Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 2

This data set provides daily sea ice motion vectors derived from a wide variety of sensors in both gridded and non-gridded, or raw, files. For the gridded data, mean fields are also provided; they include yearly, monthly, and weekly means, as well as a mean for the entire time series—from November 1978 through December 2012. Browse images of all mean fields are also available.

Table of Contents

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

Citing These Data

We kindly request that you cite the use of this data set in a publication using the following citation. For more information, see our Use and Copyright Web page.

Fowler, C., W. Emery, and M. Tschudi. 2013. Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors. Version 2. [indicate subset used]. Boulder, Colorado USA: National Snow and Ice Data Center.



Aqua, POES, IABP Buoys, NIMBUS-7, DMSP F8 – F17, NCEP/NCAR (Global weather model data from various platforms; see Table 11 for details)



1Available for Northern Hemisphere only.
2 Includes multiple sensors; see Table 11 for details.

Spatial Coverage

Spatial coverage extends from 48.4° N to 90° N, and from 53.2° S to 90° S. Coverage extends beyond these limits in the grid corners.

Spatial Resolution

25 km

Temporal Coverage

Varies by sensor. Gridded data are available November 1978 – December 2012.

Temporal Resolution



Sea ice motion

Data Format

Raw ice motion vectors: space-delimited ASCII text
Daily and mean grids: 2-byte integer binary, little endian
Browse images of mean fields: PNG, PS

Metadata Access

View Metadata Record


V2. See the Version History section of this document for version information.

Data Access


1. Detailed Data Description


Raw Ice Motion Vectors

Raw ice motion vectors are in space-delimited ASCII text format and each daily file contains a variable number of vectors. At the top of every file is a one-line header containing three numbers as described in Table 1.

Table 1. Header Row Description for Raw Ice Motion Vector Files
Number Description
First Specifies the number of vectors (lines) in the file
Second Original grid dimensions (x)
Third Original grid dimensions (y)

After the header line, the data are listed in five1 columns, as described in Table 2.

Table 2. Column Descriptions for Raw Ice Motion Vector Files
Column Name Description
1 x EASE-Grid row number for the start of the vector (vector starts in the center of the grid cell). The upper left corner is represented by x = -0.5.
2 y EASE-Grid column number for the start of the vector (vector starts in the center of the grid cell). The upper left corner is represented by y = -0.5.
3 u Vector component in cm/sec.
4 v Vector component in cm/sec.
51 t Time of day in Universal Coordinated Time (UTC)
6 z Source of the data; z value varies depending on instrument:
AMSR-E: z = 0.0 – 1.0 (correlation coefficient); only 89V GHz channel used.
AVHRR: z = Number of vectors averaged together at a given location from up to four passes and two channels (thermal and visible).
Buoys: z = IABP buoy number
SMMR: z = 1: The vector was from 37V GHz channel
z = 2: The vector was from both 37 GHz channels
SSM/I-SSMIS: z = 1: The vector was from 37V GHz channel
z = 2: The vector was from both 37 GHz channels
z = 3: The vector was derived from the 85V GHz channel
Winds: z = 1: From NCEP/NCAR wind data
1 Files containing buoy data are listed in six columns, with the fifth column containing time of day in Universal Coordinated Time (UTC).

See the Sample Data Record for an example of a raw vector file derived from SSM/I.

Daily and Mean Grids

Both daily and mean gridded fields are projected to Northern and Southern Hemisphere EASE-Grids. Data are stored in 2-byte integer binary format (little endian) and are pixel-interleaved three-item vectors (3 by x by y). Each vector represents three variables:

  • U Component (cm/sec)—Scaled by a factor of 10; divide by 10 to revert to original units.
  • V Component (cm/sec)—Scaled by a factor of 10; divide by 10 to revert to original units.
  • Third Variable—Varies for daily and mean grids (see below). For both daily and mean grids, a pixel value of 0 in the third variable indicates no vectors at that location.
Third Variable for Daily Grids

For the daily grids, the third variable contains the square root of the estimated error variance, scaled by a factor of 10, at a given location. The error variance is the estimated error of that vector obtained from the optimal interpolation process. The input vectors from the individual sources (NCEP/NCAR Winds, SSM/I-SSMIS, SMMR, AMSR-E, and AVHRR) are weighted separately based upon cross-correlations with buoy vectors. The optimal interpolation uses these weights, along with their distances from the location being estimated, to obtain the final error variance.

If the closest input vector was greater than 1250 km, then a value of 1000 is added to this variable. Because interpolation was applied to a surface map from passive microwave data, coastlines may contain false ice. In this case, the third variable was assigned a negative value to allow users to remove these vectors near coastlines (within 25 km). For example, a value of -1035 indicates all of the following conditions:

  • The vector was near a coastline
  • The nearest sampled vector was further than 1250 km
  • The vector had a σ value of 3.5, or the estimated error variance (σ2) is 12.25
Third Variable for Mean Grids

For the mean grids, the third variable is the number of daily gridded values that contributed to the mean value. For example, at a grid point in the weekly product, the number of vectors would be between 1 and 7, indicating the number of days of the week with a valid vector at that grid point; for a monthly product, the number would be between 1 and 31. Generally, the greater fraction of days in the mean field that contain valid values, the higher the data quality.

Thus, the information contained in the third variable provides a means of characterizing data quality, in addition to the "near coastline" check described above. For example, a data user might choose to filter out vectors with error variances above a certain level, or values for which the nearest observed vector was beyond a particular distance.

File and Directory Structure

All files for this data set are organized on the FTP site into three top-level directories: browse, data, and tools. For a more detailed outline of the directory structure, refer to the 00README.txt file provided on the FTP site.

File Naming Convention

The file naming convention for all files is listed here and described in Tables 3 and 4.

Raw Ice Motion Vectors



Table 3. File Naming Convention Values
Variable Description
icemotion Ice motion
vect Vector
xxxx(x) Sensor (amsre1, avhrr, buoy1, grid2, ssmi3, winds1)
mean Mean
yyyy 4-digit year4
ddd 3-digit day of year4
h Hemisphere (n: Northern, s: Southern)
vVV Version (v02)
.txt Indicates an ASCII text file
.bin Indicates a binary file

1 Available for Northern Hemisphere only.
2 Represents grid files, not vector/sensor files.
3 Files named ssmi include three sensors: SMMR, SSM/I, and SSMIS.
4 File dates indicate the beginning of the vector, either the start of buoy motion or the first satellite image.

Mean Grids

icemotion.mean.01.12.1978.yyyy.h.vVV.bin (Time Series)
icemotion.mean.yyyy.h.v02.bin (Years)
icemotion.mean.mm.1978[1979].yyyy.h.v02.bin (Months)
icemotion.mean.mm.yyyy.h.vVV.bin (Single Month)
icemotion.mean.week.ww.yyyy.h.v02.bin (Weeks)


Table 4. File Naming Convention Values
Variable Description
icemotion Ice motion
mean Mean
01.12 Indicates yearly mean grids
1978.yyyy Indicates yearly mean grids for entire time series (Note: valid time series files also begin in 1979)
yyyy 4-digit year
mm 2-digit month
week Indicates weekly mean grids
ww 2-digit week
h Hemisphere (n: Northern, s: Southern)
vVV Version (v02)
.bin Indicates a binary file
.png Indicates a Portable Network Graphics (PNG) browse image
.ps Indicates a Postscript (PS) browse image

File Size

When uncompressed, approximate file sizes are as follows:

  • Raw ice motion vectors: 14 – 319 KB
  • Daily and mean grids: 604 KB (Southern Hemisphere), 764 KB (Northern Hemisphere)
  • Browse images: 29 – 36 KB (PNG); 521 – 712 KB (PS)

Spatial Coverage

Tables 5 and 6 list the values of corner grid cells for the Northern and Southern Hemispheres.

Table 5. Northern Hemisphere Pixels
Corner Center of Pixel Outer Edge of Pixel
Upper Left 29.89694° N, 135.00000° W 29.71270° N, 135.00000° W
Upper Right 29.89694° N, 135.00000° E 29.71270° N, 135.00000° E
Lower Left 29.89694° N, 45.00000° W 29.71270° N, 45.00000° W
Lower Right 29.89694° N, 45.00000° E 29.71270° N, 45.00000° E
Table 6. Southern Hemisphere Pixels
Corner Center of Pixel Outer Edge of Pixel
Upper Left 37.13584° S, 45.00000° W 36.95776° S, 45.00000° W
Upper Right 37.13584° S, 45.00000° E 36.95776° S, 45.00000° E
Lower Left 37.13584° S, 135.00000° W 36.95776° S, 135.00000° W
Lower Right 37.13584° S, 135.00000° E 36.95776° S, 135.00000° E

Spatial Coverage Maps

Northern Hemisphere Spatial Coverage Southern Hemisphere Spatial Coverage Map

Figure 1. The maps above show spatial coverage for the Northern and Southern Hemispheres.

Determining Vector Components

Note that the U and V vector components are determined with respect to the grid; positive U vectors run from left to right and positive V vectors run from bottom to top. Thus, consider the longitude when retrieving East/West and North/South components.

Spatial Resolution

Source data are regridded to Northern and Southern Hemisphere EASE-Grids with 25 km pixel spacing.

Projection and Grid Description

Data are georeferenced to the EASE-Grid projection, an azimuthal equal area projection. The northern grid is 361 x 361, centered on the geographic North Pole. The southern grid is 321 x 321, centered on the geographic South Pole. Nominal grid size is 25 km. Grid coordinates begin in the center of the upper left grid cell. These grids are subsets of the Northern and Southern EASE-Grids.

Further details on the EASE-Grid projection are provided on the Original EASE-Grid Format Description Web page. For more information on related products and tools, refer to the EASE-Grid Web site.

Temporal Coverage

The temporal coverage varies by type of data and/or by sensor, as shown in Table 7.

Table 7. Temporal Coverage
Type/Sensor Start Date End Date
Daily Gridded Fields 31 October 1978 31 December 2012
Daily ASCII Ice Motion Vectors
     AMSR-E 19 June 2002 08 August 2011
     AVHRR 24 July 1981 30 December 2000
     Buoy 18 January 1979 30 December 2011
     SMMR, SSM/I, SSMIS 25 October 1978 30 December 2012
     Winds (NCEP/NCAR) 01 November 1978 31 December 2012
Mean Gridded Fields
     All 1978 2012
     Climatological monthly means November 1978 December 2012
     Single months November 1978 December 2012
     Weekly means Week 45 in 1978 Week 52 in 2012
     Yearly means 1979 2012

Missing Data

Note that actual data coverage varies slightly and is outlined on the Missing Data page for this data set.

Temporal Resolution

The temporal resolution varies by sensor, as shown in Table 8.

Table 8. Temporal Resolution
Sensor Resolution
AMSR-E Data are available every day for any given grid cell.
AVHRR Four satellite passes are used each day when available.
Buoys The 12:00 Greenwich Mean Time (GMT) buoy positions were used to compute 24-hour mean velocities.
NCEP/NCAR Data are available every day for any given grid cell.
SMMR Data are available every two days for any given grid cell.
SSM/I-SSMIS Data are available every day for any given grid cell.

Sample Data Record

Following is a sample of raw vectors derived from SSM/I data. The first seven lines of icemotion.vect.ssmi.2003078.n are shown. The first line is the header and indicates that this file contains 1679 vectors and that the original grid was 1805 x 1805 pixels. For a description of the data columns see the Raw Ice Motion Vectors Format section of this document.

 1679 1805 1805  
    747.50    267.50      0.00      0.00      3.00
    897.50    267.50      0.00      0.00      3.00
    912.50    267.50      0.00      0.00      3.00
    882.50    282.50      9.05      7.24      3.00
    897.50    282.50      0.00      3.62      3.00
    912.50    282.50      0.00      0.00      3.00
    1242.50   282.50      0.00      0.00      3.00
    1257.50   282.50      0.00      0.00      3.00
    1272.50   282.50     -1.81      3.62      3.00

Quality Assessment

The following Web pages provide accuracy estimates of ice motion from each sensor:

2. Data Access and Tools

Data Access

Data are available via FTP.

Software and Tools

Several IDL programs are available via FTP to read ice motion data, and create Postscript plots or display data to a screen. The IDL procedures and descriptions are listed in Table 9.

Table 9. IDL Procedures and Descriptions
IDL Procedure Description
show_vectors.pro Displays AMSR-E, AVHRR, SMMR, SSM/I-SSMIS, and buoy-derived ASCII sea ice motion vectors
disp_ice_motion.pro Creates animations of gridded and non-gridded sea ice motion vectors
Important Note to Users:

The tools directory also contains the following two map files, which are required for the IDL programs listed in Table 9 to run. These files must be in the same directory as the IDL program:

Following is an example of running an IDL program using the vector file for SSM/I-SSMIS:
IDL> show_vectors, ‘icemotion.vect.ssmi.2012365.n.v02.txt’


The file disp_ice_motion.pro animates daily and mean gridded data by day, week, month, or year. The map files nsidc_north_map and nsidc_south_map must be in the same directory as the IDL program. Following is an example of how to animate northern daily ice motion grids from 01 November 1978 through 01 December 1978:

IDL> disp_ice_motion
% Compiled module: DISP_ICE_MOTION.
Enter time category (1 = Daily Raw Sensor Data or Grids)
                           (2 = Weekly Mean Grids)
                           (3 = Monthly Mean Grids)
                           (4 = Yearly Mean Grids)
: 1 Enter start and end dates for animation (yyyymmdd, e.g., 19950610).
Start Date: 19781101
% Compiled module: JULDAY.
End Date: 19781201
Enter the data type (1 = AVHRR)
                           (2 = Buoy)
                           (3 = SMMR)
                           (4 = SSM/I)
                           (5 = grid)
: 5
Enter the hemisphere (1 = northern)
                             (2 = southern)
: 1
Enter the full name of the directory that the ice motion files are in.
(Note: must correctly use upper and lower case letters.)
: <enter relative or full directory path here>

Row, Column to Latitude, Longitude

In addition, the tools directory contains the following latitude and longitude grids with 25 km pixel spacing, which provide row/column to latitude/longitude conversion information:

Table 10 provides the descriptions for the four columns in each of these files.

Table 10. Column Descriptions for Latitude and Longitude Files
Column Name Description
1 x Grid row number
2 y Grid column number
3 lat Corresponding latitude
4 lon Corresponding longitude

3. Data Acquisition and Processing

Theory of Measurements

Sea ice movement is measured using imagery acquired by frequent, repeat coverage of remote sensing instruments. Ice motion computed from satellite imagery represents the displacement between the acquisition times of two images with the same spatial coverage. Researchers identify a feature, such as an ice floe, on two registered images and measure its pixel displacement. Ice velocity vectors are computed based on the pixel resolution and time span between images.

A more automated method is to measure the correlation of groups of pixels between image pairs. A small target area in one image is correlated with several areas of the same size in a search region of the second image. The displacement of the ice is then defined by the location in the second image where the correlation coefficient is the highest. This spatial correlation method is used to produce ice motion vectors for this data set. This approach is generally valid over short distances away from the ice edge in areas where ice conditions are relatively stable from day to day. Spatial correlation methods cannot, however, find matches between images where a complete knowledge of ice dynamics is needed; for example, in areas where ice is deforming or in the ice margins near the open ocean where ice can deform and rotate—for example, areas where the spatial or spectral characteristics of the ice within a pixel are changing rapidly (Emery, Fowler, and Maslanik 1995).

Data Sources


AVHRR Global Area Coverage (GAC) images at 5 km gridded resolution were used to estimate ice motion over the Arctic and Antarctic because they were available for nearly the entire time series, they provide an intermediate spatial resolution between passive microwave and buoys, they provide finer time sampling than microwave data, and because they are not subject to the same error sources as the other data sets.

Buoy Data

International Arctic Buoy Program (IABP) "C" data were used to calculate ice motion vectors from buoys. IABP provides buoy location information through satellite tracking of buoys placed on sea ice. Several buoy locations are determined each day, and corresponding ice motions are calculated. Ice motion from buoys is very accurate, but it is limited since the numbers and locations of buoys are driven by cost and logistics. Also, buoys have not been placed on ice in the Eastern Arctic.


NCEP/NCAR Reanalysis data were used to derive wind vectors for this data set. The data, called U-wind at 10 m, are available from the NOAA Earth System Research Laboratory (ESRL) Physical Sciences Division (PSD).

The NCEP/NCAR Reanalysis source data set is an assimilation of land surface, rawinsonde, ship, pibal, aircraft, satellite, and various other data within a global weather model. A partial list of some of the sensors and data sources used in the NCEP/NCAR Reanalysis is provided in Table 11. For complete documentation regarding the sensors used as a basis for this data set, refer to the NCEP-NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation paper (Kistler 2001).

Table 11. Examples of Data Sources/Sensors used in NCEP/NCAR Reanalysis Data
Example Data Type Example Data Source and/or Sensor(s) Description
Rawinsonde NCEP Global Telecommunication System (GTS) data The main source for the rawinsonde data, a global collection of upper-air observation data. Also includes pibal and aircraft data.
Surface Marine Data Comprehensive Ocean-Atmosphere Data Set (COADS) data Among other data, includes data from ships, drifting buoys, fixed buoys, pack-ice buoys, and near-surface data from ocean station reports, such as Expendable Bathythermographs (XBTs).
Aircraft Data NCEP Global Telecommunication System (GTS) data The main source for the aircraft data, a global collection of upper-air observation data. Also includes pibal and rawinsonde data.
Surface Land Synoptic Data Air Force Global Telecommunication System (GTS) data The main source for the surface land synoptic data, a global collection of surface data.
Satellite Sounder Data TIROS Operational Vertical Sounder (TOVS) sensors:
High Resolution Infrared Radiation Sounder (HIRS)
Microwave Sounding Unit (MSU)
Stratospheric Sounding Unit (SSU)
The TOVS suite of sensors provides global measurements used in weather forecasting, such as the vertical distribution of temperature and moisture in the atmosphere.
Surface Wind Speed Data Special Sensor Microwave Imager (SSM/I) SSM/I data were used with the Krasnopolsky et al. (1995) algorithm which resulted in wind speeds closer to buoy data, and coverage under cloudy conditions. Measurements include SSM/I wind speed, total precipitable water, and other parameters. (Kalnay et al. 1996)
Satellite Cloud Drift Wind Data Geostationary Meteorological Satellite (GMS) data The GMS program is a series of satellites operated by the Japan Meteorological Agency (JMA). The Visible and Infrared Spin Scan Radiometer (VISSR), the primary instrument aboard GMS, collects visible and infrared images of Earth and its cloud cover.

Passive Microwave Data

NSIDC provided NIMBUS-7 SMMR Pathfinder Brightness Temperatures at 37V GHz (25 km gridded resolution). Due to satellite limitations, full Arctic coverage is only available every two days with SMMR. NSIDC also provided DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures at 37V GHz (25 km resolution) and 85 GHz (12.5 km resolution) in both vertical and horizontal polarizations, as well as AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures at 89 GHz (10 km resolution) in vertical polarization. These passive microwave data essentially provide all-sky coverage, whereas AVHRR data are limited by cloud cover.

Processing Steps

Refer to the following Web pages for detailed information about the methods used to compute ice motion fields:

Mean Fields

Mean ice motion was computed from the daily gridded ice motion data. The northern and southern polar regions have several mean fields: weekly, monthly, annual, and the mean for the entire time series. For the northern region, a mean was calculated for October through June—from freezing to melting seasons. In some cases, this may be of more use than the annual mean in the Arctic.

For the weekly means, at least five out of seven days were needed to compute each vector mean. Weekly means for each year start at 01 January for consistency. The last day of each year (or last two days if in a leap year) were not used. For example, week 1 is always January 1-7 and week 52 is either December 25-31 or December 25-29 (if on a leap year).

For the monthly means, at least 20 days were needed. For any mean greater than one month, at least 40 days were needed.

Version History

Table 12 outlines the processing and algorithm history for this product.

Table 12. Description of Version Changes
Version Date Description of Changes
V2 Sep 2013
  • Added AMSR-E and NCEP/NCAR data for the Northern Hemisphere
  • Extended gridded data from November 1978 through December 2012
  • Updated data and documentation to reflect change to Version 2 (V2)
V1 May 2003 Original version of data. Note: V1 is not indicated in Version 1 file names.

Sensor or Instrument Description

Refer to the following for information on each sensor:

4. References and Related Publications

Cracknell, A. 1997. The Advanced Very High Resolution Radiometer. London: Taylor and Francis.

Emery, W., C. Fowler, and J. Maslanik. 1995. Satellite Remote Sensing of Ice Motion, in Oceanographic Applications of Remote Sensing, ed. Motoyoshi Ikeda and Frederic W. Dobson. CRC Press, Boca Raton.

Isaaks, E., and R. M. Srivastava. 1989. An Introduction to Applied Geostatistics. New York: Oxford University Press.

Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, A. Leetmaa, R. Reynolds, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. Mo, C. Ropelewski, J. Wang, R. Jenne, and D. Joseph. 1996. The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of the American Meteorological Society, 77, 437–471.

Kidwell, K. 1995. NOAA Polar Orbiter Data User's Guide. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, NESDIS.

Kistler, R., et al. 2001. The NCEP–NCAR 50–Year Reanalysis: Monthly Means CD–ROM and Documentation. Bull. Amer. Meteor. Soc., 82, 247–267. doi: http://dx.doi.org/10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2.

Krasnopolsky, V. M., L. C. Breaker, and W. H. Gemmill. 1995. A Neural Network as a Nonlinear Transfer Function Model for Retrieving Surface Wind Speeds from the Special Sensor Microwave Imager. Journal of Geophysical Research, 100(C6), 11,033–11,045. PDF

Maslanik, J., C. Fowler, J. Key, T. Scambos, T. Hutchinson, and W. Emery. 1998. AVHRR-based Polar Pathfinder Products for Modeling Applications. Annals of Glaciology 25:388-392

Rosborough, G., D. Baldwin, and W. Emery. 1994. Precise AVHRR Image Navigation. IEEE Transactions in Geosciences and Remote Sensing 32(3):644-657.

Schweiger, A., C. Fowler, J. Key, J. Maslanik, J. Francis, R. Armstrong, M. J. Brodzik, T. Scambos, T. Haran, M. Ortmeyer, S. Khalsa, D. Rothrock, and R. Weaver. 1999. P-Cube: A Multisensor Data Set for Polar Climate Research. Proceedings on the 5th Conference on Polar Meteorology and Oceanography, American Meteorological Society, Dallas, TX, 15-20 Jan., 136-141.

Thorndike, A. S., and R. Colony. 1982. Sea Ice Motion in Response to Geostrophic Winds. J. Geophys. Res. 87(C8):5845–5852, doi:10.1029/JC087iC08p05845.

Related Data Collections

5. Contacts and Acknowledgments


Mark Tschudi
University of Colorado
Colorado Center for Astrodynamics Research (CCAR), 431 UCB
Boulder, Colorado USA 80309-0431

Technical Contact

NSIDC User Services
National Snow and Ice Data Center
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

6. Document Information

Acronyms and Abbreviations

The acronyms used in this document are listed in Table 13.

Table 13. Acronyms and Abbreviations
Acronym Description
AMSR-E Advanced Microwave Scanning Radiometer - Earth Observing System
ASCII American Standard Code for Information Interchange
AVHRR Advanced Very High Resolution Radiometer
CCAR Colorado Center for Astrodynamics Research
COADS Comprehensive Ocean-Atmosphere Data Set
DMSP Defense Meteorological Satellite Program
EASE-Grid Equal Area Scalable Earth-Grid
PS Postscript
ESRL Earth System Research Laboratory
FTP File Transfer Protocol
GAC Global Area Coverage
GMS Geostationary Meteorological Satellite
GMT Greenwich Mean Time
GTS Global Telecommunication System
HIRS High Resolution Infrared Radiation Sounder
IABP International Arctic Buoy Programme
JMA Japan Meteorological Agency
MCC Maximum Cross Correlation
MSU Microwave Sounding Unit
NCAR National Center for Atmospheric Research
NCEP National Centers for Environmental Prediction
NSIDC National Snow and Ice Data Center
NOAA National Oceanic and Atmospheric Administration
PNG Portable Network Graphics
PSD Physical Sciences Division
RMS Root mean square
SMMR Scanning Multichannel Microwave Radiometer
SSM/I Special Sensor Microwave/Imager
SSMIS Special Sensor Microwave Imager/Sounder
SSU Stratospheric Sounding Unit
TOVS TIROS Operational Vertical Sounder
URL Uniform Resource Locator
UTC Universal Coordinated Time
VISSR Visible and Infrared Spin Scan Radiometer
XBT Expendable Bathythermograph

Document Creation Date

May 2003

Document Revision Date

September 2013

Document URL