This data set consists of Northern Hemisphere daily snow depth analysis data processed by the Canadian Meteorological Centre (CMC). Snow depth data obtained from surface synoptic observations (synops), meteorological aviation reports (metars), and special aviation reports (SAs) were acquired from the World Meteorological Organization (WMO) information system for use in the CMC analyses. This CMC data set includes daily observations from 1998 through 2012 and will be updated annually. Monthly averages and monthly climatologies of snow depth and estimated Snow Water Equivalent (SWE) are provided, where SWE was estimated using a density look-up table. The volume of the data set is approximately four gigabytes. Data are provided in tab-delimited ASCII text files and are available via FTP.
The following example shows how to cite the use of this data set in a publication. For more information, see our Use and Copyright Web page.
Brown, R. D. and B. Brasnett. 2010, updated annually. Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data. [indicate subset used]. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice Data Center.
Important: These data are provided by Environment Canada
for research purposes only. Refer to the Conditions
of Data Use section before working with these data.
|Data format||ASCII tab-delimited text
Audio-Visual Interleave (AVI animation)
Graphic Interchange Format (GIF image)
|Spatial coverage and resolution||Southernmost Latitude: 0° N
Northernmost Latitude: 90° N
Westernmost Longitude: 180° W
Easternmost Longitude: 180° E
Spatial resolution: 24 km
|Temporal coverage and resolution||01 August 1998 - 31 December 2012
Daily data collection
|Tools for accessing data||Any text editor or Web browser
Any video/media player software
|File naming convention||File names vary; refer to Table 2 for
details on file name variables.
|File size||1 - 900 MB|
Snow Water Equivalent (SWE)
|Procedures for obtaining data||Data are available via FTP.|
Ross D. Brown
Climate Processes and Earth Observation Division
Environment Canada @ Ouranos
550 Sherbrooke St. West, 19th Floor
Montréal QC H3A 1B9
Meteorological Service of Canada
2121 Trans Canada Highway
Dorval, QC H9P 1J3
NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449 USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
The CMC data files are in ASCII tab-delimited format for the Northern Hemisphere and have been interpolated to a 24 km resolution (706 x 706 pixel) polar stereographic grid that closely approximates the grid used for the NOAA Interactive Multisensor Snow and Ice Mapping System (IMS) daily snow cover product.
A Northern Hemisphere subset of the daily global analysis was created on a standard 24 km polar stereographic grid that closely approximates the grid used by NOAA for the 24 km daily IMS snow product. At 706 pixels, the grid covers a slightly smaller area than the full 1024-pixel IMS grid. The land/sea mask should be used to remove snow over sea ice and over Greenland.
North Polar Stereographic
NI = 706, NJ=706 (bottom left grid point = 1,1)
Grid rotation -10°
Pole position = 353, 353
Grid resolution at 60°N = 23812.5 m
The latitude and longitude coordinates corresponding to the center of each grid point is provided in the file cmc_analysis_ps_lat_long.txt.
Each file contains one year of data with the following FORTRAN statements:
do 1001 iday=1,ndays ! 365 or 366 depending on # days in year
write(60,*) idate ! date in format YYYYMMDDHH where HH is always 00
do 1002 i=1,NI
write(60,100) (sdep(i,j),j=1,706) !cm
100 format(706(1x,f5.1)) !values exceeding 1000 set to 999.9
Note: In 1998, the data start at 01 August, listed as 1998080100 in the data file.
The CMC analysis includes snow on sea ice. A custom binary (0,1) land/sea mask is provided to mask out ocean areas and Greenland. Land (mask=1) was assigned for grid land cover fractions greater than or equal to fifty percent. The array should be read in as follows:
do 5 i=1,706
Monthly average snow depth data are included with one year of data per file with naming convention: cmc_analysis_mly_avg_YYYY.txt. An upper snow depth limit of 600 cm was applied to the recent analyses to maintain continuity. The land/sea mask should be used to remove snow over sea ice and over Greenland where the analysis is unreliable.
Each file contains one year of data with the following FORTRAN statements:
do 1000 imon=1,12
do 1001 i=1,ni
write(60,100) (sd_avg(i,j),j=1,706) !cm
Note: In 1998, the data start
The directory structure on the FTP site is described in Table 1.
||Description of Directory Contents|
|nsidc0447_CMC_snow_depth_v01||Along with three subdirectories, the top-level directory contains the
cmc_analysis_ps_lat_long.zip: Provides the position of grid points (latitude/longitude coordinates) for the Northern polar stereographic grid centered on the pole
cmc_analysis_lsmask_binary_nogl.zip: Land/sea mask defining ocean points for the data set
ps_cmc_sdepth_analyses_yyyy_ascii.zip: Snow depth analyses data files
|Monthly_Climatologies||This directory contains the following files:
cmc_monthly_mean_sdep_animation_1999-2006.avi: Snow depth animation file
cmc_sdep_legend.gif: Snow depth legend file
cmc_sdep_mly_climatol_1998to2011.txt.gz: Snow depth climatology file
cmc_swe_mly_climatol_1998to2011.txt.gz: SWE climatology file
|Monthly_Snow_Depth_Files||Contains monthly average files for each year from 1998-2012:
|Monthly_SWE_Estimates||Contains one monthly SWE file for 1998-2012:
For a description of file names, refer to Table 2.
The data files employ a variety of naming
conventions. All file name variables are listed and described in Table 2.
|cmc||Refers to the Canadian Meteorological Centre|
|ps||Refers to the Polar Stereographic grid|
|ims||Refers to the Interactive Multisensor Snow and Ice Mapping System|
|nogl||No Greenland (used in land/sea mask file that masks out Greenland)|
|swe||Snow Water Equivalent|
|.zip||Indicates this is a zipped file|
|.gz||Indicates this is a zipped file|
|.txt||Indicates this is an ASCII text file|
|.avi||Indicates this is an animation file|
|.gif||Indicates that this is a GIF image file|
The files included in this data set range from approximately 1 MB to 900 MB.
Southernmost Latitude: 0° N
Northernmost Latitude: 90° N
Westernmost Longitude: 180° W
Easternmost Longitude: 180° E
The analysis has a resolution of 1/3° Gaussian. The error correlations used by the analysis have an e-folding distance of approximately 120 km horizontally and 800 m vertically.
Data include daily observations from 01 August 1998 to 31 December 2012.
The analysis is updated every six hours, but only the 00 hour analysis is archived in this data set.. For more information, refer to the Processing Steps section of this document.
This data set includes all available real-time snow depth observation measurements from synops, metars, and SAs.
Monthly average estimates of SWE (mm) are also included in this data set. Monthly average SWE for the October through June period of each year was estimated from monthly average snow depth files applying a look-up table (see Table 3) of mean monthly snow density values. Mean monthly snow density values were derived from Canadian snow course observations corresponding to snow climate classes in the Sturm et al. (1995) classification. The July through September time period was not processed due to a lack of observed snow density information during the time period.
Table 3 lists the mean monthly snow density look-up table used
to estimate SWE based on Canadian snow course observations averaged over the
snow-climate classes defined by Sturm et al. (1995)
and Mote, 2009). This assumes the Canadian density
observations are representative of snow-climate classes in other regions of
the Northern Hemisphere.
The method used in Sturm et al. (1995) for snow climate classification interpolated from the 0.5° by 0.5° gridded version at the National Snow and Ice Data Center (NSIDC) (Liston and Sturm 1998) to the 24 km polar stereographic grid of the monthly averaged snow depth. This process resulted in land/sea confusion at a number of points which were excluded from the analysis. The number of points affected by this problem (nconf) is indicated in the header record for each month.
The SWE estimates are contained in a single file (cmc_mly_swe_1998to2012.txt) with -999.0 values at all grid points where SWE could not be calculated (such as ocean or Sturm snow-class undefined). Greenland was excluded from the analysis as the analysis is considered unreliable in this area. Values were written as tab-delimited with the following FORTRAN statements:
do 1002 i=1,ni
write(60,107) (swe(i,j),j=1,706) !mm
Note: In 1998, values start on 01 August.
Monthly average snow depth and SWE climatologies for the 1998/99 to 2011/12 snow seasons are included along with an animation of monthly mean snow depth averaged over the 1999-2006 period (cmc_monthly_mean_sdep_animation_1999-2006.avi). The land/sea mask was applied to these outputs. A legend for the snow depth animation is included in a separate GIF image file; units are cm.
The monthly snow depth climatology includes values from January to December while the SWE climatology includes values from October to June. Both files are written in comma-delimited latitude-longitude tagged format with a single header record containing the variable names.
Figure 1 displays an example of the CMC analysis
data used for evaluating Global Climate Model (GCM) output from Brown
and Mote (2008).
|Figure 1. Sample
of CMC Analysis Data Used for Evaluating Model Output
Comparison of thirteen GCM mean SWEmax (panel 2) with estimated SWEmax from CMC daily snow depth analyses (panel 1) for 2001-2006. The mean model bias (model-CMC) is shown in panel 3. From top to bottom, Figure 1 displays panels 1, 2, and 3. Sample analysis image courtesy of Ross Brown.
A complete description of the analysis methodology and validation is published in Brasnett (1999). The methodology was applied to carry out a reanalysis of snow depths over North America for the Atmospheric Model Intercomparison Project - 2 (AMIP-2) project from 1979-1997 using a more elaborate snow model for the first guess field (Brown, et al. 2003). The scheme makes use of an analysis of screen-level temperature produced with vertical correlations taken into account.
Over most of the Arctic region there are no observations, so the analysis is based on estimated snow depths from the first guess field. In addition, snow depth observations over northern Canada tend to be biased to coastal locations with observing sites at open areas near airports. The snow at these sites tends to be shallower and to melt out earlier than snow in surrounding terrain.
In cold, high precipitation environments, such as Greenland,
the snow accumulation is capped at 600 cm to avoid excessive amounts
of snow accumulating. The analysis is not considered reliable in these
regions. This limit was changed to 1200 cm in October 2008 when a Limited
Area Model (LAM) version of the analysis was implemented over British Columbia.
Verification of that product showed it had insufficient residual snow during
the summer months due to the 600 cm limit, so the limit was also changed
in the global analysis. Mean annual snowfall in some locations in British
Columbia exceeds 1000 cm, so this limit is not unreasonable. The following
mean annual snowfall levels for the 1951 through 1980 normal climate
period confirms this assertion:
Allison Pass: 1431.5 cm
Rogers Pass: 1106.7 cm
Pine Pass: 1075.5
Tahtsa Lake: 1041.2
Mt. Fidelity: 1974.8 cm
Values exceeding 1000 cm after 01 January 2007 were set to 999.9 to conform to the existing database format.
The analysis had been run essentially unchanged from 12 March
1998. An error was introduced into the operational implementation of the analysis
in October 2006, but this has been corrected in offline runs and an offline
version of the analysis is being run in parallel with the operational analysis
to maintain data continuity.
Prior to 04 January 2010, the analyses from October 2006 were inadvertently run with the vertical correlation component of the optimal interpolation switched off which would have affected snow depths in mountainous areas. These files were corrected and replaced on 04 January 2010. The error resulted in slightly lower continental snow cover extent (less than 10 percent) from October to June, but 10 to 20 percent underestimates of snow cover extent from July to September.
A change in the resolution of the GEM model generating the forecast precipitation fields in 31 October 2006 from 100 km to 33 km has likely resulted in increased SWE values. A preliminary evaluation over Arctic land areas suggests maximum SWE values are approximately 20 mm higher after the implementation of the higher resolution version of GEM.
Data prior to 01 August 1998 have been removed from the data archive as the snowpack model used in the analysis was unable to be properly initialized for the 1997/98 snow season. The snow depths have been determined to be anomalously high in consequence.
Snow depth and SWE values over Arctic land areas in March, April, and May 2002 are anomalously low compared to other data sets. There is evidence from Canadian in situ observations that spring 2002 snow depths were the shallowest observed since 1951. However, the striking discrepancy between CMC and other data sets in these particular months suggests it may be prudent to exclude them from any analysis.
Data are available via FTP.
The volume of this data set is approximately four gigabytes.
Tools appropriate for viewing these data include any video or media software package and any text editor or Web browser.
Real-time snow depth data were originally acquired from the World Meteorological Organization (WMO) information system.
The analysis is updated every six hours using the method of optimum interpolation with an initial guess field provided by a simple snow accumulation and melt model using analyzed temperatures and forecast (six hour) precipitation from the CMC Global Environmental Multiscale (GEM) forecast model. The precipitation is assumed to be snow if the analyzed screen-level temperature is less than 0 degrees. A degree-day melting algorithm removes mass from the snowpack at the rate of 0.15 mm-h-1-K-1.
In regions where there are no observations of snow depth, the snow depth shown in the analysis corresponds to the initial guess field simplified assumptions regarding snowfall, melt and aging.
Note: When there is an ice cover, the analysis will accumulate snow on it so the snow field can extend over water bodies. This can be masked out if desired.
The first-guess snow model assumes the density of new snow
to be 100 kg/m3 and the snowpack gradually increases in density as it ages.
The increase in density with aging stops when the density reaches 300kg/m3
(except 210 kg/m3 if the vegetation is needleleaf forest, since in these
regions the canopy shelters the snowpack from wind and sunlight and densities
are less). New snow causes the density to decrease by an amount related
to the mass of the new snow and the mass of the existing snowpack. During
melting, the density is allowed to increase up to a maximum of 550 kg/m3.
Table 4 lists the acronyms and abbreviations used in this document.
|AMSR-E||Advanced Microwave Scanning Radiometer - Earth Observing System|
|AMIP-2||Atmospheric Model Intercomparison Project - 2|
|ASCII||American Standard Code for Information Interchange|
|AVI||Audio-Visual Interleave (video format)|
|CMC||Canadian Meteorological Centre|
|DAAC||Distributed Active Archive Center|
|FTP||File Transfer Protocol|
|GCM||Global Climate Model and/or General Circulation Model|
|GEM||Global Environmental Multiscale|
|GIF||Graphic Interchange Format|
|IMS||Interactive Multisensor Snow and Ice Mapping System|
|LAM||Limited Area Model|
|Metars||Meteorological aviation reports|
|NASA||National Aeronautics and Space Administration|
|NOAA||National Oceanic and Atmospheric Administration|
|NSIDC||National Snow and Ice Data Center|
|SA||Special Aviation report|
|SWE||Snow Water Equivalent|
|Synops||Surface synoptic observations|
|URL||Uniform Resource Locator|
|WMO||World Meteorological Organization|