Historical gridded snow water equivalent and snow cover fraction over Canada from remote sensing and land surface models
Download observation-based datasets of monthly snow cover fraction (SCF), monthly snow water equivalent (SWE) and annual maximum snow water equivalent (SWEmax) over Canada for 1981-2016.
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- Technical notes
- Data and processing
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Annual maximum snow water equivalent
Datasets of monthly snow cover fraction (SCF), monthly snow water equivalent (SWE), and annual maximum snow water equivalent (SWEmax) over Canada are constructed using a multi-dataset approach for the time period, 1981-2016.
For further details on the methodology and analyses of the datasets, please see Mudryk et al. (2015)Footnote 1.
Table 1. Main Characteristics
|Datasets and units||
Monthly snow cover fraction
Monthly snow water equivalent
Annual maximum snow water equivalent
|Spatial resolution and geographical coverage||0.25x0.25 degree grid resolution across Canada|
Snow cover fraction: monthly
Snow water equivalent: monthly
Maximum snow water equivalent: annual
Data and processing
Monthly snow cover fraction (SCF) and monthly snow water equivalent (SWE) are calculated using daily SWE data taken from the following four sources over the 35-year period from 1981 to 2016.
Four sources of daily SWE data:
- The Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) (Global Modeling and Assimilation Office, 2016Footnote 2; Gelaro et al., 2017Footnote 3) is a National Aeronautics and Space Administration (NASA) atmospheric reanalysis product generated with the Goddard Earth Observing System Model, Version 5.2.0 (GEOS-5), atmospheric general circulation model and atmospheric data assimilation system (ADAS).
- The temperature index model described by Brown et al. (2003)Footnote 4 reconstructs daily SWE using 6-hourly temperature field and 12-hourly precipitation field inputs from ERA-Interim reanalysis. This simplified index model includes most of the temperature-dependent processes included in the snow component of numerical land surface schemes (e.g. partitioning of precipitation into solid and liquid fractions, melt from rain-on-snow events, specification of new snowfall density, snow aging, and snowmelt).
- The physical snowpack model Crocus simulates daily SWE using meteorology from ERA-Interim (Brun et al., 2013Footnote 5).
- The European Space Agency GlobSnow product (Version 2; www.globsnow.info, last access: 20 September 2016) is a gridded product derived through a combination of satellite passive microwave data, forward snow emission model simulations, and climate station observations for non-alpine regions of the Northern Hemisphere (Takala et al., 2011Footnote 6).
The GlobSnow product is partially masked over mountainous regions, defined as regions with a slope of 2 degrees or larger. SWE was replaced in grid cells which contain mountains with a blend of the GlobSnow SWE data (if any) and the mean value from the other three data sources. The weighting for the blend was determined by the fraction of the grid cell area which is mountainous. For grid cells with no mountainous terrain, unaltered GlobSnow data are used. As the fraction of mountainous terrain increases, the weight applied to the GlobSnow data is linearly reduced, reaching zero for grid cells containing only mountainous terrain.
Regridding daily snow water equivalent (SWE) data
For a given dataset of daily SWE, the data was interpolated to a regular 0.25 degree grid over Canada.
Monthly snow cover fraction (SCF)
Monthly SCF is produced by applying a 4mm threshold to each of the four daily SWE fields to produce a daily binary snow cover field; this daily field is averaged over each month to produce a monthly snow cover fraction and the four data sets are averaged together.
Monthly snow water equivalent (SWE)
Monthly SWE is produced by averaging the regridded daily SWE fields from each source over the given month.
Annual maximum snow water equivalent (SWEmax) fields
Annual maximum SWE fields are calculated as the maximum value of daily SWE attained at each grid location over a given snow season.
Note: grid cell values for SCF, SWE and SWEmax have been weighted by the fraction of land surface within each grid cell (excluding ocean, lakes and glaciers/ice caps). For example, a grid cell containing 50% land and 50% ocean which is fully snow-covered for the month will have a listed SCF value of 50%.
Open Government Licence - Canada (http://open.canada.ca/en/open-government-licence-canada).