Precipitation is a challenging parameter to model and measure accurately, making in situ observations from networks, like the approximately 3,400 USGS precipitation stations, especially valuable. Ensuring the accuracy of these observations is critical, particularly because provisional data is made publicly available in near real time. Station measurements are affected by various types of errors, several of which occur randomly in an unpredictable manner. The DRIP application is a threshold-based tool that leverages existing NOAA and USGS data to automatically identify potentially anomalous measurements to help maximize station uptime, prevent skewing of precipitation totals, and streamline field response.
