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Data Set ID:
GGD641

Arctic Soil Freeze/Thaw Status from SMMR and SSM/I, Version 2

This data set contains near-surface (< 5 cm) soil freeze/thaw status on snow-free and snow-covered land surfaces over the Arctic terrestrial drainage basin. The near-surface soil freeze/thaw status is determined by using passive-microwave remote sensing data over snow-free land and a numerical model over snow-covered land. Data are projected to a 25 km x 25 km Northern Hemisphere EASE-Grid. Version 2 of this data set greatly extends the temporal coverage and makes use of data from SMMR as well as SSM/I. Data are from October 1978 to June 2004. Data are in ASCII text format and are available via FTP.

Geographic Coverage

Parameter(s):
  • Snow/Ice > Freeze/Thaw
  • Frozen Ground > Seasonally Frozen Ground
Spatial Coverage:
  • N: 90, S: 45, E: 180, W: -180

Spatial Resolution:
  • 25 km x 25 km
Temporal Coverage:
  • 1 October 1978 to 30 June 2004
Temporal Resolution: 1 day
Data Format(s):
  • ASCII Text
Platform(s) DMSP, NIMBUS-7
Sensor(s): SMMR, SSM/I
Version: V2
Data Contributor(s): Tingjun Zhang, Richard Armstrong
Data Citation

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.

Zhang, T. and R. Armstrong 2003. Arctic Soil Freeze/Thaw Status from SMMR and SSM/I, Version 2. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. [Date Accessed].

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Detailed Data Description

This data set contains near-surface (< 5 cm) soil freeze/thaw status on snow-free and snow-covered land surfaces over the Arctic terrestrial drainage basin. The near-surface soil freeze/thaw status is determined by using passive-microwave remote sensing data over snow-free land and a numerical model over snow-covered land. Data are projected to a 25 km x 25 km Northern Hemisphere EASE-Grid. Version 2 of this data set greatly extends the temporal coverage and makes use of data from SMMR as well as SSM/I. Data are from October 1978 to June 2004. Data are in ASCII text format and are available via FTP.

Format

Data are in ASCII text format, compressed with gzip. Three hundred nine files contain data from October 1998 through June 2004. Each file contains columns for latitude, longitude, and surface type for each day of the month. A two line header indicates the column headers, the year and month, and a key to the values for the surface types. Surface type values are as follows:

1: Snow-free, unfrozen ground
2: Snow-free, frozen ground
3: Snow-covered, unfrozen ground
4: Snow-covered, frozen ground
5: Desert (south of 50°N)
6: Mixed land and ocean
7: Lake or ocean

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File Naming Convention

The file-naming convention is "ggd641_freezethaw_arctic.yyyy.mm.txt."

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File Size

One 148.3 MB tarred and compressed file contains 309 individual 10.3 MB files.

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Spatial Coverage

This data set covers the entire Arctic terrestrial drainage basin. This area includes land with ice or water that empty into the Arctic Ocean, Hudson Bay, James Bay, Hudson Strait, and the Bering Sea. The Arctic drainage basin spans overs regions of seasonally-frozen ground in the south, to permafrost regions in the north. Continuous permafrost underlies nearly half of the Arctic drainage basin (Brown et al. 1998Zhang et al. 2000).

Spatial Coverage Map:

The following image from 02 January 1999 was created from "Arctic Soil Freeze/Thaw Status from SMMR and SSM/I, Version 2" data. It shows the spatial extent of the Arctic terrestrial drainage basin. Click on the thumbnail to see a larger image.

Sample image

Spatial Resolution:

Spatial resolution is 25 km.

Grid Description:

Input data are interpolated to a spatial subset of the Northern Hemisphere EASE-Grid projection that represents the Arctic drainage basin. (See All About EASE-Grid for further details.) Data are output to ASCII text format.

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Temporal Coverage

Data are grouped by month from October 1978 through June 2004. Each file contains daily data values.

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Quality Assessment
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Data Acquisition and Processing

Data Source

Zhang and Armstrong obtained input data from the following sources:

Passive-microwave TBs
This study uses 18-Ghz and 37-Ghz TBs from the Nimbus-7 SMMR Pathfinder Daily EASE-Grid Brightness Temperatures and the 19-GHz and 37-GHz TBs from the DMSP SSM/I-SSMIS Pathfinder Daily EASE-Grid Brightness Temperatures data set, available from NSIDC.

Air Temperature
The National Water and Climate Center (NWCC), Natural Resources Conservation Center (NRCC) of the U.S. Department of Agrictulture provided mean daily and monthly air temperature data. The University of Delaware's Center for Climate Research provided gridded mean monthly air temperatures over the study area. The 0.5° x 0.5° gridded latitude/longitude data were gridded into the 25-km EASE-Grid. Mean daily air temperature was derived from the mean annual air temperature and annual amplitude, which were derived from mean monthly air temperature.

Snow Cover
Zhang and Armstrong calculated snow water equivalent from the Nimbus-7 SMMR Pathfinder Daily EASE-Grid Brightness Temperatures and DMSP SSM/I-SSMIS Pathfinder Daily EASE-Grid Brightness Temperatures data sets, available from NSIDC. The Chang (1987) algorithm, originally used for calculating snow water equivalent from Scanning Multichannel Microwave Radiometer (SMMR) passive-microwave data from 1978 to 1987, was modified for the SSM/I data.

Soil Temperature
The National Water and Climate Center (NWCC), Natural Resources Conservation Center (NRCC) of the U.S. Department of Agrictulture provided hourly soil temperature data at depths of 0 cm, 5 cm, 10 cm, 20 cm, 40 cm, 80 cm, 100 cm, and 150 cm. Ground surface temperature is measured only at a few selected sites. This study uses soil temperature data at 5-cm depth from all sites.

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Derivation Techniques and Algorithms

This data set is derived from a frozen-soil algorithm that combines passive-microwave remote sensing and numerical modeling methods. The first step is to compile the input data described in the Data Source section of this document. Using available ground-based and satellite data, Zhang and Armstrong determine where snow exists over the study area. Over snow-free land, they use a frozen-soil algorithm using SMMR and SSM/I data to detect near-surface freeze/thaw status. Over snow-covered land areas, they use a one-dimensional heat transfer numerical model with phase change to detect soil freeze/thaw status.

Passive-microwave algorithm
SSM/I 19-GHz and 37-GHz vertically-polarized TBs discriminate frozen ground from unfrozen ground over prairie soils, using the following equation:

(TB(37V) - TB(19V))/18 < 0

and

TB(37V) < 258.2 K

A similar approach is used with the SMMR data using the 18-Ghz and 37-Ghz channels.

Mixed land and water pixels provide misleading information on the land surface freeze and thaw status; therefore, areas up to approximately 50 km from the coasts of large water bodies are masked out.

Numerical model
This study uses a numerical model for one-dimensional heat transfer with phase change to simulate the soil freezing and thawing processes with or without snow cover. This model has shown excellent previous results for active-layer depth and soil temperatures when driven by well-known boundary conditions and forcing parameters at specific locations (Zhang, Osterkamp, and Stamnes 1996).

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References and Related Publications

Document Information

DOCUMENT CREATION DATE

May 2003

DOCUMENT REVISION DATE

December 2005 

No technical references available for this data set.
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