Gridded radar-based quantitative precipitation estimates (QPEs) are potentially ideal inputs for hydrological modeling and monitoring because of their high spatiotemporal resolution. Beam blockage is a common type of bias in radar QPEs related to the blockage of the radar beam by an obstruction, such as topography or tall buildings. This leads to a diminishment in the power of the transmitted beam beyond the range of obstruction and a systematic underestimation of reflectivity return to the radar site. A new spatial analysis technique for objectively identifying regions in which precipitation estimates are contaminated by beam blockage was developed. The methodology requires only a long-term precipitation climatology with no prerequisite knowledge of topography or known obstructions needed. For each radar domain, the QPEs are normalized by climatology and a low-pass Fourier series fit captures the expected precipitation as a function of azimuth angle. Beam blockage signatures are identified as radially coherent regions with normalized values that are systematically lower than the Fourier fit. Precipitation estimates sufficiently affected by beam blockage can be replaced by values estimated using neighboring unblocked estimates. The methodology is applied to the correction of the National Weather Service radar-based QPE dataset, whose estimates originate from the NEXRAD network in the central and eastern United States. The methodology is flexible enough to be useful for most radar installations and geographical regions with at least a few years of data.