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DMSP SSM/I Daily and Monthly Polar Gridded Sea Ice Concentrations in polar stereographic projection currently include Defense Meteorological Satellite Program (DMSP) -F8, -F11, and -F13 daily and monthly sea ice concentrations. Using the Bootstrap algorithm, data gridded at a resolution of 25 x 25 km, begin 25 June 1987. Processing is ongoing. The Special Sensor Microwave Imager (SSM/I) derived ice concentrations are daily total and monthly averaged ice fractions for both hemispheres. The data are provided in Hierarchical Data Format (HDF), with accompanying Graphical Interchange Format (GIF) browse files and are available via FTP.
Note: Users interested in sea ice concentration using the NASA Team algorithm are advised to use Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I Passive Microwave Data.
To broaden awareness of our services, NSIDC requests that you acknowledge the use of data sets distributed by NSIDC. Please refer to the citation below for the suggested form, or contact NSIDC User Services for further information. We also request that you send us one reprint of any publication that cites the use of data received from our Center. This helps us to determine the level of use of the data we distribute. Thank you.
The following example shows how to cite the use of this data set in a publication. List the principal investigators, year of data set release, data set title, dates of data used (for example, 01 January to 15 March 2004), publisher (NSIDC), and media format.
Comiso, J. 1990, updated 2005. DMSP SSM/I daily and monthly polar gridded sea ice concentrations, [list dates used]. Edited by J. Maslanik and J. Stroeve. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media.
| Category | Description | ||||
|---|---|---|---|---|---|
| Data format | HDF format sea ice concentration data (compressed with the UNIX 'tar' utility) GIF browse images |
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| Spatial coverage and resolution | North and south polar regions at 25 km resolution. | ||||
| Temporal coverage and resolution | 25 June 1987 through 31 March 2007 Daily and monthly data |
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| Tools for accessing data | Software tools are available via FTP. | ||||
| Grid type and size | See Polar Stereographic Projections and Grids. | ||||
| File naming convention |
|
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| File sizes | Daily .tar files range from 45 - 777 KB Monthly .tar files are approximately 2 KB |
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| Parameter | Sea ice concentration | ||||
| Procedures for obtaining data | Available via FTP |
DMSP SSM/I Daily and Monthly Polar Gridded Sea Ice Concentrations
Twenty years ago, changes in sea ice from season to season and year to year were not well known. As Robert Massom writes in Satellite Remote Sensing of Polar Regions (1991), "Before the advent of remote sensing from space, estimates of sea ice extent and associated meteorological and oceanic variables came from a combination of ship, island station, and aircraft observations." Studies were "conducted on an opportunity basis and often concentrated in areas of logistic convenience during the summer navigation season...[yielding] data sets inherently biased and therefore of limited scientific value."
Fortunately, the situation has improved. Since 1972, three generations of space borne passive microwave imagers have been launched by the United States, including the Electrically Scanning Microwave Radiometer (ESMR), the Scanning Multichannel Microwave Radiometer (SMMR), and a series of the Defense Meteorological Satellite Program's (DMSP) Special Sensor Microwave/Imagers (SSM/I).
Today, one of the most important parameters provided by passive microwave data in the polar regions is sea ice concentration. Data acquisition is possible because passive microwave wavelengths are relatively unaffected by the frequent and extensive cloud cover that is prevalent in these regions. Sea ice concentration maps are used to track ice edges, estimate ice extent, ice type, actual ice area and the amount of open water within the ice pack. The latter is in turn needed to monitor occurrence, impact, and persistence of polynyas, to calculate heat and salinity fluxes between the ocean and the atmosphere in the polar regions, in addition to many other applications. Global data, immediately practical for use in shipping and petroleum development activities, have broader implications from the standpoint of adding to the meteorological foundations used in understanding and modeling climate change.
Several techniques have been developed to obtain ice concentration from passive microwave data (Svendson et al. 1983; Cavalieri et al. 1984; Swift et al. 1985; Comiso 1986; Comiso and Sullivan 1986; Smith 1996). A review of these techniques and a comparison of some ice concentration results are presented by Steffen et al. (1992) and Smith (1996). Although the various techniques are consistent in finding the location of the ice edge, there are differences in the derived fraction of open water within the ice pack, partly due to the use of different sets of SSM/I channels. Comparative studies with limited Landsat images did not yield conclusive evaluation of the merit of each technique. However, current work with synthetic aperture radar (SAR) data may provide new insights about the discrepancies. These discrepancies can be more than 20 percent as in the Bellingshausen/Amundsen Seas, where effects due to flooding, roughness and snow may be considerable (Comiso 1991). It is also important to mention that since these comparison studies, there has been an adjustment in the Bootstrap algorithm tie points to match ice concentrations derived from SAR during the melt period. This adjustment can be found in Comiso et al. (1997).
This guide accompanies daily north and south polar sea ice concentration grids, and monthly averaged sea ice concentrations.
Roger Barry, Jim Maslanik, and Julienne Stroeve
National Snow and Ice Data Center (NSIDC)
Cooperative Institute for Research in Environmental Sciences (CIRES)
University of Colorado, Boulder, CO, U.S.
Cryospheric Data Management System
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
Sea ice concentration data are used primarily in the following applications:
NSIDC provides a suite of value-added products to aid in investigations of the variability and trends of sea ice cover. These products provide users with information about sea ice extent, total ice covered area, ice persistence, monthly climatologies of sea ice concentrations, and ocean masks.
Sea ice concentrations are calculated using brightness temperatures mapped onto a polar stereographic grid.
The Bootstrap technique, as described by Comiso (1986) and Comiso and Sullivan (1986), uses basic radiative transfer equations and takes advantage of unique multichannel distributions of sea ice emissivity. To derive sea ice concentration using the Bootstrap algorithm, only two microwave channels are needed but additional channels may be required to mask the open ocean.
The SSM/I is a seven channel, four frequency, orthogonally polarized, passive microwave radiometric system. The instrument measures combined atmosphere and surface radiances at 19.3, 22.2, 37.0 and 85.5 GHz. For more information please see the DMSP SSM/I Daily Polar Gridded Brightness Temperatures data set document. Also see the SSM/I instrument description for more details.
Satellite
DMSP-F8, DMSP-F11, and DMSP-F13
The first SSM/I was launched June 19, 1987 as a joint Navy/Air Force operational program to obtain synoptic maps of critical atmospheric, oceanographic, and selected land parameters on a global scale. Key geophysical variables observable by the SSM/I were rain storms over land, ocean surface wind speed, sea ice concentration, and ice/water boundaries.
The SSM/I instrument measures dual polarized radiances at 19.3, 37.0 and 85.5 GHz, and vertically polarized radiances at 22.2 GHz.
Comparison of Orbital Parameters, DMSP-F8, DMSP-F11 and DMSP-F13
The DMSP Block 5D-2 F8, F11 and F13 spacecraft flew in a near polar sun-synchronous orbit. Launched on 18 June 1987, the F8 satellite accomplished 14.1 revolutions per day, with the subsatellite ground track repeating approximately every 16 days. F8 coverage ended 31 December 1991. The F11 was launched on 28 November 1991 with coverage ending 30 September 1995. Processing continues with the launch of the F13, 5 May 1995.
A comparison of instruments, and of the differences in orbital parameters (Abdalati et al. 1995) between the F8 and F11 using overlapping data indicated a high degree of correlation (greater than 0.98) between the F8 and F11 data sets. Small variations were attributed to the different orbital characteristics of the two satellites, especially to the differences in data collection times. When comparing F11 to F13, in terms of hemispheric averages of mean sea ice concentration, the biases introduced by the switch from F11 to F13 are slight and are not statistically significant; however, in some regions relatively large and significant differences are seen. In addition, differences in sea ice extent and total ice-covered area between the two platforms were found to be statistically significant (see NSIDC Special Publication 5 for more information).
| Parameter | DMSP F8 | DMSP F11 | DMSP F13 |
|---|---|---|---|
| Nominal Altitude | 860 km | 830 km | 850 km |
| Inclination Angle | 98.8 degrees | 98.8 degrees | 98.8 degrees |
| Orbital Period | 102 minutes | 101 minutes | 102 minutes |
| Ascending Node Equatorial Crossing (local time) | approximately 6:00 a.m. | approximately 5:00 p.m. | approximately 5:43 p.m. |
Based on the analysis, a set of corrections have been applied to F11 data to maximize consistency between the two data sets.
(adapted from Hollinger and Lo 1983, p. 1-3)
The SSM/I is a seven channel, four frequency, linearly polarized, passive microwave radiometric system. The instrument measures atmospheric/ocean surface antenna temperatures at 19.3, 22.2, 37.0 and 85.5 GigaHertz (GHz).
The instrument consists of a 24 x 26 inch offset parabolic reflector fed by a corrugated, broad-band, seven-port horn antenna. The reflector and feed are mounted on a drum which contains the radiometers, digital data subsystem, mechanical scanning subsystem, and power subsystem.
The reflector-feed drum assembly is rotated about the axis of the drum by a coaxially mounted bearing and power transfer assembly (BAPTA). All data, commands, timing and telemetry signals, and power pass through the BAPTA on slip ring connectors to the rotating assembly.
The SSM/I rotates at a uniform rate making one revolution in 1.9 seconds, during which time the satellite advances 12.5 km. The antenna beams are at an angle of 45 degrees to the BAPTA rotational axis, which is normal to the earth's surface. Thus, as the antenna rotates, the beams define the surface of a cone, and, from the orbital altitude of 833 km, make an angle of incidence of 53.1 degrees at the earth's surface.
The scene is viewed over a scan angle of 102.4 degrees centered on the ground track aft of the satellite, resulting in a scene swath width of 1394 km. The radiometer outputs are sampled differently on alternate scans. During the scene portion of the scans (Type A) the five channels are each sampled over 64 equal 1.6 degree intervals.
Sampling, to 12-bit precision, is accomplished by the "integrate, hold, and dump" method, with an integration period of 7.95 milliseconds for the five channels. Alternate 0.8 degree intervals are centered on the mid-points of the 1.6 degree intervals.
The five channels are sampled on an approximately 25 km grid along the scan and along the track.
Hughes Aircraft Company
A small mirror and a hot reference absorber are mounted on the BAPTA and do not rotate with the drum assembly. They are positioned off-axis such that they pass between the feed horn and the parabolic reflector, occulting the feed once each scan. The mirror reflects cold sky radiation into the feed, thus serving, along with the hot reference absorber, as calibration references for the SSM/I.
This scheme provides an overall absolute calibration which includes the feed horn. Corrections for spillover and antenna pattern effects from the parabolic reflector are incorporated in the data processing algorithms.
NSIDC produced brightness temperatures derived from the SMM/I instruments on DMSP -F8, -F11, and -F13 satellites to create the sea ice concentration data sets.
See Section 5, Errors, below for information about bad data values and file naming conventions.
Beginning with January 2000, processing of brightness temperature data was modified to include two additional quality control steps. The first performs a statistical analysis on the brightness temperature data to look for possible calibration errors. The second was an along-scan adjustment which corrects for interference by the cold-space reflector at scans of 100 or greater, and the difference between antenna temperature observations and the Wentz radiative transfer model. Corrections can be as large as 1 Kelvin. See Stroeve (1998) for more details. Brightness temperature data that included these additional quality control steps are only available for dates after January 2000.
Instrument coverage is global except for circular sectors centered over the pole, approximately 310 km in radius, located poleward of 87 degrees North and 87 degrees South, which are never measured due to orbit inclination. Data set coverage is of the polar regions and is defined by the spatial coverage map described below. The measurement footprint size (effective field of view) is as follows:
| Channel | Field of View |
|---|---|
| 19.3 GHz | 70x45 km |
| 22.2 GHz | 60x40 km |
| 37.0 GHz | 38x30 km |
SSM/I A/B Scan Geometry: SSM/I A/B Scan Geometry:
Swath data consist of A/B scan
pairs. Each pair includes 256 scene stations (numbered).
Scene station numbers (parameter
position numbers) are indicated. Large circles signify
all channels, small circles stand for 85
GHz channels. Brackets indicate scene stations lost
due to antenna pattern correction.
 Northern Hemisphere |
 Southern Hemisphere |
The sea ice concentrations are provided at a resolution of 25 km.
The grids are in a polar stereographic projection. The polar stereographic projection used specifies a projection plane (i.e., the grid) tangent to the earth at 70 degrees. The planar grid is designed so that the grid cells at 70 degrees latitude are 25 km by 25 km. See the data files pixlarea.n and pixlarea.s provided with the tools (Section 7) for information on the true earth-area coverage of all grid cells. For more information on this topic please refer to Pearson (1990) and Snyder (1987).
The polar stereographic projection often assumes that the plane (i.e., the grid) is tangent to the Earth at the pole. Thus, there is a one-to-one mapping between the Earth's surface and grid (i.e., no distortion) at the pole. Distortion in the grid increases as the latitude decreases because more of the Earth's surface falls into any given grid cell, which can be quite significant at the edge of the northern SSM/I grid where distortion reaches 31 percent. For the South Pole, the SSM/I grid has a maximum distortion of 22 percent. To minimize the distortion, the projection is true at 70 degrees rather than the poles. This increases the distortion at the poles by three percent and decreases the distortion at the grid boundaries by the same amount. The latitude of 70 degrees was selected so that little or no distortion would occur in the marginal ice zone. Another result of this assumption is that fewer grid cells will be required as the Earth's surface is more accurately represented. This saves about 100 megabytes per year in data storage.
The polar stereographic formulae for converting between latitude/longitude and X-Y grid coordinates have been taken from Map Projections Used by the U.S. Geological Survey (Snyder 1982). Several different ellipsoids were compared to the Hughes ellipsoid and in each case, differences were less than 1 km over the SSM/I grids. However, differences of up to 9 km were found if a sphere rather than an ellipsoid was used. Thus, it is an explicit requirement that an ellipsoid be used in processing the data.
There are a variety of ellipsoids, for instance, SEASAT has its own ellipsoid. An ellipsoid is defined by equatorial radius and eccentricity. The ellipsoid used in the Hughes (1980, p.3-266) software assumes a radius of 3443.992 nautical miles or 6378.273 kilometers (km) and an eccentricity (e) of 0.081816153 (or e**2 = 0.006693883). The origin of this ellipsoid is not specified in the available Hughes documentation. However, the Hughes ellipsoid is similar to other ellipsoids quoted in the literature (Snyder 1982). To properly convert these coordinates to a polar stereographic grid (the projection of choice), the conversion should assume the Hughes ellipsoid.
Grid dimensions (column,row)
| 85.5 GHz | All other channels |
|
|---|---|---|
| North | (608,896) | (304,448) |
| South | (632,664) | (316,332) |
Grid Coverage:
The origin of each x, y grid is the pole. The grids' approximate outer boundaries are defined in the following table. Values refer to the outside corner of corner pixels, and the outside edge of midpoint pixels. Apply values to the polar grids reading clockwise from upper left. Interim rows define boundary midpoints.
| X(km) | Y(km) | Latitude (deg) | Longitude (deg) | ||
| North Polar: | -3850 | 5850 | 30.98 | 168.35 | corner |
| 0 | 5850 | 39.43 | 135.00 | midpoint | |
| 3750 | 5850 | 31.37 | 102.34 | corner | |
| 3750 | 0 | 56.35 | 45.00 | midpoint | |
| 3750 | -5350 | 34.35 | 350.03 | corner | |
| 0 | -5350 | 43.28 | 315.00 | midpoint | |
| -3850 | -5350 | 33.92 | 279.26 | corner | |
| -3850 | 0 | 55.50 | 225.00 | midpoint | |
| X(km) | Y(km) | Latitude (deg) | Longitude (deg) | ||
| South Polar | -3950 | 4350 | -39.23 | 317.76 | corner |
| 0 | 4350 | -51.32 | 0.00 | midpoint | |
| 3950 | 4350 | -39.23 | 42.24 | corner | |
| 3950 | 0 | -54.66 | 90.00 | midpoint | |
| 3950 | -3950 | -41.45 | 135.00 | corner | |
| 0 | -3950 | -54.66 | 180.00 | midpoint | |
| -3950 | -3950 | -41.45 | 225.00 | corner | |
| -3950 | 0 | -54.66 | 270.00 | midpoint | |
The F8 data stream began 9 July 1987 through 18 December 1991; F11 began 3 December 1991 through 30 September 1995; and the F13 data stream began 5 May 1995, processing continues.
Note to users of SSM/I polar stereographic data for 1994 through April 1995:
Substantial amounts of swath data over Alaska and the Canadian Prairies are missing beginning early in 1994 until May 1995. During this period the data tape recorder on the DMSP-F11 failed. As a result, it was necessary to download data to ground stations more frequently than usual. Data download and acquisition could not occur simultaneously, consequently data gaps exist in the SSM/I data for Alaska and the Canadian Prairies from early 1994 until data were available.
A complete summary of missing dates is available from the DMSP SSM/I Daily Polar Gridded Brightness Temperatures documentation.
Daily and monthly averaged sea ice concentration grids.
The data set consists of sea ice concentration derived from gridded brightness temperatures. Sea ice concentrations range from 0 to 100 percent.
Sea Ice: any ice found at sea which has originated from freezing of sea water. Sea Ice Concentration: fraction of a given area covered by sea ice irrespective of ice type; the ratio describing the areal density of ice in a given area.
Sea ice concentrations are measured in percents or fractions of the pixel area covered by sea ice.
DMSP-F8, F11, and F13 SSM/I
Sea ice concentration data are stored in unsigned 1-byte arrays representing sea ice concentrations ranging from 0 to 100 percent. A stored value of 168 stands for land, and a stored value of 157 indicates missing data.
Monthly averaged sea ice concentration data files also contain sea ice concentration in percent ranging from 0 percent to 100 percent. A value of -88 (or 168 for unsigned byte data types) indicates a land pixel, and a value of -99 (or 157 for unsigned byte data types) indicates missing data.
SSM/I sea ice concentration grids produced by either algorithm are displayed as raster images. Each pixel contains eight bits. Each image for the north polar region contains 448 records (lines) with each line containing 304 pixels (304x by 448y). South polar images contain 332 records (lines) with each line containing 316 pixels (316x by 332y).
The same grid orientation is used for all SSM/I polar stereographic products. That is, the first data value in Northern Hemisphere files corresponds to 30.98 degrees latitude, 168.35 degrees longitude; and the first data value in Southern Hemisphere files corresponds to -39.23 degrees latitude, 317.76 degrees longitude. See page Grid Coverage above for grid coordinate information.
For each product (grid type) there are corresponding land and coastline masks in raster format. Each grid cell contains a flag for the cell type, either 1 or 0. In the land mask, 1 = non-water, 0 = water. In the coastline mask, 1 = coastline, 0 = all land or all water. The mask values are 8-bit bytes. See the Software section of this document for further details on the masks.
Browse images of daily and monthly sea ice concentration are also available in GIF format.
A granule of data is the smallest aggregation of data that is independently managed (i.e., described, inventoried, retrievable). Granules may be managed as logical granules and/or physical granules.
For the SSM/I data set, a data granule consists of the grids that are compiled for the daily and monthly averaged data.
Daily and monthly SSM/I F8, F11, and F13 sea ice concentrations are provided in HDF format. Daily and monthly browse images (in GIF format) are available via FTP.
Also see Importing SSM/I Daily and Monthly Sea Ice Concentration Data into ArcInfo.
Sea ice concentration data from the FTP site are compressed with the UNIX tar utility and contain daily averaged data for the day, hemisphere and algorithm indicated. File naming conventions differ according to temporal resolution. The following table summarizes file naming conventions using the F13 platform as an example:
| Compressed | Uncompressed | |
| Daily | SSMI-sss-vvvyyyymmIHA.tar.Z | Ssmi-sss-vvvyyyymmdd.iha |
| Monthly | sss-yyyy-iha-pp.tar | Ssmi-F13-vvvyyyymm.iha.pp |
Where:
Daily .tar files range in size from 45 - 777 KB each; and monthly .tar files are approximately 2 KB each.
Data are available FTP.
The daily and monthly sea ice concentration grids are generated using the Bootstrap algorithm developed by Joey Comiso.
Daily sea ice concentrations are derived from brightness temperatures. For more details please see NSIDC's DMSP SSM/I Daily Polar Gridded Brightness Temperatures.
SSM/I daily averaged sea ice concentration grids for the Northern and Southern Hemispheres were generated using the Bootstrap algorithm (Comiso 1986, Comiso and Sullivan 1986).
It is important to note that in deriving the ice concentrations from the Bootstrap algorithm, different adjustments were made to the brightness temperatures before they were input into the ice algorithms. The brightness temperatures were adjusted to improve the consistency in ice concentrations between the different SSM/I platforms.
For the Bootstrap algorithm, we found that the brightness temperature adjustments as recommended by Wentz (1993) improved the consistency in total ice fraction, ice extent and ice-covered area between the successive SSM/I sensors.
Beginning with January 2000, processing of brightness temperature data was modified to include two additional quality control steps. The first performs a statistical analysis on the brightness temperature data to look for possible calibration errors. The second was an along-scan adjustment which corrects for interference by the cold-space reflector at scans of 100 or greater, and the difference between antenna temperature observations and the Wentz radiative transfer model. Corrections can be as large as 1 Kelvin. See Stroeve (1998) for more details.
Comparisons between F8, F11 and F13 are summarized in the tables below. In making the comparisons, an enlarged land mask was used to eliminate the large differences found along the coastlines as a result of geolocation uncertainties and to false retrievals of ice cover in open-ocean coastal pixels due to mixed-pixel effects from adjoining land (" land contamination" ).
Summaries using the Bootstrap Algorithm
Comparisons for F8 and F11
Note, overlap period is from 3 December to 18 December 1991.
Comparison of the 16-day mean ice concentrations between F8, F11 and F11 adjusted via Wentz's brightness temperature adjustments. Given are mean F8 and F11 ice fractions, mean differences (F11 minus F8), standard deviation of the differences, correlation coefficient and the root mean square (rms) of the differences.
Mean Mean Standard Correlation rms
Ice Difference Deviation Coefficient error
(%) (%) (%) (r) (%)
Northern Hemisphere
F8 24.36
F11 24.61 0.25 1.29 0.999 1.29
F11(wentz) 24.48 0.11 1.21 0.999 1.21
Southern Hemisphere
F8 16.15
F11 16.18 0.03 1.25 0.999 1.25
F11(wentz) 15.92 -0.23 1.30 0.999 1.28
|
Comparison of the 16-day mean ice extent and ice-covered area between F8, F11 and F11 adjusted via Wentz's brightness temperature adjustments. Percent differences are given in parentheses. Given are the mean F8 and F11 ice extents and ice-covered areas, mean differences (F11 minus F8) and standard deviation of the differences.
Ice Extent:
Mean Mean Difference Std. Dev
x10**6 km**2 (F11-F8) x10**6 km**2
Northern Hemisphere
F8 9.31
F11 9.48 0.17(1.91%) 0.16
F11(wentz) 9.35 0.04(0.42%) 0.10
Southern Hemisphere
F8 9.90
F11 10.03 0.13(1.25%) 0.05
F11(wentz) 9.91 0.01(0.09%) 0.04
|
Ice-Covered Area:
Mean Mean Difference) Std. Dev
x10**6 km**2 (F11-F8) x10**6 km**2
Northern Hemisphere
F8 8.45
F11 8.51 0.06(0.68%) 0.04
F11(wentz) 8.48 0.03(0.34%) 0.03
Southern Hemisphere
F8 7.06
F11 7.18 0.12(1.62%) 0.04
F11(wentz) 7.07 0.01(0.05%) 0.03
|
F11/F13 intercomparison
Note, overlap period is from 3 May through 30 September
Comparison of the 139-day mean ice concentrations between F11, F13 and F13
adjusted via Wentz's brightness temperature adjustments. Given are the mean
F11 and F13 ice fractions, mean differences (F13 minus F11), standard deviation
of the differences, correlation coefficient and the rms of the differences.
Mean Mean Standard Correlation rms
Ice Difference Deviation Coefficient error
(%) (%) (%) (r) (%)
Northern Hemisphere
F11 16.67
F13 16.85 0.17 0.84 0.999 0.79
F13(Wentz) 16.90 0.23 0.81 0.999 0.80
Southern Hemisphere
F11 25.34
F13 25.77 0.43 0.84 0.999 0.72
F13(wentz) 25.75 0.41 0.84 0.999 0.70
|
Ice Extent:
Mean Mean Difference Std. Dev
x10**6 km**2 (F11-F8) x10**6 km**2
Northern Hemisphere
F11 6.95
F13 7.04 0.09(1.36%) 0.07
F13(wentz) 7.04 0.09(1.37%) 0.05
Southern Hemisphere
F11 13.57
F13 13.71 0.14(1.02%) 0.06
F13(wentz) 13.66 0.10(0.70%) 0.06
Ice-Covered Area:
Mean Mean Difference Std. Dev
x10**6 km**2 (F11-F8) x10**6 km**2
Northern Hemisphere
F11 5.71
F13 5.79 0.08(1.47%) 0.07
F13(wentz) 5.77 0.06(1.11%) 0.05
Southern Hemisphere
F11 11.46
F13 11.65 0.19(1.63%) 0.06
F13(wentz) 11.64 0.17(1.53%) 0.06
|
In summer 1999, NSIDC was alerted to errors in latitude, longitude and pixel area files supplied with SSM/I polar stereographic gridded data. Please see the error notice explaining the steps taken to correct the problem.
Missing Pixels:
The links below provide textual and graphical summaries of sea ice data missing
from the grids of this data set. This information allows users computing
various statistics from the data such as ice extent, to quickly determine
the viability of including a particular day's data in their calculations.
For each daily image, NSIDC sums the total number of missing pixels for the
entire image to determine the percentage of missing pixels.
| F8
Northern Hemisphere |
F8
Southern Hemisphere |
|---|---|
 |
 |
| F11
Northern Hemisphere |
F11
Southern Hemisphere |
|---|---|
 |
 |
| F13
Northern Hemisphere |
F13
Southern Hemisphere |
|---|---|
 |
 |
See also:
Geolocation Errors
Geolocation is a continuing problem for users of the SSM/I passive microwave
data. Shortly after the SSM/I temperature data records (TDRs) were released by Fleet Numerical Meteorology and Oceanography Center (FNMOC), independent investigations
at the University of Massachusetts and at NSIDC determined that geolocation
for the sensor was inaccurate. In addition, while processing the 1988 SSM/I
data, RSS found a number of problems with the spacecraft and Earth locations
computed at FNMOC, causing errors in excess of 20 to 30 km being routinely
observed in the SSM/I data. Latitudes and longitudes on the DEF tapes produced
by FNMOC were found to be in error due to the following problems (see Wentz's Users
Manual for more detail).
There are some algorithm errors in the FNMOC data processing software (FNMOC and its contractors are continuing to improve their operational software).
The satellite ephemeris is sometimes incorrect due to spacecraft tracking errors and orbit prediction errors. This problem is particularly severe during periods of increased solar activity.
The boresite nadir angle and the alignment of the SSM/I instrument relative to the spacecraft are slightly misspecified.
In response to the problems identified, RSS developed their own routine for computing the latitude and longitudes rather than using the DEF values. The input into their geolocation routine is the satellite ephemeris for a 7-day period centered on the orbit being processed. The ephemeris is first subjected to quality control and then smoothed to remove any noise. The smoothed ephemeris is then used to compute the SSM/I cell latitudes and longitudes. This algorithm is believed to improve the geolocation accuracy to approximately 5 km (Wentz, personal communication).
For data collected prior to 1989, a correction algorithm developed by researchers at the University of Massachusetts' Department of Electrical and Computer Engineering was used that results in location accuracies of approximately eight kilometers both along and across the scan (Goodberlet 1990). This algorithm assumes all geolocation errors are a result of the pitch, yaw, and roll of the satellite. The three altitude angles were found to have latitude and time dependencies.
Table of coefficients used for data collected before May 15, 1988
*angle = C(l) + C(2)*JDAY + C(3)*abs(LAT) + (C(4)*(JDAY**2))/10000 where: angle = the pitch, yaw or roll correction angle in degrees JDAY = number of days since the beginning of 1987 LAT = scene latitude in degrees |
Although the correction algorithm appears suitable for most of the pre-1989 data, the algorithm does not bring the mislocation to within the 8 kilometer tolerance in later data. The geolocation correction seems to have a periodicity of about one year.
Researchers at Remote Sensing Systems, Inc. attributed the larger errors in the 1989 data to the following circumstances:
An increase in solar activity during early 1989 caused up to 50 km errors in the orbit predictions;
FNMOC implemented irregularities in the geolocation algorithm that occasionally caused " drifts" upwards of hundreds of kilometers. (FNMOC and its contractors are continuing to improve their operational software).
Bootstrap Algorithm Error Analysis
Under ideal winter situations when only thick ice and open water are present,
ice concentration can be derived with the Bootstrap technique at an accuracy
of about five to 10 percent, based on standard deviations of emissivities
as used in the formulation. Errors are higher in the seasonal sea ice region
than in the central Arctic region because of higher standard deviations of
consolidated sea ice in the 19 vs 37 GHz plots. This is partly because of
spatial changes in surface temperature that are not as effectively accounted
for by this set of data.
Constantly changing emissivities of some surfaces present unresolved problems. For example, when leads open up during winter, the open water is exposed to the cold atmosphere and grease ice quickly forms at the surface. The surface then metamorphoses from grease ice, to nilas, to young ice and then to first-year ice with snow cover. During these transitions, the emissivity of the surface can change considerably from one stage to another (Grenfell and Comiso 1986). Since such changes in emissivity are not taken into account in ice concentration algorithms, the derived fractions of open water are therefore not strictly those of open water and may include some mixtures of grease ice and new ice. In spring and summer, the emissivity of thick ice also changes with time, especially over the perennial ice region in the Arctic. The slopes and offsets of the consolidated ice line AD in the scatter plots (see Comiso 1986) are adjusted to automatically take this into account during onset of spring in June; original values should be restored during winter freeze-up. Despite this adjustment, the error is still substantial and can be larger than 20 percent due to spatial variations in melt and affects of meltponding.
Several field and aircraft experiments have been performed in both polar regions for algorithm evaluation. In some of these experiments, basic assumptions about ice types and interpretation of the cluster plots have been confirmed. However, validation of satellite ice concentration data using data from these experiments has not been easy. Field data are difficult to use because of limited coverage compared to the large footprint of the satellite sensors (about 30x30 km). While generally easier to interpret because of fine resolution and availability of ancillary measurements, aircraft data are useful but need to be validated by ground measurements.
Another strategy has been to utilize high resolution satellite data for validation. While the use of high resolution data has its advantages, such strategies degenerate into comparative analysis because the other satellite data also need to be validated. For example, unambiguous discrimination of open water, grease ice, small pancakes, and gray nilas in both visible and microwave channels may be impossible even with high resolution sensors. Generally, however, the passive microwave data provide valuable information about large scale characteristics of the ice cover as well as locations of ice edges, polynyas, and extensive leads. It is, however, useful to note that some of the comparative studies yielded high correlation coefficients.
Note: Users interested in sea ice concentrations using the NASA Team algorithm are advised to use Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I Passive Microwave Data. Although NSIDC no longer distributes or supports the old NASA Team algorithm version of the SSM/I Daily and Monthly Sea Ice Concentrations data set, we are still providing the NASA Team guide document for users that have and wish to continue to use that version of the data. The document is no longer maintained and is being made available for historical purposes only.
Processing of data is ongoing. Input data are received by NSIDC approximately three to six months after they are collected. Processing and release of the ice concentrations typically occur within another three to six months.
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
National Snow and Ice Data Center
Data are available via FTP.
Data processing is ongoing.
Data are in HDF Raster Image Format for sea ice or in HDF Scientific Data Set (SDS) for brightness temperatures. HDF software and libraries are developed and maintained by The HDF Group and may be accessed from the HDF Group Web site. Browse images of daily and monthly sea ice concentration are also provided in GIF format. Finally, NSIDC has provided the tools described below to work with this data set.
Software for reading and displaying the sea ice concentration files is provided via FTP. Included are tools to extract the sea ice concentration files and geolocate the data, as well as masking tools that limit the influence of non-sea ice brightness temperatures.
Source code to extract images from DMSP SSM/I ice concentration products are available via FTP. The extraction executables listed below are from the HDF Group. For more detailed information, please visit the HDF Group Web site.
Interactive Data Language (IDL) is a commercial data visualization and analysis software package available from ITT Visual Systems Solutions. The package is widely used at NSIDC, though no endorsement of the vendor or product is implied. We have provided procedures developed at NSIDC for the convenience of IDL users.
The IDL tools provided with this data set consist of procedures that allow the user to read, display, and export F-8, F-11, and F-13 SSM/I sea ice grids. These were revised in April 2001 to provide display and export capability for the Near Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations. For examples of running these IDL routines, please see the IDL Routines for Passive Microwave Data: Usage Examples Web page.
The following table describes the IDL routines available and how to access them.
| Tool | Description | Access |
|---|---|---|
| extract_ice.pro | IDL program that extracts a time series of SSM/I polar sea ice data. The extraction routine works on both the daily and monthly sea ice files allowing users to select and display sea ice concentrations. For monthly data, users may select which image threshold to view (0, 5, 10, or 15 percent ice cut off). Usage Example. | FTP |
| disp_ssmi_ice_xa.pro | IDL program that will automatically display animations of the sea ice concentration grids. The routine works on both the daily and monthly sea ice files and allows users to display sea ice concentrations. For monthly data, users may select which image threshold to view (0, 5, 10, or 15 percent ice cut off). Usage Example. | FTP |
Useful IDL commands:
openw - a procedure that opens a file for write
IDL> openw,1,'n199809av.ic'
writeu - a procedure that writes data (ex: 'seaice') into an opened file
IDL> writeu,1,seaice
loadct - a procedure that loads a color palette by providing a list or loading the palette indicated by the argument.
xloadct - a procedure that opens a new window giving the user a visual choice of colors to use
For a complete description of IDL, please visit ITT Visual Information Systems Web site.
Example IDL commands to read and display sea ice grids and latitude/longitude grids are provided here.
The geolocation and pixel area tools consist of a FORTRAN routine called locate.for, a latitude/longitude grid and a pixel area grid. The routine locate.for allows the user to enter an i,j coordinate and get the corresponding latitude/longitude coordinate, and vice versa.
Sample IDL commands to read and display latitude/longitude grids are provided here.
Geocoordinate and Pixel Area Tools are available via FTP.
locate.for
A fortran executable that allows the user to
enter an i,j coordinate and get the corresponding latitude/longitude coordinate,
and vice versa.
mapll.for and mapxy.for
These subroutines are associated
with the locate.for program. These programs need to be compiled, but are not
run explicitly. They are called by locate.for. Thus, the user should
compile these programs with locate.for and then use locate to do the conversions.
psn12lats_v2.dat and pss12lats_v2.dat
Grids that can be used to
determine the latitude of a given pixel for the 12.5 km grids (85 Ghz data)
for either hemisphere. These latitude grids are in binary format and stored
as long word integers (4 byte) scaled by 100,000. Each array location (i,j)
contains the latitude value at the center of the corresponding data grid cells.
psn12lats_v2.dat: 608 columns x 896 rows, range = [31.0967, 89.8363]
pss12lats_v2.dat: 632 columns x 664 rows, range = [-39.3649, -89.8368]
psn12lons_v2.dat and ps12lons_v2.dat
Grids that can be used to determine
the longitude of a given pixel for the 12.5 km grids (85 Ghz data) for either
hemisphere. These longitude grids are in binary format and stored as long word
integers (4 byte) scaled by 100,000. Each array location (i,j) contains the
longitude value at the center of the corresponding data grid cells.
psn12lons_v2.dat: 608 columns x 896 rows, range = [00.0000, 360.0000]
pss12lons_v2.dat: 632 columns x 664 rows, range = [000.1651, 359.8350]
psn25lats_v2.dat and pss25lats_v2.dat
Grids that can be used to
determine the latitude of a given pixel for the 25 km grids for either hemisphere.
These latitude grids are in binary format and stored as long word integers
(4 byte) scaled by 100,000. Each array location (i,j) contains the latitude
value at the center of the corresponding data grid cells.
psn25lats_v2.dat: 304 columns x 448 rows, range = [31.0967, 89.8363]
pss25lats_v2.dat: 316 columns x 332 rows, range = [-39.3649, -89.8368]
psn25lons_v2.dat and ps25lons_v2.dat
Grids that can be used to determine
the longitude of a given pixel for the 25 km grids for either hemisphere. These
longitude grids are in binary format and stored as long word integers (4 byte)
scaled by 100,000. Each array location (i,j) contains the longitude value at
the center of the corresponding data grid cells.
psn25lons_v2.dat: 304 columns x 448 rows, range = [00.0000, 360.0000]
pss25lons_v2.dat: 316 columns x 332 rows, range = [000.1651, 359.8350]
Please note that the data ranges given here are latitude and longitude values for the center of each grid cell. The range covered by the full grid extends to the pole (90 degrees latitude) and all longitudes (0 to 360 degrees longitude).
To determine the lat/lon values of corresponding (i,j) data grid cells:
psn12area_v2.dat and pss12area_v2.dat
Grids that can be used
to determine of the area of a given pixel for the 12.5 km grids (85 Ghz data)
for either hemisphere.
The arrays are in binary format and stored as long word integers (4 byte) scaled
by 1000. Each array location (i,j) contains the real value of the corresponding
grid cell.
psn12area_v2.dat and pss12area_v2.dat: 608 columns x 896 rows
psn25area_v2.dat and pss25area_v2.dat
Grids that can be used
to determine of the area of a given pixel for the 25 km grids for either hemisphere.
The arrays are in binary format and stored as long word integers (4 byte) scaled
by 1000. Each array location (i,j) contains the real value of the corresponding
grid cell.
psn25area_v2.dat and pss25area_v2.dat: 304 columns x 448 rows
Beginning with the SMMR era, the first masks to be developed were landmask.ntb and landmask.stb . Other masks were later added, for use with SSM/I F8 data (n3a and s3a ). The next set of masks added are those beginning with "gsfc," which were originally developed for use with SSM/I F11 and F13. The last set of masks added are those beginning with "amsr." All of the masks provided here will work across all platforms (SMMR through SSM/I F13).
Four sets of land masks are available via FTP. The first two are "built in" to SMMR and SSM/I sea ice concentrations, respectively; therefore, users should be aware of effects of land mask differences in time-series analyses from multiple data sets. The following table summarizes the history of land mask development at NSIDC; all are currently provided via FTP.
| Data that the Tools were Distributed with | File name | Characteristics | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SSM/I F-8 series |
|
|||||||||||||||||||||||||
| SSM/I F-11 and F-13 series | gsfc_25n.hdf gsfc_25s.hdf |
North 25 km land mask South 25 km land mask |
||||||||||||||||||||||||
| Snow Melt Onset Over Arctic Sea Ice from SMMR and SSM/I Brightness Temperatures | n3blcmsk.hdf | North 25 km land mask. Ocean pixels adjacent to land or one pixel removed from land are designated as "land-contaminated." |
||||||||||||||||||||||||
| AMSR-E/Aqua Daily L3 12.5-km and 25-km sea ice polar grids | amsr_gsfc_12n.hdf amsr_gsfc_12s.hdf amsr_gsfc_25n.hdf amsr_gsfc_25s.hdf |
The North 25 km AMSR-E land mask is identical to gsfc_25n.hdf, while the South land masks are based on data from the 1997 RADARSAT Antarctic campaign. Although the AMSR-E land masks are more current than those NSIDC uses for SSM/I data, they have not been updated since 1997 to account for many iceberg calvings. | ||||||||||||||||||||||||
The following table summarizes which land masks are used for NSIDC's three primary sea ice products:
| Data set | Land mask used | Differences |
| DMSP SSM/I Daily and Monthly Polar Gridded Sea Ice Concentrations | n3bmask.hdf s3bmask.hdf gsfc_25n.hdf gsfc_25s.hdf |
North polar grid: There are 591 additional pixels that gsfc_25n.hdf classifies as ocean and n3bmask.hdf classifies as land. There are 1305 additional pixels that n3bmask.hdf classifies as ocean and gsfc_25n.hdf classifies as land South polar grid: There are 223 additional pixels that gsfc_25n.hdf classifies as ocean and n3bmask.hdf classifies as land. There are 232 additional pixels that n3bmask.hdf classifies as ocean and gsfc_25n.hdf classifies as land. |
| Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I | gsfc_25n.hdf gsfc_25s.hdf | |
| Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I Passive Microwave Data | gsfc_25n.hdf gsfc_25s.hdf | South polar grid: gsfc_25s.hdf has seven additional pixels of land area, compared with the gsfc_25s.hdf land mask in the Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I product. |
| Data set | Land mask | Source |
| Nimbus-7 SMMR | GSFC-1 | CIA World Shoreline Data Bank II |
| DMSP SSM/I | JPL-1 GSFC-2 |
CIA World Shoreline Data Bank I USGS Digital Chart of the World |
Note on Land Masks
The relatively slight differences in numbers of SSM/I-grid pixels masked as land in the three grids noted above can introduce discrepancies in analyses of time series spanning the SMMR and SSM/I period. One method of addressing this issue is to generate a composite mask in which all pixels mapped as land in any of the masks are coded as land pixels in the composite mask. Use of such a composite mask improves the consistency of the SMMR and SSM/I record at the expense of masking additional ocean areas as land. A composite of the CIA World Data Bank I and II (GSFC-1 and JPL-1) has been produced by J. Maslanik at NSIDC.
An additional issue concerns effects on coastal ocean pixels of contamination by proximity to land. Such proximity can modify the brightness temperatures of coastal ocean pixels, producing false ice concentration values along some coasts. These " pixel mixing" errors are considered in the summer 1996 issue of NSIDC Notes (Issue no. 18). Maslanik et al. discuss the effects of such land contamination in introducing differences between SMMR and SSM/I time series, and describe the use of a modified land mask where land areas are extended to mask substantial contamination. The Snow Melt Onset Over Arctic Sea Ice from SMMR and SSM/I Brightness Temperatures land mask (n3bclmsk.hdf) alleviates this problem whereby ocean pixels adjacent to land or one pixel removed from land are designated as " land-contaminated."
Regional Masks
The regional masks sectmask.n and sectmask.s, available via FTP, are described further in: " Arctic and Antarctic Sea Ice, 1978-1987 Satellite Passive Microwave Observations and Analysis," NASA SP-511.
The files contain standard 300-byte headers, followed by 2-dimensional byte arrays of 448 rows x 304 columns (332 x 316) stored by rows in column order. Regions are assigned different byte values as follows:
Arctic
Region Byte Value
Lakes 0
Non - region Oceans 1
Sea of Okhotsk and Japan 2
Bering Sea 3
Hudson Bay 4
Baffin Bay/Davis Strait/Labrador Sea 5
Greenland Sea 6
Kara and Barents Seas 7
Arctic Ocean 8
Canadian Archipelago 9
Gulf of St. Lawrence 10
Land 11
Coastline 12
Antarctic
Sector Byte Value
Weddell Sea 2
Indian Ocean 3
Pacific Ocean 4
Ross Sea 5
Bellingshausen Amundsen Sea 6
Land 11
Coastline 12
|
Ocean Masks and images of maximum ice extent
Please see Sea Ice Trends and Climatologies from SMMR and SSM/I for details.
Also see Importing SSM/I Daily and Monthly Sea Ice Concentration Data into ArcInfo.
Abdalati, W., K. Steffen, C. Otto, and K. C. Jezek. 1995. Comparison of brightness temperatures from SSMI instruments on the DMSP F8 and F11 satellites for Antarctica and the Greenland Ice Sheet. International Journal of Remote Sensing 16(7):1223-1229.
Ackley, S. F., A. J. Gow, K. R. Buck, and K. M. Golden. 1980. Sea ice studies in the Weddell Sea aboard USCGC Polar Sea. Antarctic Journal of U. S. 15(5):84-86.
Bonbright, D. I. 1984. PODS SSM/I Functional Requirements (Version 1.0). Jet Propulsion Laboratory Document 715-63.
Bonbright, D. I., J. W. Brown, J. E. Hilland, I. T. Hsu, J. A. Johnson, T. L. Kotlarek, R. A. Lassanyi, C. L. Miller, C. S. Morris, and F. J. Salamone. 1987. NASA ocean data system version 3.0. User handbook. Jet Propulsion Laboratory. Document 715-66, 50pp. + appendices.
Cavalieri, D. J., K. M. St. Germain, and C. T. Swift. 1995. Reduction of weather effects in the calculation of sea ice concentration with the DMSP SSM/I. Journal of Glaciology 41(139): 455-464.
Cavalieri, D. J., J. Crawford, M. R. Drinkwater, D. Eppler, L. D. Farmer, R. R. Jentz and C. C. Wackerman. 1991. Aircraft active and passive microwave validation of sea ice concentration from the DMSP SSM/I. Journal of Geophysical Research 96(C12):21,989-22,009.
Cavalieri, D. J., P. Gloersen, and W. J. Campbell. 1984. Determination of sea ice parameters with the NIMBUS-7 SMMR. Journal of Geophysical Research 89(D4):5355-5369.
Comiso J. C., D. J. Cavalieri, C. L. Parkinson, and P. Gloersen. 1997. Passive Microwave Algorithms for Sea Ice Concentration: A Comparison of Two Techniques, Remote Sensing of the Environment 60:357-384.
Comiso, J. C., T. C. Grenfell, M. Lange, A. Lohanick, R. Moore, and P. Wadhams. 1992. Microwave remote sensing of the Southern Ocean Ice Cover. Chapt. 12 In Microwave remote sensing of sea ice. Frank Carsey, editor. American Geophysical Union. Washington, D.C. 243-259.
Comiso, J. C., P. Wadhams, W. Krabill, R. Swift, J. Crawford, and W. Tucker. 1991. Top/bottom multisensor remote sensing of Arctic sea ice. Journal of Geophysical Research 96(C2):2693-2711.
Comiso, J. C. 1991. Satellite remote sensing of the polar oceans. Journal of Marine Systems 2:295-434.
Comiso, J. C. 1990. Arctic multiyear ice classification and summer ice cover using passive microwave satellite data. Journal of Geophysical Research 95(C8):13411-13422.
Comiso, J. C., T. C. Grenfell, D. Bell, M. Lange, and S. Ackley. 1989. Passive microwave in-situ observations of Weddell Sea ice. Journal of Geophysical Research 88(C12):7686-7704.
Comiso, J. C. 1986. Characteristics of Arctic winter sea ice from satellite multispectral microwave observations. Journal of Geophysical Research 91(C1): 975-994.
Comiso, J. C., and C. W. Sullivan. 1986. Satellite microwave and in-situ observations of the Weddell Sea ice cover and its marginal ice zone. Journal of Geophysical Research 91(C8):9663-9681.
Comiso, J. C., S. F. Ackley, and A. L. Gordon. 1984. Antarctic sea ice microwave signatures and their correlation with in-situ ice observations. Journal of Geophysical Research 89(C1):662-672.
Goodberlet, M. A. 1990. Special Sensor Microwave/Imager Calibration/Validation. Ph.D. dissertation submitted to the University of Massachusetts.
Grenfell, T. C. and J. C. Comiso. 1986. Multifrequency passive microwave observations of first-year sea ice grown in a tank. IEEE Transactions on Geoscience and Remote Sensing GE-24:826-831.
Hollinger, J. P., J. L. Pierce, G. A. Poe. 1990. SSM/I instrument evaluation. IEEE Transactions on Geoscience and Remote Sensing 28(5):781-790.
Hollinger, J. P., B. E. Troy, R. O. Ramseier, K. W. Asmus, M. F. Hartman, and C. A. Luther. 1984. Microwave emission from high Arctic sea ice during freeze-up. Journal of Geophysical Research 89(C5): 8104-8122.
Hollinger, J. P. and R. C. Lo. 1983. SSM/I Project Summary Report. Naval Research Laboratory. NRL Memorandum Report 5055. 106 pp.
Hughes Aircraft Company. 1986. Data requirements document for Fleet Numerical Oceanography Center, Rev. B.
Hughes Aircraft Company. 1980. Special Sensor Microwave Imager (SSM/I), computer program product specification (Specification for FNMOC). Vol. II, Sensor Data Processing, Computer Program Component (SMISDP).
Martino, M. G., D. J. Cavalieri and P. Gloersen. 1995. An improved land mask for the SSM/I Grid. NASA Technical Memorandum. TM104625.
Maslanik, J. A. 1992. Effects of weather on the retrieval of sea ice concentration and ice type from passive microwave data. International Journal of Remote Sensing 13(1):37-54.
Massom, R. A. 1991. Satellite remote sensing of polar regions. Boca Raton: Lewis Publishing.
National Center for Supercomputing Applications. 1993. Getting started with HDF. Draft Version 3.2, pp. 44.
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The following acronyms and abbreviations are used in this document.
| DMSP | Defense Meteorological Satellite Program |
| FNMOC | Fleet Numerical Meteorology and Oceanography Center |
| FTP | File Transfer Protocol |
| GHz | Gigahertz |
| GIF | Graphical Interchange Format |
| GSFC | Goddard Space Flight Center |
| HDF | Hierarchical Data Format |
| IDL | Interactive Data Language |
| NASA | National Aeronautics and Space Administration |
| NSIDC | National Snow and Ice Data Center |
| rms | Root Mean Square |
| SSM/I | Special Sensor Microwave Imager |
| SMMR | Scanning Multichannel Microwave Radiometer |
| TDR | Temperature Data Record |
| URL | Uniform Resource Locator |
May 2008
September 2007
http://nsidc.org/data/docs/daac/nsidc0002_ssmi_seaice.gd.html
