The quantification and correction of wind-induced precipitation measurement errors
- 1ARL/Atmospheric Turbulence and Diffusion Division, National Oceanic and Atmospheric Administration, Oak Ridge, TN 37830, USA
- 2National Centers for Atmospheric Research, Boulder, CO 80305, USA
- 3Norwegian Meteorological Institute, 0313 Oslo, Norway
- 4Cooperative Institute of Climate and Satellites, North Carolina State University, Asheville, NC 28801, USA
- 5National Centers for Environmental Information, National Oceanic and Atmospheric Administration, Asheville, NC 28801, USA
- 6Oak Ridge Associated Universities, Oak Ridge, TN 87830, USA
Abstract. Hydrologic measurements are important for both the short- and long-term management of water resources. Of the terms in the hydrologic budget, precipitation is typically the most important input; however, measurements of precipitation are subject to large errors and biases. For example, an all-weather unshielded weighing precipitation gauge can collect less than 50 % of the actual amount of solid precipitation when wind speeds exceed 5 m s−1. Using results from two different precipitation test beds, such errors have been assessed for unshielded weighing gauges and for weighing gauges employing four of the most common windshields currently in use. Functions to correct wind-induced undercatch were developed and tested. In addition, corrections for the single-Alter weighing gauge were developed using the combined results of two separate sites in Norway and the USA. In general, the results indicate that the functions effectively correct the undercatch bias that affects such precipitation measurements. In addition, a single function developed for the single-Alter gauges effectively decreased the bias at both sites, with the bias at the US site improving from −12 to 0 %, and the bias at the Norwegian site improving from −27 to −4 %. These correction functions require only wind speed and air temperature as inputs, and were developed for use in national and local precipitation networks, hydrological monitoring, roadway and airport safety work, and climate change research. The techniques used to develop and test these transfer functions at more than one site can also be used for other more comprehensive studies, such as the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE).