics were applied. However, the number of months with potentially significant differences precludes the use of PRISM estimates for any retrospective month-by-month analyses of possible interactions between climate, crop management, and productivity.