Methods to Calculate Precipitation from Weighing-Bucket Gauges with Redundant Depth Measurements

Ronald D. Leeper, Michael A. Palecki, Egg Davis
2015 Journal of Atmospheric and Oceanic Technology  
The U.S. Climate Reference Network (USCRN) monitors precipitation using a well-shielded Geonor T-200B gauge. To ensure the quality and continuity of the data record, the USCRN adopted an innovative approach to monitor precipitation using redundant technology: three vibrating-wire load sensors measuring the liquid depth of a weighing-bucket gauge. In addition to detecting and flagging suboptimally operating sensors, quality assurance (QA) approaches also combine the redundant observations into a
more » ... observations into a precipitation measurement. As an early adopter of this technology, USCRN has pioneered an effort to develop QA strategies for such precipitation systems. The initial USCRN approach to calculating precipitation from redundant depth observations, pairwise calculation (pairCalc), was found to be sensitive to sensor noise and gauge evaporation. These findings led to the development of a new approach to calculating precipitation that minimized these nonprecipitation impacts using a weighted average calculation (wavgCalc). The two calculation approaches were evaluated using station data and simulated precipitation scenarios with a known signal. The new QA system had consistently lower measures of error for simulated precipitation events. Improved handling of sensor noise and gauge evaporation led to increases in network total precipitation of 1.6% on average. These results indicate the new calculation system will improve the quality of USCRN precipitation measurements, making them a more reliable reference dataset with the capacity to monitor the nation's precipitation trends (mean and extremes). In addition, this study provides valuable insight into the development and evaluation of QA systems, particularly for networks adopting redundant approaches to monitoring precipitation.
doi:10.1175/jtech-d-14-00185.1 fatcat:ahpppkr5nndanjae372lnhpyse