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 (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., J. Maslanik, 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 25 October 1978 – 31 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



Data Access


1. Detailed Data Description


Raw Ice Motion Vector Files

The raw ice motion vector files provide the motion vectors from each specific sensor in space-delimited ASCII text format. Each daily file contains a variable number of vectors that are described at the top of every file in 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 five columns for all files, except for the IABP buoy data which contains six columns. The columns are 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 The horizontal vector component in cm/sec
4 v The vertical vector component in cm/sec
51 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 and 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 For the buoy data, there are six columns with the fifth column containing time of day in Universal Coordinated Time (UTC) and the sixth column containing the z value with the IABP buoy number.

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

Daily Gridded and Mean Gridded Files

The daily gridded files provide ice motion vectors by merging the raw ice motion vectors together using a set of rules. See the Processing Steps section of this document for more information on this merging process. The mean gridded files provided averages of the daily gridded data at different resolutions: weekly, monthly, yearly, and the complete time series. Both the 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, u, v). 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 reside on the FTP site in the ftp://sidads.colorado.edu/pub/DATASETS/nsidc0116_icemotion_vectors_v2/ directory. There are three top-level directories: browse, data, and tools. The browse directory contains the browse images of all of the mean fields. The tools directory contains code and applications for reading the data. The data directory is further subdivided by hemisphere: north and south. Within these two directories resides the raw ice motion vectors as well as the daily and mean gridded data in a number of subdirectories. These subdirectories are described in Table 3. For a detailed visual outline of the directory structure, refer to the 00README.txt file provided on the FTP site.

Table 3. Directory Content Description for the data Directory
Subdirectory Description
/north/amsre/ Contains the AMSRE raw ice motion vectors (available for the northern hemisphere only). Within this directory are year directories of the form YYYY that contain the AMSRE raw daily files for that year.
/north/avhrr/ and /south/avhrr/ Contains the AVHRR raw ice motion vectors. Within this directory are year directories of the form YYYY that contain the AVHRR raw daily files for that year.
/north/buoy/ Contains the IABP buoy raw ice motion vectors (available for the northern hemisphere only). Within this directory are year directories of the form YYYY that contain the IABP buoy raw daily files for that year.
/north/grid/ and
Contains the merged gridded daily ice motion vectors. Within this directory are year directories of the form YYYY that contain the daily gridded files for that year.
/north/means/ and /south/means/ Contains the mean gridded ice motion vectors. Within this directory are four subdirectories that contain the different temporal resolution that the data have been averaged to. The complete time series, the monthly means, the weekly means, and the yearly means reside in all, months, weeks, and years, respectively.
/north/ssmi/ and /south/ssmi Contains the SMMR, SSM/I, and SSMIS raw ice motion vectors. Within this directory are year directories of the form YYYY that contain the raw daily files for that year for the SSM/I fleet of instruments.
/north/winds/ Contains the NCEP/NCAR wind vectors. Within this directory are year directories of the form YYYY that contain the NCEP/NCAR raw daily files for that year.

File Naming Convention

This section describes the file naming convention for all files, the raw ice motion vectors and the mean grids, with examples.

Raw Ice Motion Vectors and Daily Gridded Files

Generic File Name: icemotion.vect.xxxx[x].YYYYddd.h.vVV.ext

Example File Name: icemotion.vect.amsre.2011008.n.v02.txt


Table 4. File Naming Convention Values
Variable Description
icemotion.vect Indicates that the file contains ice motion vectors
xxxx[x] Sensor (amsre1, avhrr, buoy1, grid2, ssmi3, or winds1)
YYYY 4-digit year4
ddd 3-digit day of year4
h Hemisphere (n: Northern, s: Southern)
vVV Version (v02: version 2)
.ext File extension (.txt: ASCII text file, .bin: binary file5)
1 Available for Northern Hemisphere only.
2 Represents the daily gridded files; not a sensor file.
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.
5 Available for daily gridded files only

Mean Gridded Files and Browse Images

The mean gridded files and browse images names change depending on the temporal averaging applied to the data.

Generic File Name

Complete Time Series Mean: icemotion.mean.01.12.1978.YYYY.h.vVV.ext
Yearly Means: icemotion.mean.YYYY.h.vVV.ext
Monthly Means: icemotion.mean.mm.1978[1979].YYYY.h.vVV.ext
Single Monthly Mean: icemotion.mean.mm.YYYY.h.vVV.ext
Weekly Means: icemotion.mean.week.ww.YYYY.h.vVV.ext

Example File Name: icemotion.mean.week.01.1980.n.v02.bin


Table 5. File Naming Convention Values
Variable Description
icemotion.mean Indicates that this contains ice motion vector means
01.12.1978 Indicates that this is the time-series averaged file
YYYY 4-digit year. For the yearly, single monthly, and weekly means, this is the year of the data in the file. For the complete time series and monthly means, this is the last year of data in the file.
mm 2-digit month of year
week Indicates that this files contains weekly mean grids
ww 2-digit week of year
h Hemisphere (n: Northern, s: Southern)
vVV Version (v02: version 2)
.ext File extension (.bin: binary data file, .png: PNG browse image, .ps: PostScript browse image)

File Size

When uncompressed, approximate file sizes are as follows:

  • Raw ice motion vectors (.txt): 14 KB - 319 KB
  • Daily and mean grids (.bin): 604 KB (Southern Hemisphere), 764 KB (Northern Hemisphere)
  • Browse images: 29 KB - 36 KB (.png); 521 KB - 712 KB (.ps)

Spatial Coverage

Tables 6 and 7 list the values of corner grid cells for the Northern and Southern Hemispheres, respectively.

Table 6. 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 7. 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. In addition, NSIDC's Mapx Map Transformations Library provides tools for geographic grid conversion. The ice motion grids are described by the files Na25.gpd and N200correct.mpp.

Temporal Coverage and Resolution

The temporal coverage and resolution vary by type of data and/or by sensor, as shown in Table 8.

Table 8. Temporal Coverage and Resolution
Type/Sensor Start Date End Date Resolution
Daily Gridded Fields 31 October 1978 31 December 2012 Daily
Daily ASCII Ice Motion Vectors
AMSR-E 19 June 2002 08 August 2011 Data are available every day for any given grid cell.
AVHRR 24 July 1981 31 December 2004 Four satellite passes are used each day when available.
Buoys 18 January 1979 31 December 2011 The 12:00 Greenwich Mean Time (GMT) buoy positions
were used to compute 24-hour mean velocities.
NCEP/NCAR (Winds) 01 November 1978 31 December 2012 Data are available every day for any given grid cell.
SMMR 25 October 1978 08 July 1987 Data are available every other day for any given grid cell.
See the SMMR 48 Hour Temporal Resolution Consequences for more information.
SSM/I 09 July 1987 31 December 2006 Data are available every day for any given grid cell.
SSMIS 01 January 2007 31 December 2012 Data are available every day for any given grid cell.
Mean Gridded Fields
All 1978 2012 Climatology
Climatological monthly means November 1978 December 2012 Climatology
Single months November 1978 December 2012 Monthly
Weekly means Week 45 in 1978 Week 52 in 2012 Weekly
Yearly means 1979 2012 Yearly

Missing Data

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

Sample Data Record

Following is a sample of raw vectors derived from SSM/I data. The first ten lines of icemotion.vect.ssmi.2003078.n.v02.txt are shown in Figure 2. 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. Figure 3 shows a browse image for the yearly mean ice motion for 2012.

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

Figure 2. First ten lines of icemotion.vect.ssmi.2003078.n.v02.txt

Northern Hemisphere Spatial Coverage

Figure 3. Yearly mean ice motion for 2012. Click for larger image.

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

Read/Plot Data

An IDL program is available in the tools directory on FTP to read ice motion data and create PostScript plots or display data to a screen. The file show_vectors.pro displays AMSR-E, AVHRR, SMMR, SSM/I, SSMIS, and buoy-derived ASCII 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 and SSMIS:
IDL> show_vectors, ‘icemotion.vect.ssmi.2012365.n.v02.txt’

Animate Data

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>

Convert Row/Column Values 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 9 provides the descriptions for the four columns in each of these files.

Table 9. 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 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 a 5 km gridded resolution were used to estimate ice motion over the Arctic and Antarctic for several reasons. First, they were available for nearly the entire time series. Second, they provide an intermediate spatial resolution between passive microwave and buoys and finer time sampling than microwave data. Finally, they are not subject to the same error sources as the other data sets. AVHRR channel 2 (visible band) and channel 4 (infrared) are used.

Buoy Data

International Arctic Buoy Program (IABP) "C" buoy position 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. In addition, buoys have not been placed on ice in the Eastern Arctic.

IABP buoy locations are generally provided every 12 hours: at noon and at midnight Greenwich time. This ice motion product uses 24-hour motion estimates from the IABP. For example, the IABP motion estimate for a buoy at noon on 01 January 2010 is derived by taking the difference of the buoy's location at noon on 02 January 2010 and its location at noon on 01 January 2010 and then dividing by 24 hours. The intervening midnight location value is not factored into the noon-to-noon 24-hour motion estimate. Similarly, the IABP motion estimate for midnight is calculated the same way, ignoring the intervening noon location information. Therefore, each buoy generally has two independent 24-hour motion estimates, one for midnight and one for noon.


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 10. For complete documentation regarding the sensors used as a basis for the NCEP/NCAR data, refer to the NCEP-NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation paper (Kistler 2001).

Table 10. 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

Passive microwave data come from four different instruments: SMMR, SSM/I, SSMIS, and AMSR-E. All the data are downloaded from NSIDC. The SMMR data comes from the NIMBUS-7 SMMR Pathfinder Brightness Temperatures data set at a 25 km gridded resolution. Due to satellite limitations, full Arctic coverage is only available every two days with SMMR. See the SMMR 48 Hour Temporal Resolution Consequences discussion for more information.

The SSM/I and SSMIS data come from DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures and the AMSR-E data come from the AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures. These passive microwave data essentially provide all-sky coverage, whereas AVHRR visible and infrared data are limited by cloud cover. Table 11 provides the channels used from each instrument and their frequencies and resolutions.

Table 11. Channel Frequencies and Resolutions of the Passive Microwave Instruments
Instrument Channel Frequency Resolution
AMSR-E 89 GHz vertical 12.5 km
SMMR 37 GHz vertical and horizontal 25 km
SSM/I 37 GHz vertical and horizontal
85 GHz vertical and horizontal
25 km
12.5 km
SSMIS 37 GHz vertical and horizontal
91 GHz vertical and horizontal
25 km
12.5 km

Processing Steps

The following steps were used to create this ice motion product.

  1. Grid the Input Data to the 25 km EASE-Grid
  2. Compute the Ice Motion Fields
    Detailed information about the methods used to compute ice motion fields for each input data source:
  3. Merge the Ice Motion Fields
    Each of the ice motion estimates, for example from NCEP winds, IABP buoys, or AMSR-E, are computed and gridded individually. Once computed, these independent estimates are then combined into a final motion estimate. Each source is weighted according to the expected accuracy of the source data. For example, estimates derived from nearby buoys are weighted higher than NCEP-derived estimates.

    To compute the final gridded motion estimate, each of the independent estimates are mapped to the output grid. A source-weighted and distance-weighted average of the nearest 15 estimates is used to compute the final motion estimate. Note that where data are sparse, the data sources will be widely separated; and when data are dense, only the very nearest estimates are considered. If the motion estimates vary significantly from each other, this method can result in motion fields that do not always vary smoothly.

    See the Merged Daily Gridded Vectors for more information.
  4. Compute Mean Fields
    Mean ice motion was computed from the merged 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 in 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.
  5. Write Data to ASCII and Binary Data Files

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

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.

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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
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
PS PostScript
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 Locater
UTC Universal Coordinated Time
VISSR Visible and Infrared Spin Scan Radiometer
XBT Expendable Bathythermograph

Document Creation Date

May 2003

Document Revision Date

February 2015
September 2013

Document URL