Snow Atlas

Snow cover duration

Onset and melt-off dates of snow cover are important climate and ecological markers, particularly spring snow melt which has a strong linkage to the climate system (Groisman et al., 1994). Snow cover duration can be derived from surface based observations of daily snow depth, and from satellite information. Surface-based observation are available in Canada from the early 1950s at some sites, but the observing network does not adequately sample mountainous and northern regions. Ruler-based observations of snow depth are also likely to be more subjective as the snowpack becomes shallow and patchy.

The longest period of available satellite data for looking at snow cover is the weekly NOAA dataset. This dataset has a major advantage of complete spatial coverage. However, this is offset by problems discriminating snow in regions with extensive cloud cover and dense forest. The following snow cover climatology maps were derived from the NOAA weekly dataset using data from Rutgers University which includes the corrections recommended by Robinson et al. (1993).

Snow Depth

The depth of snow on the ground is important in relation to surface energy exchanges, frost penetration, and plant and animal ecology. Within Canada, daily snow depth data are used in many applications such as roof snow load calculations for the National Building Code, snow clearing contracts, winter survival of crops, biological studies, calculation of forest fire severity and validation of satellite algorithms and snow process models. Canadian daily snow depth data have also been used to reconstruct snow-covered area to extend the satellite snow cover extent record back to the early 1900s (Brown, 2000).

Regular daily snow depth measurements are made by ruler at several hundred climate and weather observing stations across Canada. However, these sites tend to be concentrated in populated areas at lower elevations and are only point estimates. Satellite-derived snow depth estimates are currently not sufficiently reliable to use in constructing a snow depth climatology for Canada. Brown et al. (2003) derived a snow depth climatology for Canada based on the snow depth analysis scheme developed by Brasnett (1999) and employed operationally at the Canadian Meteorological Centre (CMC). The method was applied to generate a 0.3° latitude/longitude grid of monthly mean snow depth and corresponding estimated water equivalent for North America to evaluate GCM snow cover simulations for the Atmospheric Model Intercomparison Project II (AMIP II) for the period 1979-96. Approximately 8000 snow depth observations per day were obtained from U.S. cooperative stations and Canadian climate stations for input to the analysis. The first-guess field used a simple snow accumulation, aging and melt model driven by 6-hourly values of air temperature and precipitation from the European Centre for Medium-range Weather Forecasting (ECMWF) ERA-15 Reanalysis with extensions from the Tropical Ocean Global Atmosphere (TOGA) operational data archive. Monthly means snow depths are provided below. The datasets used to derived these maps can be downloaded from the Canadian Cryospheric Information Network. The monthly averages are considered most reliable south of about 55°N where the snow depth observing network is relatively dense. Further details about the derived data can be obtained from Brown et al. (2003).

Monthly mean snow depth maps (cm):

May

Dec.

Animation of monthly mean snow depth maps

Snow Water Equivalent (SWE)

Several sources of information are available for mapping SWE. Many government agencies and hydro-power authorities take regular (usually at two-weekly intervals) measurements of snow depth and mass over a series of points termed a "snow course". Canadian snow courses also tend to be concentrated in southern regions of Canada, but there is less low elevation bias than the daily snow depth network. An overview of the methodology and techniques for ground-based measurements of snow cover is provided by Woo (1997).

Both active and passive microwave satellites have demonstrated an all-weather ability to map snow water equivalent over selected types of terrain. Snow water equivalent maps are routinely derived from passive microwave data for the [Canadian Prairies] and are used extensively by water resource managers. Scientists are currently working to extend this method to other environments such as forest, where snow cover microwave signatures are more difficult to interpret.

The following maps of mean monthly SWE were derived from objective analysis of daily snow depth data by Brown et al (2003) with snow density information estimated from a simple snow model (see description of method above). The datasets used to derived these maps can be downloaded from the Canadian Cryospheric Information Network .

Monthly mean SWE maps (mm):

May

Dec.

Snow Density

Snow density information is important for a variety of needs such as the thermal properties of a snowpack (low density snow is a good insulator), trafficability, and the potential for snow to be eroded by wind. One of the main sources of snow density information in Canada is bi-weekly snow course measurements. These are not evenly distributed in space (see SWE section above) and time, and the bulk of the currently available historical observations come from the twenty-year period 1966-1985. The number of available observations declined considerably after 1985 with the curtailment of a nationally-coordinated program to collect and publish snow course data from agencies across Canada. The number of snow course observation has also declined substantially in recent years due to budget cutbacks.

An approximate idea of the large-scale seasonal and spatial variation in snow density can be obtained from simple interpolation of the available snow course observations in the Canadian SNOW CD(MSC, 2000). The following maps of mean snow density from December to April clearly show the seasonal evolution in snow density, as well as the spatial variability with higher snow densities in mountains and coastal regions, and the lowest snow densities over the boreal forest zone.

Apr.