Quantifying Uncertainty and Biases in Automated Precipitation Measurements

Precipitation measurements are relied upon by policy makers, hydrologists, and watershed managers to quantify and allocate the water available for society's needs. In addition to this, precipitation measurements are necessary to understand our changing climate and for public safety in areas as diverse as avalanche control, flood forecasting, roadway safety, and aircraft de-icing operations. Although precipitation has been measured for many centuries and the need to continue monitoring precipitation will continue for the foreseeable future, precipitation measurements are still beset with significant biases and errors. Solid precipitation is particularly difficult to measure accurately, and biases between winter-time precipitation measurements made using different technologies, different measurement networks, or in different regions can be greater than 50%. A need to inter-compare different measurement systems and to better understand the automated precipitation gauges that have proliferated in the last 20 years has spawned the creation of the WMO Solid Precipitation Intercomaparison Exerperiment (WMO-SPICE), which is an international intercomparison of automated and manual solid precipitation measurement techniques. The NOAA/FAA/NCAR Winter Precipitation Testbed in Marshall, CO is participating in this study, and the findings from this well-established testbed have contributed to the analysis and measurement techniques implemented in WMO-SPICE. Recent results and analysis techniques from these intercomparisons, with a focus on U.S. contributions to WMO-SPICE, will be presented here.