Because knowledge of the melting level is critical to river forecasters and other users, an objective algorithm to detect the brightband height from profiles of radar reflectivity and Doppler vertical velocity collected with a Doppler wind profiling radar is presented. The algorithm uses vertical profiles to detect the bottom portion of the bright band, where vertical gradients of radar reflectivity and Doppler vertical velocity are negatively correlated. A search is then performed to find the peak radar reflectivity above this feature, and the brightband height is assigned to the altitude of the peak. Reflectivity profiles from the off-vertical beams produced when the radar is in the Doppler beam swinging mode provide additional brightband measurements. A consensus test is applied to subhourly values to produce a quality-controlled, hourly averaged brightband height. A comparison of radar-deduced brightband heights with melting levels derived from temperature profiles measured with rawinsondes launched from the same radar site shows that the brightband height is, on average, 192 m lower than the melting level. A method for implementing the algorithm and making the results available to the public in near–real time via the Internet is described. The importance of melting level information in hydrological prediction is illustrated using the NWS operational river forecast model applied to mountainous watersheds in California. It is shown that a 2000-ft increase in the melting level can triple run off during a modest 24-h rainfall event. The ability to monitor the brightband height is likely to aid in melting-level forecasting and verification.