Improvement of Snow Gauge Collection Efficiency through a Knowledge of Solid Precipitation Fall Speed - Leroux, Nicolas R.; Thériault, Julie M.; Rasmussen, Roy (Journal of Hydrometeorology, 2021)
Abstract The collection efficiency of a typical precipitation gauge-shield configuration decreases with increasing wind speed, with a high scatter for a given wind speed. The high scatter in the collection efficiency for a given wind speed arises in part from the variability in the characteristics of falling snow and atmospheric turbulence. This study uses weighing gauge data collected at the Marshall Field Site near Boulder, Colorado, during the WMO Solid Precipitation Intercomparison Experiment (SPICE). Particle diameter and fall speed data from a laser disdrometer were used to show that the scatter in the collection efficiency can be reduced by considering the fall speed of solid precipitation particles. The collection efficiency was divided into two classes depending on the measured mean-event particle fall speed during precipitation events. Slower-falling particles were associated with a lower collection efficiency. A new transfer function (i.e., the relationship between collection efficiency and other meteorological variables, such as wind speed or air temperature) that includes the fall speed of the hydrometeors was developed. The root-mean-square error of the adjusted precipitation with the new transfer function with respect to a weighing gauge placed in a double fence intercomparison reference was lower than using previously developed transfer functions that only consider wind speed and air temperature. This shows that the measured fall speed of solid precipitation with a laser disdrometer accounts for a large amount of the observed scatter in weighing gauge collection efficiency.

Improvement of Solid Precipitation Measurements Using a Hotplate Precipitation Gauge - Thériault, Julie M.; Leroux, Nicolas R.; Rasmussen, Roy M. (Journal of Hydrometeorology, 2021)
Abstract Accurate snowfall measurement is challenging because it depends on the precipitation gauge used, meteorological conditions, and the precipitation microphysics. Upstream of weighing gauges, the flow field is disturbed by the gauge and any shielding used usually creates an updraft, which deflects solid precipitation from falling in the gauge, resulting in significant undercatch. Wind shields are often used with weighing gauges to reduce this updraft, and transfer functions are required to adjust the snowfall measurements to consider gauge undercatch. Using these functions reduces the bias in precipitation measurement but not the root-mean-square error (RMSE). In this study, the accuracy of the Hotplate precipitation gauge was compared to standard unshielded and shielded weighing gauges collected during the WMO Solid Precipitation Intercomparison Experiment program. The analysis performed in this study shows that the Hotplate precipitation gauge bias after wind correction is near zero and similar to wind corrected weighing gauges. The RMSE of the Hotplate precipitation gauge measurements is lower than weighing gauges (with or without an Alter shield) for wind speeds up to 5 m s −1 , the wind speed limit at which sufficient data were available. This study shows that the Hotplate precipitation gauge measurement has a low bias and RMSE due to its aerodynamic shape, making its performance mostly independent of the type of solid precipitation.

Adjustments for Wind-Induced Undercatch in Snowfall Measurements Based on Precipitation Intensity - Colli, Matteo; Stagnaro, Mattia; Lanza, Luca G.; Rasmussen, Roy; Thériault, Julie M. (Journal of Hydrometeorology, 2020)
Abstract Adjustments for the wind-induced undercatch of snowfall measurements use transfer functions to account for the expected reduction of the collection efficiency with increasing the wind speed for a particular catching-type gauge. Based on field experiments or numerical simulation, collection efficiency curves as a function of wind speed also involve further explanatory variables such as surface air temperature and/or precipitation type. However, while the wind speed or wind speed and temperature approach is generally effective at reducing the measurement bias, it does not significantly reduce the root-mean-square error (RMSE) of the residuals, implying that part of the variance is still unexplained. In this study, we show that using precipitation intensity as the explanatory variable significantly reduces the scatter of the residuals. This is achieved by optimized curve fitting of field measurements from the Marshall Field Site (Colorado, United States), using a nongradient optimization algorithm to ensure optimal binning of experimental data. The analysis of a recent quality-controlled dataset from the Solid Precipitation Intercomparison Experiment (SPICE) campaign of the World Meteorological Organization confirms the scatter reduction, showing that this approach is suitable to a variety of locations and catching-type gauges. Using computational fluid dynamics simulations, we demonstrate that the physical basis of the reduction in RMSE is the correlation of precipitation intensity with the particle size distribution. Overall, these findings could be relevant in operational conditions since the proposed adjustment of precipitation measurements only requires wind sensor and precipitation gauge data.

How Well Are We Measuring Snow Post-SPICE? - Kochendorfer, John; Earle, Michael; Rasmussen, Roy; Smith, Craig; Yang, Daqing; Morin, Samuel; Mekis, Eva; Buisan, Samuel; Roulet, Yves-Alain; Landolt, Scott; Wolff, Mareile; Hoover, Jeffery; et al. (Bulletin of the American Meteorological Society, 2022)
Abstract Accurate snowfall measurements are necessary for meteorology, hydrology, and climate research. Typical uses include creating and calibrating gridded precipitation products, the verification of model simulations, driving hydrologic models, input into aircraft deicing processes, and estimating streamflow runoff in the spring. These applications are significantly impacted by errors in solid precipitation measurements. The recent WMO Solid Precipitation Intercomparison Experiment (SPICE) attempted to characterize and reduce some of the measurement uncertainties through an international effort involving 15 countries utilizing over 20 types and models of precipitation gauges from various manufacturers. Key results from WMO-SPICE are presented herein. Recent work and future research opportunities that build on the results of WMO-SPICE are also highlighted.