The current practice of snowfall forecasting in Canada is to determine the snow water equivalent (SWE) expected to precipitate using a numerical weather predication model and then multiplying this amount by a snow/SWE ratio to determine the forecast snow depth. The 10:1 "rule of thumb" is still widely used operationally as this ratio, even though it is well-known to introduce error in the forecasts because the density of snow is highly variable. In 2003 Ivan DubE developed a decision tree type algorithm to find the snow/SWE ratio which has subsequently been automated in 2004 by the Meteorological Service of Canada (MSC). The objectives of this study are to explore the behaviour of snow/SWE ratio by developing a Canada-wide climatology of this quantity and examining performance of the MSC algorithm over the winter 2004-2005 using several verification techniques. We found that the mean annual snow/SWE ratio across Canada is 13:1 with large variations temporally and spatially and that the MSC algorithm performed with equal or better skill than the 10:1 algorithm in 84% of the events.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.97936 |
| Date | January 2005 |
| Creators | Cox, Jessica, 1976- |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Science (Department of Atmospheric and Oceanic Sciences.) |
| Rights | © Jessica Cox, 2005 |
| Relation | alephsysno: 002492748, proquestno: AAIMR24649, Theses scanned by UMI/ProQuest. |
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