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David G. Baggaley
John M. Hanesiak


Blowing snow has a major impact on transportation and public safety. The goal of this study is to provide an operational technique for forecasting high-impact blowing snow on the Canadian arctic and the Prairie provinces using historical meteorological data. The focus is to provide some guidance as to the probability of reduced visibilities (e.g., less than 1 km) in blowing snow given a forecast wind speed and direction. The wind character associated with blowing snow was examined using a large database consisting of up to 40 yr of hourly observations at 15 locations in the Prairie provinces and at 17 locations in the arctic. Instances of blowing snow were divided into cases with and without concurrent falling snow. The latter group was subdivided by the time since the last snowfall in an attempt to account for aging processes of the snowpack. An empirical scheme was developed that could discriminate conditions that produce significantly reduced visibility in blowing snow using wind speed, air temperature, and time since last snowfall as predictors. This process was evaluated using actual hourly observations to compute the probability of detection, false alarm ratio, credibility, and critical success index. A critical success index as high as 66% was achieved. This technique can be used to give an objective first guess of the likelihood of high-impact blowing snow using common forecast parameters.

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Qiang Huang
John Hanesiak
Sergiy Savelyev
Tim Papakyriakou
, and
Peter A. Taylor


A field study on visibility during Arctic blowing snow events over sea ice in Franklin Bay, Northwest Territories, Canada, was carried out from mid-January to early April 2004 during the Canadian Arctic Shelf Exchange Study (CASES) 2003–04 expedition. Visibilities at two heights, wind and temperature profiles, plus blowing and drifting snow particle flux at several heights were monitored continually during the study period. Good relations between visibility and wind speed were found in individual events of ground blowing snow with coefficients of determination >0.9. Regression equations relating 1.5-m height visibility to 10-m wind speed can be used for predicting visibility with a mean relative error in the range of 19%–32%. Similar regression functions obtained from the data for observed visibility of less than 1 km could predict visibilities more accurately for more extreme visibility reductions and wind speeds (>9.5 m s−1) with mean relative error ranging from 15% to 26%. For the event of ground blowing snow, a simple power law relationship between wind speed and visibility is sufficient for operational purposes. A poorer relationship was observed in the event of blowing snow with concurrent precipitating snow. A theoretical visibility model developed by Pomeroy and Male fit well with observed visibilities if using a mean radius of 50 μm and an alpha value of 10. The predicted visibility had a mean relative error of 30.5% and root-mean-square error of 1.3 km. The observed visibility at 1.5 m had a strong relation with particle counter readings, with an R 2 of 0.92, and was consistent among all events.

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