Understanding Winter Precipitation Impacts on Automated Gauge Observations within a Real-Time System

Abstract

Precipitation gauge observations are routinely classified as ground truth and are utilized in the verification and calibration of radar-derived quantitative precipitation estimation (QPE). This study quantifies the challenges of utilizing automated hourly gauge networks to measure winter precipitation within the real-time Multi-Radar Multi-Sensor (MRMS) system from 1 October 2013 to 1 April 2014. Gauge observations were compared against gridded radar-derived QPE over the entire MRMS domain. Gauges that reported no precipitation were classified as potentially stuck in the MRMS system if collocated hourly QPE values indicated nonzero precipitation. The average number of potentially stuck gauge observations per hour doubled in environments defined by below-freezing surface wet-bulb temperatures, while the average number of observations when both the gauge and QPE reported precipitation decreased by 77%. Periods of significant winter precipitation impacts resulted in over a thousand stuck gauge observations, or over 10%–18% of all gauge observations across the MRMS domain, per hour. Partial winter impacts were observed prior to the gauges becoming stuck. Simultaneous postevent thaw and precipitation resulted in unreliable gauge values, which can introduce inaccurate bias correction factors when calibrating radar-derived QPE. The authors then describe a methodology to quality control (QC) gauge observations compromised by winter precipitation based on these results. A comparison of two gauge instrumentation types within the National Weather Service (NWS) Automated Surface Observing System (ASOS) network highlights the need for improved gauge instrumentation for more accurate liquid-equivalent values of winter precipitation.