Affiliation:
1. Meteorological Research Division, Environment and Climate Change Canada, North York, ON M3H 5T4, Canada
2. Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC H9P 1J3, Canada
Abstract
Accurate measurement of solid precipitation (S) has a critical importance for proper understanding of the Earth’s hydrological cycle, validation of emerging technologies and weather prediction models, and developing parameterizations of severe weather elements such as visibility (Vis). However, measuring S is still a challenging problem, due mainly to wind effects. The wind effects are normally mitigated by using a Double-Fence Automated Reference (DFAR) system to reduce the wind speed (Ug). To contribute towards addressing some of these problems, we have analyzed datasets collected at two sites, Center for Atmospheric Research Experiments (CARE) and Bratt’s Lake, located in southern Ontario and southern Saskatchewan, Canada, respectively, using several instruments. The instruments at CARE include two Geonor gauges, one placed inside a DFAR (SDFAR) and the other inside a double Alter shield (DASG), a Pluvio2 gauge inside a single Alter shield (SASP), a HotPlate, a PARSIVEL2 disdrometer that measures S and fall velocity (V), and an FD12P senor that measures S and type and Vis. The instruments deployed in Bratt’s Lake includes a similar DFAR system and DAS Pluvio2 gauge. The results show that for the Ug observed in this study (Ug < 6 ms−1), both DASG and SASP have similar collection efficiency (CE) of near 70%. The transfer functions (TF) for DASG and SASP as a function of Ug and also Ug, and V were derived. The TF developed for the DASG that includes both Ug and V showed better agreement with observation than just Ug alone. The TF developed for DASG at CARE site was tested using the data collected in Bratt’s Lake and correlated well (R = 0.86), but slightly overestimated the S accumulation by about 12%. The S measured at CARE site using all the other instruments were correlated well with SDFAR (R = 0.9), but the PARSIVEL2 and FD12P overestimated and underestimated the snow amount, respectively, as compared the SDFAR. However, the HotPlate captured similar amount of S as the SDFAR. According to this study, the SDFAR showed good correlation with Vis.
Subject
General Earth and Planetary Sciences
Cited by
1 articles.
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