This data set contains snow pack properties, such as depth and snow water equivalent (SWE), from the NOAA National Weather Service's National Operational Hydrologic Remote Sensing Center (NOHRSC) SNOw Data Assimilation System (SNODAS). SNODAS is a modeling and data assimilation system developed by NOHRSC to provide the best possible estimates of snow cover and associated parameters to support hydrologic modeling and analysis.
DOWNLOADING DATA VIA FTP
Data can be downloaded through a Web browser or command line via FTP. When using a Web browser, the FTP link first directs you to an Optional Registration Form that if filled out, will allow you to receive notifications about updates or processing changes related to that specific data set. After completing the Optional Registration Form, the FTP directory becomes available. For additional help downloading data through an FTP client, go to the How to access data using an FTP client support page.
Snow Data Assimilation System (SNODAS) Data Products at NSIDC, Version 1
|Temporal Resolution:||1 day|
|Platform(s)||AIRCRAFT, GROUND STATIONS, MODELS, SATELLITES|
|Data Contributor(s):||Tom Carroll|
|Metadata XML:||View Metadata Record|
As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.National Operational Hydrologic Remote Sensing Center. 2004. Snow Data Assimilation System (SNODAS) Data Products at NSIDC, Version 1. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: http://dx.doi.org/10.7265/N5TB14TC. [Date Accessed].
This data set contains output from the NOAA National Weather Service's National Operational Hydrologic Remote Sensing Center (NOHRSC) SNOw Data Assimilation System (SNODAS). SNODAS is a modeling and data assimilation system developed by NOHRSC to provide the best possible estimates of snow cover and associated parameters to support hydrologic modeling and analysis. The aim of SNODAS is to provide a physically consistent framework to integrate snow data from satellite, airborne platforms, and ground stations with model estimates of snow cover (Carroll et al. 2001). SNODAS includes procedures to ingest and downscale output from the Numerical Weather Prediction (NWP) models, and to simulate snowcover using a physically based, spatially-distributed energy- and mass-balance snow model. SNODAS also includes procedures to assimilate satellite-derived, airborne, and ground-based observations of snow covered area and Snow Water Equivalent (SWE).
These data are not suitable for snow fall events or totals for specific regions. For snow fall data, please see the state climatology reports for a particular state. These are gridded data sets for the continental United States at 1 km spatial resolution and 24 hour temporal resolution. Data are stored in flat binary 16-bit signed integer big-endian format with header and metadata files. Both a masked version for the contiguous United States and an unmasked version that extends north into Canada are available.
Detailed Data Description
NOHRSC, located in Minneapolis, Minnesota, provides snow information in a variety of products and formats to meet operational forecasting needs. Most of these products are available from the NOHRSC Web site. NSIDC and NOHRSC have agreed that NSIDC will archive and distribute selected parameters from the NOHRSC SNODAS. These output files are valuable for hydrologists, hydrologic modelers, climatologists, ecologists, and land surface modelers. This documentation draws heavily on an assessment of SNODAS products by Barrett (2003) and on material provided by NOHRSC. Consult these sources for additional information.
The SNODAS product is model output and should not be confused with actual observations. For information on snowfall events or snowfall totals, please contact one of the climate centers listed below:
- American Association of State Climatologists Web site
- NOAA Regional Climate Centers Web site
- NOAA National Climatic Data Center Web site
Eight driving, state, and diagnostic parameters are archived by NSIDC. Driving parameters are ingested from the Rapid Update Cycle 2 (RUC2) NWP model and used to force the snow model. State variables are defined here as parameters that the snow model keeps track of and that describe the state of the model snow pack. State variables are modeled snow pack characteristics that are also required to initialize the model. Diagnostic variables are model output but do not describe the internal state of the model. The parameters archived by NSIDC are listed in Table 1 and can be used to compute snow water balance.
SNODAS data files are supplied to NSIDC as flat binary 16-bit signed integer big-endian grids. A header file is also supplied to NSIDC as a text file, which includes metadata. The data files can be read by user-written routines such as Fortran and C programs; off-the-shelf image processing packages such as ENVI, IDL, MATLAB, and ERDAS IMAGINE; and by GIS and other mapping packages such as GMT, GRASS, and ARC/INFO. For instructions, such as importing files into ENVI, refer to Barrett (2003).
The header files contain information to georegister grids contained in the flat binary files. They also contain information about creation and modification of each file, data type of each file, georeferencing data, maximum and minimum values, calibration/scaling information, and a time stamp for each field. Two attributes of the header file that most users will want to pay attention to are the minimum/maximum x and y axis coordinates. These are the grid cell edges that define the extents of the grid. The Benchmark y-axis coordinate in SNODAS header files does change over time.
If you are using ArcMap to display and analyze SNODAS products, the data will not display correctly and values may be modified. This modification occurs because SNODAS data are signed integers and ArcMap reads unsigned integers. You will need to perform the Map Algebra function in ArcMap in order to correct the data. For instructions on how to perform the Map Algebra function in ArcMap, go to the Importing SNODAS Data into ArcGIS document.
Table 2 shows the size of the files depending on level of compression or tarring and whether they are the masked or unmasked version.
|File Type||Size Range|
|Masked tar files (.tar)||1.2 MB - 35 MB|
|Masked uncompressed data files (.dat)||46.5 MB|
|Masked uncompressed header files (.Hdr)||4 KB|
|Unmasked tar files (.tar)||3.4 MB - 102 MB|
|Unmasked uncompressed data files (.dat)||67.1 MB|
|Unmasked uncompressed header files (.Hdr)||4 KB|
The masked and unmasked data files are organized on the FTP site in separate directories labeled
unmasked. Within these two directories are subdirectories labeled by a 4-digit year. Within the year directories, there are subdirectories for the months of the year of the form
MM is the two-digit month number and
mon is the three-character month abbreviation. Each month directory contains the tarred archive file, usually one for each day of the month. See the File Naming Convention section of this document for information on the data file names. Figure 1 shows a sample of the directory structure.
This section describes the file names of the files on the FTP site. There are eight daily data files (one for each data parameter) and eight daily header files (one for each data file) that are compressed using gzip. These 16 gzipped files are packaged together into one daily tar file and placed on the FTP site.
Follow the links below to see the file naming convention for that type of file:
Tarred Daily File Naming Convention (.tar)
The data are available through the FTP site as daily tar files with the following naming convention and as described in Table 3:
||Identifies this as SNODAS data|
||Identifies this as an unmasked version of the SNODAS data|
||2-digit day of month|
||Identifies that this file has been tarred|
Untarred Daily File Naming Convention (.gz)
Once you untar the daily files, you will find 16 gzipped files: Eight data files and eight header files. The gizipped files have the following naming format and are described in Table 4:
The masked data files represent snow cover in the contiguous United States, extending into Canada for certain drainage basins. The spatial coordinates of the area are listed below:
Southernmost Latitude: 24.9504 ° N
Northernmost Latitude: 52.8754 ° N
Westernmost Longitude: 124.7337 ° W
Easternmost Longitude: 66.9421 ° W
Figure 2 is an example of the SNODAS SWE field displayed as an image.
The unmasked data files represent snow cover in the contiguous United States, in addition to extending well into Canada as well as outlines the coast and contains parts of Mexico. The spatial coordinates of the area are listed below:
Southernmost Latitude: 24.0996 ° N
Northernmost Latitude: 58.2329 ° N
Westernmost Longitude: 130.5171 ° W
Easternmost Longitude: 62.2504 ° W
Note: This coverage is not consistent until 2013. SNODAS data coverage over eastern Canada is non-existent in 2010, extends up to 50° N in 2011 and 2012, and then goes up to the full 58.2329° N in 2013.
The grid for the masked data files is 6,935 columns by 3,351 rows; for the unmasked files, it is 8,192 columns by 4,096 rows. Grid values are 16-bit, signed integers (big-endian). The first value at (1,1) is the top-left corner of the array (NW corner in this context). The file is structured so that values are read across the rows. For example, the second value to be read would be the second column of the first row (2,1). Grid cells have a 30-arc second spacing (nominally 1 km on the ground). Model output and precipitation variables are point estimates for the center of each grid cell and not an areal estimate. However, for the purposes of hydrologic and snow cover forecasts, these point estimates are assumed to represent average conditions in each grid cell.
The x- and y- axis coordinates are listed in the header files (.hdr) associated with each data file. The x-axis coordinate of the center of the upper left hand cell is given in theBenchmark x-axis coordinate, and the x-axis coordinate of the left edge of the upper left hand cell is given in the Minimum x-axis coordinate. The y-axis coordinate of the center of the upper left hand cell is given in the Benchmark y-axis coordinate, and the y-axis coordinate of the top of the upper left hand cell is given in Maximum y-axis coordinate. Note: The Benchmark y-axis coordinate in SNODAS header files changes over time.
The X-axis offset and the Y-axis offset in the header files are the distances between the origin and the center of the pixel that lays over the origin. The purpose of those parameters is to provide an easy way of confirming whether or not two grids are aligned, without regard to whether or not they occupy the same region.
SNODAS fields are grids of point estimates of snow cover in latitude/longitude coordinates with the horizontal datum WGS 84. Estimates of SWE and snow depth, as well as other parameters, have no real areal extent. Therefore, projecting SNODAS output to a particular projection may not be necessary. Moreover, different users prefer different projections. For example, federal agencies are likely to use the Albers Equal Area projection, while researchers may prefer an alternative such as one of the projections used for the Equal Area Scalable Earth (EASE-Grid). Refer to All About EASE-Grid for more information. Given that SNODAS outputs are essentially point estimates, the decision to project the data and choice of projection can be left to individual users.
The masked files span 30 September 2003 to the present, and the unmasked files span 09 December 2009 to the present.
NSIDC archives fields representing the model state for 06:00 Universal Time (UTC). The time 06:00 UTC was chosen because this is closest to midnight for the United States. Snow data are for 01:00 local time for the East Coast and 22:00 for the West Coast. SWE, snow depth, and snow pack average temperature represent the state of the snow pack at 06:00 UTC. Snow melt runoff, sublimation and evaporation, and precipitation parameters that describe sources and sinks of snow pack water are integrated for the previous 24 hours, giving daily totals. Note that output for 06:00 UTC is a best estimate of snow pack characteristics. Because SNODAS only updates snow fields once a day, 18 out of 24 time steps in each day's model run do not use observations to update model estimates. Therefore, hourly data from SNODAS is model output only and does not represent the best possible estimate of the snow pack.
NSIDC has scripts that run several times a day. If new SNODAS files are found, these scripts will automatically post them to our FTP server. If you need data sooner than the normal time frame that NSIDC uploads files to our FTP site, you can contact NOHRSC, as they distribute the data for operational users.
Software and Tools
Ingesting SNODAS Data into Image Processing Software
For information on how to ingest SNODAS data into an image processing software such as ENVI, see Appendix B in the National Operational Hydrologic Remote Sensing Center Snow Data Assimilation System (SNODAS) Products at NSIDC Special Report.
Data Acquisition and Processing
NOHRSC supplies NSIDC with files that only have the eight variables contained in this data set. No additional processing is done at NSIDC except for the renaming of the file extension. See the reference information on NOHRSC processing.
References and Related Publications
Contacts and Acknowledgments
Thomas Carroll (Retired)
National Weather Service
National Operational Hydrologic Remote Sensing Center
1735 Lake Drive W.
Chanhassen, MN 55317
This data set and documentation were developed with the assistance of NOHRSC Director Thomas Carroll and NOHRSC staff, and NSIDC's Andrew Barrett. The product team at NSIDC consisted of Lisa Ballagh, Florence Fetterer, Alejandro Machado, and Keri Webster.
Development and distribution of the data set from NSIDC is supported by funding from NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) and the National Geophysical Data Center (NGDC).
This documentation was written by Keri Webster and Florence Fetterer and is based on the publication National Operational Hydrologic Remote Sensing Center Snow Data Assimilation System (SNODAS) Products at NSIDC.
23 February 2012: A. Windnagel updated the documentation to describe the unmasked files that are now available.
27 June 2011: A. Windnagel updated the File and Directory Structure and File Naming Convention sections to describe the FTP site structure. Also removed the Opening FTP .tar.gz Files with WinZip section since the files are not tarred and gzipped the same way anymore.
05 February 2010: A. Windnagel removed all references to the GISMO subsetting interface because it is being decommissioned.
15 January 2010: A. Windnagel added an SSI about the new Beta Advanced Data Search interface.
18 June 2009: A. Windnagel updated the Grid Description section with information on the order of the array.
14 May 2009: A. Windnagel updated the File Naming Convention section that was missing some information, added information on opening the .tar.gz files with WinZip, added information on obtaining near-real-time data, and added a glossary.
07 August 2008: D. Miller updated guide doc with edits from Florence Fetterer and Andy Barrett.
01 April 2008: D. Miller reformatted and reorganized the guide documentation based on comments from User Services (Kara Gergely) to make the guide documentation easier to use. USO was receiving a lot of questions about this data set.
02 February 2007: F. Fetterer made the following changes: Added link to the Bureau of Reclamation and WWA Web sites, added units and product code to table, added information on using GISMO formerly found in the FAQ.
02 February 2006: F. Fetterer added links to a Frequently Asked Questions page authored by L. Ballagh.
22 December 2005: F. Fetterer added text describing the renaming of .grz files at NSIDC. Renaming was instituted in December 2005 for the following reasons: 1) .grz is not a standard data type or file extension, 2) The compression and storage of the files is accomplished by tarring each set and then compressing them using the gzip compression program. This has several recognized file name extensions, but the most prevalent is .tar.gz. Changing the extension to this more recognized format will help alleviate user confusion while at the same time not altering the actual distributed data files contained within the tarred file.
19 December 2005: F. Fetterer added text advising users needing data on an operational basis to contact NOHRSC.
09 May 2005: F. Fetterer added information on subsetting options.
This is most likely due to a problem with Windows Winzip which corrupts the file upon dowloading (you will see that the file size will have changed from the original located on ftp)
You can correct this by changing some settings in WinZip:
- Extract the “...
The NSIDC Python Reformatting and Subsetting (PyRS) tool is a command line tool which prompts the user to specify data reformatting and subsetting preferences. Output formats available are native, GeoTIFF, and NetCDF. If the dataset is polar stereographic, subsetting can be performed in the...read more