Solid Precipitation Measurement Intercomparison in Bismarck, North Dakota, from 1988 through 1997

作者: Karen R. Ryberg , Douglas G. Emerson , Kathleen M. Macek-Rowland

DOI: 10.3133/SIR20095180

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摘要: A solid precipitation measurement intercomparison was recommended by the World Meteorological Organization (WMO) and initiated after approval ninth session of Commission for Instruments Methods Observation. The goal to assess national methods measuring against whose accuracy reliability were known. field study started in Bismarck, N. Dak., during 1988–89 winter as part intercomparison. last official season WMO 1992–93; however, Bismarck site continued operate through 1996–97. Precipitation events at categorized snow, mixed, or rain on basis descriptive notes recorded not further analyzed this study. Catch ratios (CRs)—the ratio catch each gage true (the corrected double fence reference)—were calculated. Then, regression analysis used develop equations that model snow mixed CRs functions wind speed temperature. Wind gages, temperature, upper air conditions (wind temperature 700 millibars pressure) possible explanatory variables multiple done modeled using Tretyakov gage, shielded unshielded AeroChem with fence, Wyoming windshield. As earlier studies WMO, found influence CR gage. However, study, variable represented average over duration event. did use its analysis. gages where be influenced only, other studies, but an 1987–93. had a highly varied number related CR. Despite extensive efforts find no statistically significant 0.05 level statistical significance. windshield variables, relation highest coefficient determination (R2 = 0.572) adjusted (Ra 0.476) all models identified any Three evaluated could compared those advantage much larger dataset than data longer time period. Snow is depending equipment weather conditions. Much variation accounted developed particularly gages. Extensive attempts made data, it concluded sample sizes large enough CRs. test equations. are similar they more likely underestimate when observed amounts small overestimate relatively large. Mixed underestimated adjustment Results show precision varies greatly varied, both

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