Forecasting excessive precipitation remains a challenge for warning operations, which ultimately affects life and property. Verifying quantitative precipitation forecasts using observational data is a key component of the forecast evaluation process. This is important for quantifying model biases regarding precipitation intensity, placement, and coverage, which can later be used to improve model forecasting of precipitation. To address this problem, numerous forecasting products within the Weather Prediction Center (WPC) are used to probabilistically quantify precipitation objects using the Mode Time Domain (MTD) tool, which can be applied to numerical models such as the High Resolution Rapid Refresh (HRRR) model to identify objects of heavy precipitation above a certain threshold on both the hourly and sub-hourly (15-minute) scales. Further, additional verification methods have been developed to quantify error in the WPC Excessive Rainfall Outlook (ERO) and Mesoscale Precipitation Discussion (MPD) products to better understand forecaster biases when forecasting precipitation throughout the CONUS. The dissemination of these products is also improving through the development of webpages with enhanced user interfaces, allowing for more in-depth interrogation of the data.