2.3 Assessing bias in the Canadian snow depth dataset

Monday, 20 June 2005: 11:00 AM
South Ballroom (Hilton DeSoto)
Natasha Neumann, MSC, Saskatoon, SK, Canada; and C. D. Smith and A. Eccleston

Daily snow depth measurements began in Canada in 1941 at the principal observing stations of the Meteorological Service of Canada (MSC), with the stated purpose of collecting observations of the mean depth of snow on the ground in exposed areas. The snow depth record provides the most comprehensive in situ perspective on terrestrial snowcover across Canada. The majority of these sites, however, were located near airports for easy site access and proximity to populated areas. Data from the snow depth observing network has been used to assess climate variability, to validate satellite-derived snow conditions, and to validate snow depletion rates in climate models. The limitations of these measurements (often single points) in adequately representing snow depth for the local area have been questioned but not explored in detail. A rigorous analysis of the efficacy of using these ground observations for model validation and the assessment of the impacts of climate change has similarly not been completed but has widespread implications.

Preliminary analysis of the ability of the Canadian network observations in representing local conditions for a variety of environments across the province of Saskatchewan, Canada, has indicated that the station measurements are generally poor indicators of snowcover conditions in forested areas, varying with stand density characteristics. The station snow depths are more representative of open windswept agricultural environments in the southern portion of the province, but are not indicative of snow accumulations in prairie topographical features which have a significant impact on local hydrology and an unknown influence on satellite-derived SWE measurements. The mean bias was determined for the different biophysical regions of Saskatchewan. Results emphasise the importance of informed use of observational datasets for climate variability studies, and the implications of station siting.

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