Table of Contents

1. Contacts and Acknowledgments
2. Detailed Data Description
3. Data Access and Tools
4. Data Acquisition and Processing
5. References and Related Publications
6. Document Information

Citing These Data

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.

Data Citation

Kim, Y., J. S. Kimball, J. Glassy, and K. C. McDonald. 2010, Updated 2012. MEaSUREs Global Record of Daily Landscape Freeze/Thaw Status, Version 2, [indicate subset used]. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice Data Center.

Literature Citation

Kim, Y., J. S. Kimball, K. Zhang, and K. C. McDonald. 2012. Satellite detection of increasing Northern Hemisphere non-frozen seasons from 1979 to 2008: Implications for regional vegetation growth. Remote Sensing of Environment 121: 472-487.

Overview

Platform	Nimbus 7 DMSP (Defense Meteorological Satellite Program) Aqua (EOS PM-1)
Sensor	SMMR SSM/I AMSR-E
Spatial Coverage	Global
Spatial Resolution	25 km
Temporal Coverage	01 January 1979 to 31 December 2010 (SMMR - SSM/I) 19 June 2002 to 27 September 2011 (AMSR-E)
Temporal Resolution	Daily
Parameters	Daily AM Freeze/Thaw (FT) status Daily PM Freeze/Thaw status Daily Combined (CO) Freeze/Thaw status Daily Transitional Freeze/Thaw status Daily Inverse Transitional Freeze/Thaw status Daily FT Status Accuracy Metric Annual FT Status Quality Assurance (QA) Maps and Accuracy Metrics
Data Format	HDF5 (.h5) GeoTIFF (.tif) GIF (.gif) Binary (.bin)
Metadata Access	View Metadata Record
Data Access	FTP
Version History	V01

1. Contacts and Acknowledgments

Investigators

Dr. John Kimball, PI
Numerical Terradynamic Simulation Group (NTSG)
The University of Montana
Missoula, MT 59812

Dr. Youngwook Kim, Science Lead
Numerical Terradynamic Simulation Group (NTSG)
The University of Montana
Missoula, MT 59812

Joe Glassy, Software and Data Management Lead
Numerical Terradynamic Simulation Group (NTSG)
The University of Montana
Missoula, MT 59812

Dr. Kyle McDonald, Co-PI
Jet Propulsion Laboratory (JPL)
California Institute of Technology
Pasadena, CA 91109

Technical Contact

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
e-mail: nsidc@nsidc.org

Acknowledgements

These data were generated through a grant from the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program. Portions of this work were conducted at the University of Montana and Jet Propulsion Laboratory, California Institute of Technology, under contract to NASA.

2. Detailed Data Description

Formats

HDF5

The following data are available in HDF5 v1.8 format:

• Daily freeze/thaw (FT) status for AM (morning), PM (afternoon), and CO (composite daily)
• Annual quality assurance (QA) data characterizing the FT data
• Accuracy metrics based on in situ surface maximum/minimum air temperature observations from World Meteorological Organization (WMO) weather stations.

The cell_lat and cell_lon fields appearing in the HDF5 files are included for CF v1.4 compliance allowing users of common free software packages, such as HDFView and Panoply, to immediately view the data sets projected in a global geographic grid.

FT Status

HDF5 freeze/thaw status files contain the following data fields:

Field	Description	Dimension	Data Type
FT_status	Daily global freeze/thaw status	1383 columns; 586 rows	8-bit unsigned integer
cell_lat	Latitude	1383 columns; 586 rows	32-bit floating point
cell_lon	Longitude	1383 columns; 586 rows	32-bit floating point

The metadata for the AM and PM HDF5 files includes an aggregate daily accuracy metric (Accuracy_Daily_Metric).

FT Quality Assurance

SMMR-SSM/I annual QA maps are provided as a single HDF5 file that contains one data field per year for each year in the record. QA values are reported in a range from 0.0 (low, accuracy <70%) to 1.0 (best, accuracy >90%) and represent a relative index of data quality for each grid cell based on ancillary terrain and land cover heterogeneity, satellite data gaps, and daily FT accuracy assessments (see Kim et al. 2011 for details).

HDF5 QA files contain the following data fields:

Field	Description	Dimension	Data Type
FT_Annual_QA_[Year]	QA	1383 columns; 586 rows	32-bit floating point
cell_lat	Latitude	1383 columns; 586 rows	32-bit floating point
cell_lon	Longitude	1383 columns; 586 rows	32-bit floating point

Annual QA maps for the AMSR-E FT record are provided as binary files (see the Binary format section below).

FT Accuracy

Annual FT accuracy data are provided in HDF5 files that contain two data fields (AM and PM) per year for each year in the corresponding instrument record. Accuracy was assessed in relation to daily maximum and minimum air temperature measurements from the global WMO weather station network (see Kim et al. 2011 for details) and calculated as the percent of daily FT retrievals per year that are consistent with in situ air temperature measurements. Values are reported in the range of 0.0 to 100.0.

HDF5 accuracy files contain the following data fields:

Field	Description	Dimension	Data Type
FT_Accuracy_[AM/PM]_[Year]	FT accuracy value	1383 columns; 586 rows	32-bit floating point
cell_lat	Latitude	1383 columns; 586 rows	32-bit floating point
cell_lon	Longitude	1383 columns; 586 rows	32-bit floating point

Binary

AMSR-E annual QA maps are provided as binary files (little-endian least significant byte first, single precision IEEE floating point 32 bit pixels) with one file per year for each year in the record. Because the annual QA algorithm requires a full 365-day contiguous sequence of FT classifications, QA maps for the two partial years that AMSR-E was in operation—2002 when the instrument was deployed and 2011 when the instrument failed—were derived from empirical QA relationships established from the complete annual records for 2003 and 2010, with temporally dynamic information from 2002 and 2011, respectively.

GeoTIFF

Beginning with this Version 2 release, daily FT status is available in GeoTIFF format with an ESRI projection file that facillitates viewing the data in ArcMap.

GIF

Annual FT accuracy data, derived from the PM overpass, are available as GIF image files. New for Version 2, GIF browse images of the daily CO FT status are available to quickly evaluate the data visually.

File and Directory Structure

Data are available on the FTP site in the ftp://sidads.colorado.edu/pub/DATASETS/nsidc0477_MEASURES_freeze_thaw_v02/ directory. The four folders within this directory each have /AMSRE/ and /SMMR_SSMI/ instrument subdirectories that contain individual folders for each year in the corresponding data record. Table 2 below describes the contents of the four folders at the top of the FTP directory:

Table 2. Directory Description

Directory	Description
DAILY_FT_GEOTIFF	Global daily FT status in GeoTIFF (.tif) file format. The ESRI projection (.prj) file resides at the top of this directory.
DAILY_FT_BROWSE	Global daily browse images of FT status in GIF (.gif) file format
DAILY_FT_HDF5	Global daily FT status in HDF5 (.h5) file format
QA_ACCURACY	Annual QA maps and accuracy metrics in GIF, HDF5, and binary formats (AMSR-E only). Also contains an MD5 file (.md5) with checksum hash signatures for each data file in the collection.

File Naming Convention

Daily FT Status Data Files

Each daily FT status product consists of three separate files: morning overpass (AM), afternoon overpass (PM), and a combined daily AM and PM (CO) classification. Daily FT data files utilize the following naming convention:

• [InstrumentLabel]_[Channel][Polarization]_[OverpassCode]_FT_[Year]_day[DOY]

Refer to the file extension (.h5, .tif) to determine the file format. For example, SSMI_37V_CO_FT_1993_day001 represents the SSM/I sensor, 37 GHz, vertically polarized brightness temperature based FT classification for the composite daily conditions on day (calendar year) 001. These data are available in the following formats:

• SSMI_37V_CO_FT_1993_day001.h5
• SSMI_37V_CO_FT_1993_day001.tif

Daily FT Status Browse Images

Daily FT browse images utilize the following naming convention:

• [InstrumentLabel]_[Channel][Polarization]_CO_FT_[Year]_day[DOY].gif

QA and Accuracy Files

The annual QA and accuracy files (.h5) and global mean QA files (.bin) listed below are stored in the QA_ACCURACY/[Instrument]/ subfolders:

• SMMR-SMM/I
• FT_v2_global_1979_2010_QA.h5
• FT_v2_global_1979_2010_accuracy.h5
• SSMI_global_QA_PM_mean.bin
• AMSR-E
• FT_AMSRE_global_2002_2010_accuracy.h5
• FT_AMSRE_global_2011_accuracy.h5
• AMSRE_global_QA_PM_mean.bin

Please note that the AMSR-E accuracy metrics for 2011 are currently provided as a separate file because these data were added after the main body of AMSR-E data (2002-2010) had been post-processed, and at that time the post-processing code was set up to only handle data through 2010. The PIs anticipate revising this code at a future date, at which time the AMSR-E accuracy data will be reprocessed into a single file spanning the years 2002 to 2011.

The binary AMSR-E annual QA files for the years 2003 to 2010 utilize the following naming convention:

• AMSRE_global_QA_[YEAR]_PM.bin

QA Maps

Annual FT QA maps are stored in the QA_ACCURACY/[Instrument]/GIF/ subfolder and utilize the following naming convention:

• [InstrumentLabel]_global_QA_[Year]_PM.gif

For example:

• SMMR_global_QA_1979_PM.gif

File Size

Individual daily FT status data files range from approximately 50 kb (.tif) to 200 kb (.h5). Annual QA maps and GIF browse images are approximately 25 kb. QA and accuracy data files range from 0.23 MB to 11.4 MB. Binary QA files are approximately 3.2 MB.

Volume

The complete FT dataset (11,688 daily granules) is approximately 12.49 GB. Each overpass code (AM, PM, or CO) represents approximately 4.16 GB of data. One year is approximately 125 MB per overpass code.

Spatial Coverage

Coverage is global:

• Southernmost Latitude: -86.7167° S
• Northernmost Latitude: 86.7167° N
• Westernmost Longitude: -179.9999° W
• Easternmost Longitude: 179.9999° E

Spatial Resolution

25 km

Projection and Grid Description

Each grid cell is projected in a global EASE-Grid format (Armstrong and Brodzik, 1995; Brodzik and Armstrong 2002) at 25km spatial resolution, with 1383 columns and 586 rows consisting of 8-bit/byte data for a total of 810438 pixels per daily data product.

Temporal Coverage

• SMMR - SSM/I
• 01 January 1979 to 31 December 2010
• AMSR-E
• 19 June 2002 to 27 September 2011

Temporal Resolution

Daily

Parameter Description

AM Freeze/Thaw status

Freeze/thaw status for the morning satellite overpass

PM Freeze/Thaw Status

Freeze/thaw status for the afternoon satellite overpass

Combined Freeze/Thaw Status

Combined freeze/thaw status for the morning and afternoon satellite overpasses

Transitional Freeze/Thaw

AM frozen, PM thawed

Inverse Transitional Freeze/Thaw

AM thawed, PM frozen

Daily FT Status Accuracy Metric

Accuracy_Daily_Metric, stored as a metadata object in HDF5-formatted AM and PM files, provides an aggregate daily accuracy metric.

Annual QA Metric of FT Classification Accuracy

Annual QA maps that provide a relative index of data quality derived from ancillary terrain and land cover heterogeneity information, satellite data gaps, and daily FT accuracy assessments.

Parameter Range

FT Status

Table 3 below describes the values used to classify FT status in data files and images:

Table 3. FT Classification Values

Classification		Browse Image Color Table
	Value	R	G	B
Frozen (AM/PM frozen)	0	000	000	255
Thawed (AM/PM thawed)	1	255	000	000
Transitional (AM frozen and PM thawed)	2	168	168	000
Inverse Transitional (PM frozen and AM thawed)	3	076	230	000
No FT status available	251	255	255	255
Non-cold constraint area, but unmasked	252	255	255	255
Masked (permanent ice, non-vegetated, and urban area)	254	255	255	255
100 percent open water	255	255	255	255
Fill value	255	255	255	255

FT Accuracy

Accuracy values are reported as a percent in the range 0.0 to 100.0. Missing values are indicated by -9999.

Sample Data Record

Figure 1 shows the SMMR-SSM/I daily combined AM/PM (CO) FT status for 9 April 2004. Areas colored in gray lie outside of the FT data set domain.

3. Data Access and Tools

Data Access

Data are available via FTP.

Software and Tools

HDF5 data files may be accessed with HDFView, Panoply, or similar HDF5-compatible applications. GeoTIFF files may be viewed with ESRI ArcMap or similar Geographical Information System (GIS) software.

4. Data Acquisition and Processing

Theory of Measurements

The MEaSUREs Global Record of Daily Landscape Freeze/Thaw Status product, Version 2 allows FT state dynamics to be quantified over vegetated land within a global domain where seasonally frozen temperatures are a major constraint to ecological processes. Satellite microwave remote sensing is well suited for monitoring global FT status due to its relative insensitivity to atmospheric contamination, independence from solar illumination, and strong sensitivity to changes in landscape dielectric properties between frozen and thawed states. This earth system data record (FT-ESDR) is derived using daily radiometric brightness temperature measurement time series from two sources: overlapping SMMR - SSM/I time series and the AMSR-E operational record. The SMMR - SSM/I derived data represent a consistent, daily FT global record that extends from 1979 to 2010, ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR brightness temperature time series based on empirical analyses of overlapping SMMR and SSM/I measurements (Kim et al. 2012).

Data Acquisition Methods

The extended SMMR - SSM/I record in this Version 2 release was developed by merging the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) 37 GHz frequency (vertical polarization) brightness temperature records and applying the same algorithms and protocols used to construct the Version 1 product. Version 2 also includes an additional Freeze/Thaw data record derived from 36V GHz daily (1:30 AM/PM equatorial crossing) brightness temperature records from the AMSR-E sensor on board NASA's Aqua space vehicle, for the years 2002 to 2011 inclusive. The FT parameter derivation for AMSR-E is consistent with the SMMR - SSM/I methodology.

Derivation Techniques and Algorithms

The FT-ESDR is intended to have sufficient accuracy, resolution, and coverage to resolve physical processes linking Earth's water, energy and carbon cycles. The product was designed to resolve the FT status of the composite landscape vegetation-snow-soil medium to a sufficient level to characterize the frozen temperature constraints to surface water mobility, vegetation productivity, ecosystem respiration and land-atmosphere CO₂ fluxes. The FT-ESDR classifies daily binary FT states on a grid cell-by-cell basis and posts them to a regular Earth grid. The FT classification algorithm detects temporal changes in radiometric brightness temperature time-series that correspond to FT transition sequences, by exploiting the dynamic temporal brightness temperature response to differences in the aggregate landscape dielectric constant that occur as the landscape transitions between predominantly frozen and nonfrozen conditions (McDonald and Kimball 2005). These techniques are well-suited to resolving daily FT state dynamics rather than single events or seasonally dominant transitions (Kim et al. 2011).

Satellite ascending and descending orbital data time series were processed separately to produce AM, PM and composite daily (CO) FT conditions. The FT-ESDR also identifies transitional (AM frozen and PM thawed) and inverse transitional (AM thawed and PM frozen) conditions. The global FT-ESDR domain encompasses unmasked vegetated land areas where low temperatures significantly constrain annual vegetation productivity as defined from climatological reanalysis data. Masked areas include permanent ice and snow, barren land, open water, and regions unconstrained by freezing temperatures. The FT-ESDR is projected in a global cylindrical Equal-Area Scalable Earth (EASE) grid (Brodzik and Armstrong 2002).

Version 2 encompasses large climate variations and longer-term trends in terrestrial FT cycles, which have been verified against global weather station records and other biophysical data including satellite vegetation greenness and tower CO₂ flux measurement networks (Kim et al. 2012).

In addition, the Version 2 product applies a modified single brightness temperature reference state seasonal threshold algorithm (STA) to anomalous areas where the annual brightness temperature frozen reference state exceeds the brightness temperature non-frozen reference state. These areas, which are assigned a low QA value, represent less than 1 percent of the FT-ESDR domain; they include portions of northern Africa, Ethiopia, and central Mexico, and in general dry climate areas where other environmental factors including seasonal wetting events result in large brightness temperature changes similar to FT transitions. Although the alternative single STA reference state FT classification was found to markedly improve FT-ESDR classification accuracy in these areas, they have still been assigned a low QA value.

Quality Assessment

Product accuracy was assessed in relation to daily maximum (T_mx) and minimum (T_mn) air temperature measurements from the global WMO weather station network (approximately 3207 stations); mean annual FT status spatial classification accuracies were 91.4 ± 1.05 [interannual standard deviation] and 84.2 ± 0.92 [interannual standard deviation] percent for respective FT-ESDR PM and AM retrievals over the global domain and long-term record. The FT classification accuracy shows strong seasonal and annual variability and is reduced during active FT transition periods when spatial heterogeneity in landscape FT processes is maximized in relation to the relatively coarse (~25 km) satellite footprint.

Surface air temperature records from global model reanalysis and in situ weather station networks were used for FT algorithm calibration and verification of FT-ESDR accuracy. Global meteorological reanalysis data were used to define the threshold levels and the global FT-ESDR domain (see Figure 2 below) as all vegetated land areas where seasonally frozen air temperatures are a major constraint to ecological processes (Kim et al. 2011).

Quality control (QC) metrics provide an indicator of FT product quality for each grid cell within the FT-ESDR domain (see Figure 3 below). The dynamic QC information includes the number of days per year with SSM/I radiometric brightness temperature data gaps and flagged precipitation events (Ferraro et al. 1996). The static QC information includes the potential effects of fractional open water cover (MODIS 17-class IGBP Global Land Cover Product, Friedl et al. 2002), complex topography (GLOBE, 1999) and heterogeneous land cover conditions defined from the 1 km resolution global land cover classification and Digital Elevation Model (DEM), and the average number of days (first year) with global model reanalysis air temperatures within ± 3 Celcius degrees of 0.0 Celcius degrees (Kim et al. 2011).

The additional data quality metrics developed for this Version 2 release provide more spatially explicit accuracy information, including potential negative impacts of temporal gaps in sensor data time series, precipitation, open water, terrain and land cover heterogeneity effects, and uncertainty associated with use of global reanalysis temperature data to define per grid-cell frozen and non-frozen reference state thresholds for the STA based FT classifications. The resulting database provides a consistent and continuous, multi-year (1979 onward) record of daily (AM and PM) FT dynamics for the global biosphere.

Sensor or Instrument Description

The Special Sensor Microwave/Imager (SSM/I) instruments used for this product were deployed on the DMSP F-8, F-11, and F-13 satellites. The SSM/I instrument is a seven-channel, four-frequency, orthogonally polarized passive microwave radiometric system. The system measures combined atmosphere and surface radiances at 19.3 GHz, 22.2 GHz, 37.0 GHz, and 85.5 GHz. Please see NSIDC's Special Sensor Microwave/Imager Instrument Description Web page for more details.

The Scanning Multichannel Microwave Radiometer (SMMR) operated on NASA's Nimbus-7 satellite from 26 October 1978 to 20 August 1987. SMMR was a ten-channel instrument capable of receiving both horizontally and vertically polarized radiation. A parabolic antenna 79 cm in diameter reflected microwave emissions into a five-frequency feed horn. The antenna beam maintained a constant nadir angle of 42 degrees, resulting in an incidence angle of 50.3 degrees at Earth's surface. The antenna was forward viewing and rotated equally ± 25 degrees about the satellite subtrack. The 50 degree scan provided a 780 km swath of the Earth's surface. Scan period was 4.096 seconds. See NSIDC's Scanning Multi-channel Microwave Radiometer (SMMR) Instrument Description Web page for more information.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a twelve-channel, six-frequency, passive-microwave radiometer system on board the NASA Earth Oberserving System Aqua Satellite. The instrument measures horizontally and vertically polarized brightness temperatures at 6.9 GHz, 10.7 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz, and 89.0 GHz. Spatial resolution of the individual measurements varies from 5.4 km at 89 GHz to 56 km at 6.9 GHz.

AMSR-E was developed and provided by the Japan Aerospace Exploration Agency (JAXA, Contractor: Mitsubishi Electric Corporation) with close cooperation of U.S. and Japanese scientists. The AMSR-E instrument onboard Aqua was modifed from the design used for AMSR, which flew on the Japanese ADEOS-2 satellite. See NSIDC's AMSR-E Instrument Description page for more information.

5. References and Related Publications

Armstrong, R. L., and M. J. Brodzik. 1995. An Earth-Gridded SSM/I Data Set for Cryospheric Studies and Global Change Monitoring. Advances in Space Research 16: 155-63.

Brodzik, M. J. and R. L. Armstrong. 2002. EASE-Grid: A versatile set of equal-area projections and grids. In M. Goodchild (Ed.), Discrete Global Grids. Santa Barbara, California USA: National Center for Geographic Information and Anlaysis.

Ferraro, R. R., F. Weng, N. C. Grody, and A. Basist. 1996. An eight-year (1987-1994) time series of rainfall, clouds, water vapor, snow cover, and sea ice derived from SSM/I measurements. Bulletin of the American Meteorological Society, 77(5), 891-905.

Friedl, M. A., D. K. McIver, J. C. F. Hodges, X. Y. Zhang, D. Muchoney, A. H. Strahler, C. E. Woodcock, S. Gopal, A. Schneider, A. Cooper, A. Baccini, F. Gao, and C. Schaaf. 2002. Global land cover mapping from MODIS: algorithms and early results. Remote Sensing of Environment, 83, 287-302

GLOBE Task Team and others (Hasting, D. A., P. K. Dunbar, G. M. Elphingstone et al.). 1999. The global land one-kilometer base elevation (GLOBE) digital elevation model, version 1.0. National Oceanic and Atmospheric Administration, National Geophysical Data Center, 325 Broadway, Boulder, Colorado 80305-3328, U.S.A. Digital data base at http://www.ngdc.noaa.gov/mgg/topo/globe.html and CD-ROMs.

Jones, L.A., and J.S. Kimball, 2010. Daily Global Land Surface Parameters Derived from AMSR-E, Version 1.1. Boulder Colorado USA: NASA DAAC at the National Snow and Ice Data Center. http://nsidc.org/data/nsidc-0451.html.

Kim, Y., J.S. Kimball, K.C. McDonald and J. Glassy, 2010. MEaSUREs Global Record of Daily Landscape Freeze/Thaw Status, Version 1 [1988 to 2007]. Boulder Colorado USA: NASA DAAC at the National Snow and Ice Data Center. http://nsidc.org/data/nsidc-0477.html.

Kim, Y., J. S. Kimball, K. C. McDonald, and J. Glassy. 2011. Developing a Global Data Record of Daily Landscape Freeze/Thaw Status using Satellite Microwave Remote Sensing. IEEE Transactions on Geoscience and Remote Sensing.

Kim, Y., J.S. Kimball, K. Zhang, and K.C. McDonald, 2012. Satellite Detection of Increasing Northern Hemisphere Non-Frozen Seasons from 1979 to 2008: Implications for Regional Vegetation Growth. Remote Sensing of Environment 121, 472-487.

McDonald, K.C, and J.S. Kimball, 2005. Hydrological Application of Remote Sensing: Freeze-thaw States using both Active and Passive Microwave Sensors. Encyclopedia of Hydrological Sciences. Part 5. Remote Sensing. M.G. Anderson and J.J. McDonnell (Eds.), John Wiley & Sons Ltd. doi: 10.1002/0470848944.hsa059a.

Related Data Collections

• Seasonal frost depths, midwestern USA
• Global Annual Freezing and Thawing Indices
• Arctic EASE-Grid Freeze and Thaw Depths, 1901 - 2002
• Modeled Daily Thaw Depth and Frozen Ground Depth
• Arctic Soil Freeze/Thaw Status from SMMR and SSM/I, Version 2
• Circumpolar Active-Layer Permafrost System (CAPS)
• Near-Real-Time DMSP SSM/I-SSMIS Pathfinder Daily EASE-Grid Brightness Temperatures
• Daily Global Land Surface Parameters Derived from AMSR-E, Version 1.1

Related Web Sites

• Freeze/Thaw Earth System Data Record

6.Document Information

Acronyms and Abbreviations

Acronyms and abbreviations used in this document are listed in Table 3.

Table 3. Acronyms and Abbreviations

Acronym	Description
AMSR-E	Advanced Microwave Scanning Radiometer - Earth Observing System
DEM	Digital Elevation Model
DMSP	Defense Meteorological Satellite Program
ESRI	Environmental Systems Research Institute
EASE-Grid	Equal-Area Scalable Earth Grid
FT-ESDR	Freeze/Thaw - Earth System Data Record
HDF5	Hierarchical Data Format - Version 5
JPL	Jet Propulsion Laboratory
MEaSUREs	Making Earth System Data Records for Use in Research Environments
NASA	National Aeronautics and Space Administration
QA	Quality Assurance
QC	Quality Control
SMMR	Scanning Multichannel Microwave Radiometer
SSM/I	Special Sensor Microwave/Imager

Document Creation Date

7 January 2012

Document Revision Date

7 January 2012

Document URL

http://nsidc.org/data/docs/measures/nsidc0477-freeze-thaw-v02/index.html