Close

Service Interruption

The NSIDC Web site and data services are currently having intermittent problems and may be unavailable. We are working to restore these services as soon as possible and apologize for any inconvenience this may cause. Please contact NSIDC User Services for assistance.

Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data

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 example. For more information, see our Use and Copyright Web page.

Cavalieri, D., C. Parkinson, P. Gloersen, and H. J. Zwally. 1996, updated yearly. Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data. [indicate subset used]. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice Data Center.

Overview

Platforms

Nimbus-7, DMSP-F8, -F11, -F13, -F17

Sensors

SMMR, SSM/I-SSMIS

Spatial Coverage

North and south polar regions

Spatial Resolution

25 km

Temporal Coverage

26 October 1978 – most current processing

Temporal Resolution

SMMR: every other day, monthly
SSM/I-SSMIS: daily, monthly

Parameters

Sea ice concentration

Data Format

Flat binary (1-byte scaled, unsigned integers)

Note: The data format information in this document represents the data in its native format as it is archived at NSIDC. If you have downloaded the data using Polaris, please consult the 00README file located in the tar file for information on the data format operations that were performed on this data set.

Metadata Access

View Metadata Record

Data Access

FTP

1. Detailed Data Description

This data set is generated from brightness temperature data derived from the following sensors: the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the Defense Meteorological Satellite Program (DMSP) -F8, -F11 and -F13 Special Sensor Microwave/Imagers (SSM/Is), and the DMSP-F17 Special Sensor Microwave Imager/Sounder (SSMIS). The data are provided in the polar stereographic projection at a grid cell size of 25 x 25 km.

This product is designed to provide a consistent time series of sea ice concentrations (the fraction, or percentage, of ocean area covered by sea ice) spanning the coverage of several passive microwave instruments. To aid in this goal, sea ice algorithm coefficients are changed to reduce differences in sea ice extent and area as estimated using the SMMR and SSM/I sensors. The data are generated using the NASA Team algorithm developed by the Oceans and Ice Branch, Laboratory for Hydrospheric Processes at NASA Goddard Space Flight Center (GSFC).

These data include gridded daily (every other day for SMMR data) and monthly averaged sea ice concentrations for both the north and south polar regions. The data are produced at GSFC about once per year, with roughly a one-year latency, and include data since 26 October 1978. Data are produced from SMMR brightness temperature data processed at NASA GSFC and from SSM/I and SSMIS brightness temperature data processed at the National Snow and Ice Data Center (NSIDC).

Data are scaled and stored as one-byte integers in flat binary arrays. For each data file, a corresponding PNG browse image file is provided.

Accounting for Sensor Differences

The goal of this data set is to provide a long term, consistent sea ice concentration product in which sea ice extent and area differences between the sensors are reduced and could serve as a baseline for future measurements. To achieve this, it is necessary to address differences between the SMMR and the DMSP-F8, -F11, and -F13 SSM/I sensors, as well as the DMSP-F17 SSMIS sensor. This document describes the basic characteristics of the SMMR, SSM/I, and SSMIS platforms and summarizes the problems encountered when deriving sea ice concentrations from brightness temperatures measured by sensors with different frequencies, different footprint sizes, different visit times, and different calibrations. A major obstacle to resolving these differences is the lack of sufficient overlapping data from sequential sensors. The techniques employed to solve these problems, or at least reduce their impacts, include:

  • Mapping the sensor data onto a common grid
  • Applying a new land mask
  • Addressing instrument drift
  • Adjusting for land-to-ocean spillover
  • Replacement of bad data
  • Inter-sensor corrections made to reduce remaining measurement differences

Basic limitations also arise from the sensor resolution, temporal coverage, and algorithm assumptions and characteristics. The NASA Team algorithm is not designed to provide ice concentration for fresh-water ice (for example, lake and river ice). The filtering used to remove land-to-ocean spillover may affect the area of some open water features within the ice pack near coasts (coastal polynyas).

Using These Data

Potential applications for these sea ice concentration data include:

  • Monitoring the distribution, extent, and area of the Arctic and Antarctic sea ice cover
  • Identifying and monitoring large, persistent open water areas surrounded by sea ice (polynyas)
  • Analyses of regional and global trends in sea ice cover
  • Validation of sea ice models and climate models
  • Analysis of sea ice/ocean and sea ice/atmosphere interactions

Users should be aware that the ice concentration maps were derived from algorithms that were "tuned" to minimize the differences in ice extent and ice covered area during the overlap periods when transitioning from one instrument to the next (overlap from SMMR to DMSP-F8 SSM/I, from DMSP-F8 to -F11 SSM/I, from DMSP-F11 to -F13 SSM/I, and from DMSP-F13 SSM/I to DMSP-F17 SSMIS). This does not mean that the ice concentrations themselves are well matched. See the Data Verification by Data Center section of this document for a summary of ice extent and ice covered area differences during the overlap periods.

It is also important to know that SMMR and SSM/I-SSMIS have different data gaps at the North Pole due to orbital differences. Therefore, any time series of parameters, such as ice extent and ice covered area, need to take these differences into account. A pole mask is provided for this purpose (see the Masks and Overlays section).

Particular care is needed to interpret the sea ice concentrations during summer when melt is present, and in regions where new sea ice makes up a substantial part of the sea ice cover. Some residual errors remain due to weather effects and mixing of ocean and land area within the sensor field of view, or FOV, and due to sensor differences.

It is recommended that sea ice extent and area be computed from daily maps of ice concentrations that are then used to compute monthly averages of those parameters. Computations of sea ice extents and sea ice areas should not be made from the monthly-averaged ice concentration maps because that may result in a biased time series.

Format

Data are scaled, unsigned flat binary with one byte per pixel, and therefore have no byte order, or endianness. Data are stored as one-byte integers representing scaled sea ice concentration values. Range section for more information. For each data file, a corresponding browse image file in PNG format is also provided.

The file format consists of a 300-byte descriptive header followed by a two-dimensional array of one-byte values containing the data. The file header is composed of:

  • a 21-element array of 6-byte character strings that contain information such as polar stereographic grid characteristics
  • a 24-byte character string containing the file name
  • a 80-character string containing an optional image title
  • a 70-byte character string containing ancillary information such as data origin, data set creation date, etc.

For compatibility with ANSI C, IDL, and other languages, character strings are terminated with a NULL byte.

The file header can be accessed in a variety of ways. For example, it can be treated as a simple sequence of bytes containing ASCII character strings or as a complex data structure of arrays. Table 1 describes the file header.

Table 1. File Header Description
Bytes Description
1-6 Missing data integer value
7-12 Number of columns in polar stereographic grid
13-18 Number of rows in polar stereographic grid
19-24 Unused/internal
25-30 Latitude enclosed by polar stereographic grid
31-36 Greenwich orientation of polar stereographic grid
37-42 Unused/internal
43-48 J-coordinate of the grid intersection at the pole
49-54 I-coordinate of the grid intersection at the pole
55-60 Five-character instrument descriptor (SMMR, SSM/I)
61-66 Two descriptors of two characters each that describe the data;
(for example, 07 cn = Nimbus-7 ice concentration)
67-72 Starting Julian day of grid data
73-78 Starting hour of grid data (if available)
79-84 Starting minute of grid data (if available)
85-90 Ending Julian day of grid data
91-96 Ending hour of grid data (if available)
97-102 Ending minute of grid data (if available)
103-108 Year of grid data
109-114 Julian day of grid data
115-120 Three-digit channel descriptor (000 for ice concentrations)
121-126 Integer scaling factor
127-150 24-character file name (without file-name extension)
151-230 80-character image title
231-300 70-character data information (creation date, data source, etc.)

The data can be read with image processing software by specifying a 300-byte header, with an image size of 304 columns x 448 rows for Arctic data and 316 columns x 332 rows for Antarctic data. In a high-level programming language or image processing software, declare a 300-byte array for the header and an array (for example, 304 x 448 for Arctic) for the image. Read the 300-byte array first, then read the image array.

File and Directory Structure

Data are on the FTP site in the /pub/DATASETS/nsidc0051_gsfc_nasateam_seaice/ directory, as shown in Figure 1.

Within the final-gsfc directory are north and south directories that contain data files, and a browse directory that contains browse image PNG files. Daily and monthly data are further separated into directories named daily and monthly. For daily data, there is also one directory for each year of available data. For example, all of the north daily data for 1990 are in a directory named /nsidc0051_gsfc_nasateam_seaice/final-gsfc/north/daily/1990/.

The directory structure is illustrated in Figure 1; not all directories are shown fully expanded. The structure for each south directory matches that of the corresponding north directory. Each browse directory is divided into a structure that reflects that of the data. In this illustration, the year directories underneath final-gsfc are representative placeholders; on the FTP site, there are actually many such directories, each named for the year of data it contains, such as 1987, 2000, etc.

Directory structure

Figure 1. Directory Structure

File Naming Convention

Data

The file naming convention for the daily data is nt_YYYYMMDD_SSS_vVV_R.bin, where the nt prefix indicates this was created with the NASA Team algorithm, the .bin extension indicates a binary file, and:

SSS Sensor (n07 for Nimbus-7 SMMR; f08, f11, or f13 for DMSP-F8, -F11 or -F13 SSM/I; f17 for DMSP-F17 SSMIS)
YYYY Four-digit year
MM Two-digit month
DD Two-digit day
VV Data version number (for example, 01)
R Region (n = north; s = south)

For example, nt_20030115_f13_v01_n.bin is the daily file from sensor DMSP-F13 for the date 15 January 2003, and it is Version 1 data for the north region.

The file naming convention for monthly data is nt_YYYYMM_SSS_vVV_R.bin, where the nt prefix indicates this was created with the NASA Team algorithm, the .bin extension indicates a binary file, and:

SSS Sensor (n07 for Nimbus-7 SMMR; f08, f11, or f13 for DMSP-F8, -F11 or -F13 SSM/I; f17 for DMSP-F17 SSMIS)
YYYY Four-digit year
MM Two-digit month
VV Data version number (for example, 01)
R Region (n = north; s = south)

For example, nt_200301_f13_v01_n.bin is the monthly file from sensor DMSP-F13 for January 2003, and it is Version 1 data for the north region.

Browse Images

Browse image files are named using the same convention as the data files, except the file extension is .png instead of .bin.

File Size

Data file size varies by region:

  • North: 136492 bytes
  • South: 105212 bytes

Spatial Coverage

Data set coverage includes the polar regions defined by the Polar Stereographic Projections and Grids spatial coverage map.

SSM/I instrument coverage is global, except for circular sectors centered over the pole, 311 km in radius, located poleward of 87.2°. These sectors are never measured due to orbit inclination. The measurement footprint size (effective field of view, or FOV) varies by frequency for each sensor, as shown in Table 2.

Table 2. SSM/I and SSMIS FOV
Frequency Footprint Size
19.3 GHz 70x45 km
22.2 GHz 60x40 km
37.0 GHz 38x30 km

SMMR instrument coverage is global, except for circular sectors centered over the North pole, approximately 611 km in radius, located poleward of 84.5°. These sectors are never measured due to orbit inclination. The 50° scan pattern provided a swath width of 780 km at the Earth's surface. The spatial resolutions at the various frequencies ranged from approximately 27 km at 37 GHz to 148 km at 6.6 GHz. The measurement footprint size varies by frequency, as shown in Table 3.

Table 3. SMMR FOV
Frequency Footprint Size
6.6 GHz 148x95 km
10.7 GHz 91x59 km
18.0 GHz 55x41 km
21.0 GHz 46x30 km
37.0 GHz 27x18 km

Spatial Resolution

The spatial resolution for this data set is 25 km.

Projection and Grid Description

The sea ice concentration data are displayed in polar stereographic projection. For more information, see Polar Stereographic Projections and Grids. The grid size varies depending on the region, as shown in Table 4.

Table 4. Regional Grid Size
Region Columns Rows
North 304 448
South 316 332

Temporal Coverage

Data are from 26 October 1978 through the most current processing. See the Data Acquisition Methods section for dates by instrument and platform.

Temporal Resolution

The SMMR instrument scanner operated only on alternate days, due to spacecraft power limitations. Therefore, SMMR data were only collected every other day. Typically, there are at least 14 days of coverage per month, although there are major data gaps in August of 1982 (04, 08, and 16 August 1982), and in August of 1984 (13 through 23 August 1984) for both polar regions.

SSM/I data were collected daily and SSMIS data continue to be collected daily. A major data gap in the SSM/I data exists from 03 December 1987 to 13 January 1988. For the latest details regarding data gaps, refer to the SSM/I-SSMIS Brightness Temperature Data Availability Web page.

Sea ice concentrations are provided for each day of data and also as monthly means. The monthly means are generated by averaging all the available daily files for each individual month, excluding pixels of missing data (see the Monthly Data Generation section of this document for more information).

Parameter or Variable

Parameter Description

Sea ice concentration represents an areal coverage of sea ice. For a given grid cell, the parameter provides an estimate of the fractional amount of sea ice covering that cell, with the remainder of the area consisting of open ocean. Land areas are coded with a land mask value.

Parameter Source

Data sources are Nimbus-7 SMMR, DMSP-F8, -F11 and -F13 SSM/I instruments, and the DMSP-F17 SSMIS instrument.

Parameter Range

Data are stored as one-byte integers representing sea ice concentration values. The sea ice concentration data are packed into byte format by multiplying the derived fractional sea ice concentration floating-point values (ranging from 0.0 to 1.0) by a scaling factor of 250. For example, a sea ice concentration value of 0.0 (0%) maps to a stored one-byte integer value of 0, and a sea ice concentration value of 1.0 (100%) maps to a stored one-byte integer value of 250. To convert to the fractional parameter range of 0.0 to 1.0, divide the scaled data in the file by 250. To convert to percentage values (0% to 100%), divide the scaled data in the file by 2.5.

Data files may contain integers from 0 to 255, as described in Table 5.

Table 5. Description of Data Values
Data Value Description
0 - 250 Sea ice concentration (fractional coverage scaled by 250)
251 Circular mask used in the Arctic to cover the irregularly-shaped data gap around the pole (caused by the orbit inclination and instrument swath)
252 Unused
253 Coastlines
254 Superimposed land mask
255 Missing data

Data Validation by Source

The performance of the NASA Team algorithm was assessed in numerous studies (for example, Cavalieri et al. 1992); these results apply to this data set. However, improvements in this data set that differ from previous studies include the minimization of coastal and open-ocean influences that tend to yield inaccurate sea ice concentrations. Visual data checking was used to assess the performance of these modifications.

Confidence Level/Accuracy Judgment

Estimates of the accuracy of the NASA Team algorithm vary depending on sea ice conditions, methods, and locations used in individual studies. Cavalieri et al. (1992) summarizes several of these studies. In general, accuracy of total sea ice concentration is within +/- 5% of the actual sea ice concentration in winter, and +/- 15% in the Arctic during summer when melt ponds are present on the sea ice. Accuracy tends to be best within the consolidated ice pack when the sea ice is relatively thick (greater than 20 cm) and ice concentration is high. Accuracy decreases as the proportion of thin ice increases. See Cavalieri et al. (1992), Steffen et al. (1992), and other listed references for an overview of the algorithm performance.

Data Verification by Data Center

NSIDC staff visually checks the data files and selected graphics files. This includes verification of proper file structure; comparisons to existing SMMR-, SSM/I-, and SSMIS-derived sea ice concentration grids, masks, and information files; and examination of data quality.

Some weather-related effects and land contamination are still present. The amount and spatial distribution of remaining weather effects vary with season. Also, occasional bad scan lines still appear in the data. Based on NSIDC analyses, some sensor-to-sensor differences are likely to remain in these data, particularly for marginal ice zones. See NSIDC Special Report 5: An Intercomparison of DMSP F11- and F13-derived Sea Ice Products for summaries of differences among the SSM/I sensors.

Residual weather effects and processing errors in May 1986 data result in large bands of very low ice concentrations over the open ocean in the Weddell, Bellingshausen, and Amundsen seas in the Southern Hemisphere. Although the magnitude of these false ice concentrations is less than one percent, users should be aware that such errors do occur in data for many days within that month.

Overlap periods exist when transitioning from one instrument to the next. These overlaps are from SMMR to DMSP-F8 SSM/I, from DMSP-F8 to -F11 SSM/I, from DMSP-F11 to -F13 SSM/I, and from DMSP-F13 SSM/I to DMSP-F17 SSMIS. During overlap periods, data were available from two instruments, although good data may not be available from both instruments during the entire operating overlap. Differences in ice covered area and ice extent during the overlap periods were minimized by tuning the sea ice algorithms. Wavelet analysis of the time series of ice extent and ice covered area show no significant offsets between the different satellites.

Tables 6 and 7 summarize the comparison between the ice covered areas and ice extent during the overlap periods, including mean differences and linear regression results of ice covered areas and ice extent. Mean differences are computed for SMMR minus DMSP-F8 SSM/I, DMSP-F8 SSM/I minus DMSP-F11 SSM/I, DMSP-F11 SSM/I minus DMSP-F13 SSM/I, and DMSP-F13 SSM/I minus DMSP-F17 SSMIS. Regression coefficients are computed using y = a0 + a1*x, for each (x, y) pair (x=SMMR, y=DMSP-F8 SSM/I); (x=DMSP-F8 SSM/I, y=DMSP-F11 SSM/I); (x=DMSP-F11 SSM/I, y=DMSP-F13 SSM/I); and (x=DMSP-F13 SSM/I, y=DMSP-F17 SSMIS). While this analysis shows no significant differences between the overall summaries of ice covered area and ice extent, significant regional differences in ice concentration may still be present.

Table 6. Northern Hemisphere Sensor Differences
  Mean Difference
(x 106km2)
Standard Deviation
(x 106km2)
a0
(x 106)
a1
(x 106)
Correlation
Coefficient
% Difference
SMMR to DMSP-F8 SSM/I  
Ice area 0.073 0.054 0.214 0.947 0.999 1.34%
Ice extent 0.055 0.096 0.412 0.941 0.998 0.70%
DMSP-F8 to DMSP-F11 SSM/I  
Ice area -0.019 0.036 0.955 0.914 0.996 0.18%
Ice extent 0.002 0.058 0.351 0.972 0.983 0.01%
DMSP-F11 to DMSP-F13 SSM/I  
Ice area -0.0112 0.0296 0.0079 0.997 0.999 0.18%
Ice extent -0.0004 0.0457 0.0199 0.997 0.999 -0.01%
DMSP-F13 to DMSP-F17 SSMIS  
Ice area -0.0389 0.0188 0.0329 1.0007 0.999 0.5433%
Ice extent -0.0027 0.0426 -0.0297 1.0032 0.999 -0.0156%

Table 7. Southern Hemisphere Sensor Differences
  Mean Difference
(x 106km2)
Standard Deviation
(x 106km2)
a0
(x 106)
a1
(x 106)
Correlation
Coefficient
% Difference
SMMR to DMSP-F8 SSM/I  
Ice area 0.018 0.072 0.225 0.982 0.992 0.15%
Ice extent 0.005 0.058 -0.198 1.011 0.998 0.0%
DMSP-F8 to DMSP-F11 SSM/I  
Ice area -0.038 0.092 0.630 0.924 0.996 0.49%
Ice extent 0.012 0.067 0.289 0.974 0.998 0.08%
DMSP-F11 to DMSP-F13 SSM/I  
Ice area 0.0311 0.0344 -0.0474 1.007 0.999 0.26%
Ice extent 0.0126 0.0402 -0.0186 1.002 0.999 0.08%
DMSP-F13 to DMSP-F17 SSMIS  
Ice area -0.0212 0.0314 -0.0097 1.0034 0.999 0.1550%
Ice extent -0.0009 0.0309 0.0109 0.9992 0.999 0.0304%

3. Data Access and Tools

Data Access

Data are available via FTP.

Software and Tools

Software tools are available via direct FTP or via the Polar Stereographic Data Tools Web page.

Software and tools for reading and displaying the files are located in the tools directory on the FTP site (Fig. 2). Software includes IDL routines to ingest and read sea ice concentration data. Masks and overlays are also provided.

Table 8 lists the tools that can be used with this data set. For a comprehensive list of all polar stereographic tools and for more information, see the Polar Stereographic Data Tools Web page.

Table 8. Tools for this Data Set
Tool Type Tool File Name(s) or Description
Data Extraction extract_ice.pro
Data Display dataviewer.tar.gz
Geocoordinate dataviewer.tar.gz
locate.for
mapll.for and mapxy.for
psn25lats_v3.dat and pss25lats_v3.dat
psn25lons_v3.dat and pss25lons_v3.dat
Pixel-Area psn25area_v3.dat and pss25area_v3.dat
Land Masks gsfc_25n.msk and gsfc_25s.msk
coast_25n.msk and coast_25s.msk
ltln_25n.msk and ltln_25s.msk
pole_n.msk
Region Masks region_n.msk and region_s.msk
Ocean Masks Includes monthly ocean masks and maximum extent masks for the Northern (n) and Southern (s) Hemispheres

Help Topics

For instructions on importing these data into ArcGIS, see our NSIDC User Services Online Support.

4. Data Acquisition and Processing

Theory of Measurements

The SMMR, SSM/I, and SSMIS instruments are microwave radiometers that sense emitted microwave radiation. This radiation is affected by surface and atmospheric conditions, and thus provides a range of geophysical information.

Source/Platform

The Nimbus-7 and DMSP F-series spacecraft fly in near-polar sun-synchronous orbits; details their respective orbits are compared in Table 9.

Table 9. Comparison of Orbital Parameters
Parameter Nimbus-7 DMSP-F8 DMSP-F11 DMSP-F13 DMSP-F17
Nominal Altitude1 955 km 860 km 830 km 850 km 850 km
Inclination Angle 99.1 degrees 98.8 degrees 98.8 degrees 98.8 degrees 98.8 degrees
Orbital Period 104 minutes 102 minutes 101 minutes 102 minutes 102 minutes
Ascending Node Equatorial Crossing
(Local Time)
Approx. 12:00 p.m. Approx. 6:00 a.m. Approx. 5:00 p.m. Approx. 5:43 p.m. Approx. 5:31 p.m.
Algorithm Frequencies1 18.0, 37.0 GHz 19.3, 37.0 GHz 19.3, 37.0 GHz 19.3, 37.0 GHz 19.3, 37.0 GHz
Earth Incidence Angle1 50.2 53.1 52.8 53.4 53.1
3 dB Beam Width (Degrees)1 1.6, 0.8 1.9, 1.1 1.9, 1.1 1.9, 1.1 1.9, 1.1

1 Indicates sensor and spacecraft orbital characteristics of the sensors used in generating the sea ice concentrations.

Sensor or Instrument Description

The SMMR is a 10-channel instrument delivering orthogonally polarized antenna temperature data at five dual-polarized (horizontal, vertical) frequencies: 6.6 GHz, 10.7 GHz, 18.0 GHz, 21.0 GHz, and 37.0 GHz. Please see the SMMR Instrument Description for more details.

The SSM/I is a seven-channel, orthogonally polarized, passive-microwave radiometric system. The instrument measures combined atmosphere and surface radiances at 19.3 GHz, 22.2 GHz, 37.0 GHz and 85.5 GHz frequencies. Please see the SSM/I Instrument Description for more details.

The SSMIS sensor is a conically-scanning passive microwave radiometer that harnesses the imaging and sounding capabilities of three previous DMSP microwave sensors, including the SSMI, the SSM/T-1 temperature sounder, and the SSMI/T-2 moisture sounder. The SSMIS sensor measures microwave energy at 24 frequencies from 19 to 183 GHz with a swath width of 1700 km. Please refer to the SSMIS Instrument Description Web page for more details.

Data Acquisition Methods

The combined SMMR, SSM/I, and SSMIS sea ice concentration time series is produced from brightness temperatures obtained from GSFC and NSIDC. The four sets of satellite data currently used to create this data stream, and the time periods for which the data are usable, are shown in Table 10.

Table 10. Usable Time Periods for Data
Platform and Instrument Time Period
Nimbus-7 SMMR 26 October 1978 through 20 August 1987
DMSP-F8 SSM/I 09 July 1987 through 31 December 1991
DMSP-F11 SSM/I 03 December 1991 through 30 September 1995
DMSP-F13 SSM/I 03 May 1995 through 31 December 2007
DMSP-F17 SSMIS 01 January 2007 through the most recent data (data acquisition is ongoing)
SMMR

Sea ice concentrations were processed by GSFC using SMMR brightness temperatures. The SMMR brightness temperatures were processed and quality checked at GSFC (Gloersen et al. 1992).

SSM/I, SSMIS
SSM/I and SSMIS brightness temperature data used to create this sea ice concentration time series are distributed by NSIDC. Processing of DMSP-F17 SSMIS brightness temperatures is ongoing.

Derivation Techniques and Algorithms

This section is extracted from NASA Technical Memorandum 104647.

Sea ice concentrations for this data set were produced using a revised NASA Team algorithm that uses a different set of tie points and weather filters than the original NASA Team algorithm (see NASA Team Sea Ice Algorithm for a description of the original algorithm). NASA Technical Memorandum 104647 includes information about differences (e.g., tie points) between the original algorithm and the revised NASA Team algorithm. In addition, the NASA Team algorithm uses different channels of the SMMR and the SSM/I-SSMIS brightness temperature data:

Table 11. SMMR and SSM/I-SSMIS Brightness Temperature Channels
Instrument Channels
SMMR
  • Vertically and horizontally polarized (v-pol and h-pol) 18.0 GHz
  • V-pol 37.0 GHz
SSM/I
  • V-pol and h-pol 19.3 GHz
  • V-pol 37.0 GHz
SSMIS
  • V-pol and h-pol 19.3 GHz
  • V-pol 37.0 GHz

The weather filter used for the SMMR (Gloersen and Cavalieri 1986) was found to be inadequate for the SSM/I due to the SSM/I's use of the 19.3 GHz channel (which is further up on the shoulder of the water vapor line at 22.2 GHz) rather than the 18.0 GHz channel. A different weather filter is used to reduce spurious sea ice concentrations from SSM/I that result from the presence of atmospheric water vapor, non-precipitating cloud liquid water, rain, and sea surface roughening by surface winds. This filter is a combination of the SSM/I 37.0 and 19.3 GHz channels, which effectively eliminates most of the spurious sea ice concentration measurements resulting from wind-roughening of the ocean surface, cloud liquid water, and rainfall. Another filter that is based on the 19.3 and 22.2 GHz channels is also used. The rationale behind combining the 19.3 and 22.2 GHz channels is based on the sensitivity of the 22.2 GHz to water vapor and on the need to minimize the effect of ice temperature variations at the ice edge.

Processing Steps

Platform and Sensor Differences

Comparisons of sea ice concentrations calculated for each sensor during overlap periods using published algorithm tie points reveal significant differences. These may result from differences in sensor and orbital characteristics, differences in observation times (and therefore tidal effects), and/or differences in algorithm coefficients. Sensor and orbital characteristic differences for the Nimbus-7 SMMR and DMSP-F8 SSM/I include antenna beam width, channel frequency, spacecraft altitude, ascending node time, and angle of incidence. In addition, the sea ice algorithm tie points are significantly different. The DMSP sensors also differ in ascending node time, altitude, and angle of incidence. Because the visit times of the DMSP satellites occur during different phases of the diurnal cycle, tidal effects may result in differences in the sea ice distribution. GSFC presumes that any such effects are mitigated by the correction scheme described below. The Comparison of Orbital Parameters table in the Source/Platform section summarizes sensor and orbital characteristic differences. The GSFC processing attempts to accommodate for these differences in each pair of sensors by employing a set of algorithm tie points determined through linear relationships between the observed brightness temperatures during the overlap periods.

Nimbus-7 SMMR to DMSP-F8 SSM/I Transition

Daily brightness temperature maps from the Nimbus-7 SMMR and from the DMSP-F8 SSM/I during their period of overlap, 09 July to 20 August 1987, were compared for both the Arctic and Antarctic. Unfortunately, there were only 22 days of common coverage. A linear, least-squares best-fit of the cumulative data was obtained for each of the corresponding channels. For the purpose of eliminating spurious brightness temperatures resulting from residual land spillover effects, an Arctic land mask that expanded three to four pixels out from the original land mask was used in the determination of the best fit between the two data streams.

The eliminated pixels represent only a very small fraction of the total number of sea ice concentration pixels, but eliminating them helps considerably in reducing the outliers on the scatter plots. These linear relations were used to generate a set of SSM/I tie points that are consistent with the original SMMR sea ice algorithm tie points (Gloersen et al. 1992). The published DMSP-F8 SSM/I tie points (Cavalieri et al. 1992) were not used. In addition to using these transformations, the DMSP-F8 SSM/I open water tie points were subjectively tuned to help minimize the differences between the SMMR and DMSP-F8 SSM/I sea ice extent and area during the overlap period. In all cases, except for the Antarctic DMSP-F8 SSM/I values, the tuned amount is within one standard error of estimate. GSFC suspects the reason for the larger tuned values results from greater weather effects during the overlap period.

For more information on the regression coefficients and revised tie points, see the NASA Technical Memorandum 104647.

DMSP-F8 to DMSP-F11 SSM/I Transition

The transition period from DMSP-F8 to -F11 includes only 16 days of good data overlap, from 03 to 18 December 1991. The DMSP-F11 SSM/I open water tie points were also tuned to help reduce differences in sea ice extent and area as was done with the DMSP-F8 SSM/I values. A further adjustment to the Antarctic 37V sea ice type-B F11 tie point was also made to reduce the sea ice area difference. In this case, the amount of tuning needed to reduce the sea ice extent and area differences between the DMSP-F8 and -F11 values is well within one standard error of estimate.

DMSP-F11 to DMSP-F13 SSM/I Transition

The effects of changing from the DMSP-F11 to the -F13 satellite were examined for a 5-month overlap period, from 5 May 1995 through 30 September 1995. Generally, in terms of hemispheric averages of mean ice concentration, the biases introduced by the transition are slight and 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. For more information, please see NSIDC Special Report 5: An Intercomparison of DMSP F11- and F13-derived Sea Ice Products.

DMSP-F13 SSM/I to DMSP-F17 SSMIS Transition

The effects of changing from the DMSP-F13 SSM/I to the -F17 SSMIS were examined for a 12-month overlap period, from 01 January 2007 to 31 December 2007. Differences in sea ice extent and total ice covered area between the two platforms and instruments were found to be statistically significant, though fairly similar when compared with previous intersensor calibrations conducted for this time series (Cavalieri et al., 1999). Earlier intersensor calibrations, however, were limited by relatively short periods of sensor overlap (such as sixteen days) and could thus account for less agreement with this transition (Cavalieri et al. 2011). In addition, earlier agreement may be due to the subjective tuning of some tie-points that was required in past intercalibrations (Cavalieri et al., 1999).

Land Spillover and Residual Weather-Related Effects

The next step in preparing the data is the correction for land-to-ocean spillover (often referred to as "land contamination") and residual weather-related effects. While these steps eliminate much of the land-to-ocean spillover and weather effects over open ocean, these problems are not entirely removed. See the section Data Verification by Data Center for additional comments.

Arctic SMMR Total Ice Concentration NIMBUS-7 Day 213 08/01/83

Figure 2a. Sea ice concentration map
of the Arctic for Day 213, 1983 before
the application of the land spillover
and residual weather corrections.

    Figure 2b. After corrections.

Land-to-Ocean Spillover
Land-to-ocean spillover refers to the problem of blurring sharp contrasts in brightness temperature, such as exist between land and ocean, by the relatively coarse width of the sensor antenna pattern. This problem is of concern because it results in false sea ice signals along coastlines. (Both land and sea ice have much higher brightness temperatures than ocean.) The method used to reduce the spillover is an extension of the method employed for the single-channel Nimbus-5 Electrically Scanning Microwave Radiometer (ESMR) data in Parkinson et al. (1987). The rationale behind the approach is that a minimum observed (generally in late summer) sea ice concentration in the vicinity of coastlines where no sea ice remains offshore is probably the result of land spillover and is thus subtracted from the image. To reduce the error of subtracting sea ice in areas of actual sea ice cover, the technique searches for and requires the presence of open water in the vicinity of the image pixel to be corrected.

Land-to-ocean spillover was reduced by the following three-step procedure:

  1. A matrix M was created covering the entire grid and identifying each pixel as land, shore, near-shore, offshore, or non-coastal ocean. The identification of land pixels was straightforward, obtained from the land/sea mask. The identification of shore, near-shore, and offshore pixels was based on the scheme plotted in Figure 2b, where the pixel to be identified is labeled I,J. This pixel is considered a "shore" pixel if any pixel adjacent to it is land, a "near-shore" pixel if none of the A pixels is land but at least one of the B pixels is land, and an "offshore" pixel if none of the A or B pixels is land but at least one of the C pixels is land. All other ocean pixels are considered "non-coastal ocean". This matrix M is created once and then used throughout the data set.
  2. A matrix CMIN, to represent minimum sea ice concentrations on a pixel-by-pixel basis throughout the entire grid, was created for each instrument type. CMIN was created by first constructing a matrix P containing the minimum monthly average sea ice concentrations throughout a given year, then adjusting that matrix at offshore, near-shore, and shore pixels. In the case of SMMR, 1984 monthly data were used, whereas in the case of SSM/I, 1992 monthly data were used. In both cases, the adjustments were as follows: (a) at offshore pixels, any P values exceeding 20% were reduced to 20%; (b) at near-shore pixels, any P values exceeding 40% were reduced to 40%; and (c) at shore pixels, any P values exceeding 60% were reduced to 60%. The CMIN matrix was created once for SMMR and once for SSM/I, then used throughout the data set.
  3. The daily sea ice concentration matrices were adjusted at any offshore, near-shore, and shore pixels in the vicinity of open water. Specifically, the "neighborhood" of an offshore pixel was defined as containing the 8 other pixels in the 3 x 3 box centered on the offshore pixel; the "neighborhood" of a near-shore pixel was defined as containing the 24 other pixels in the 5 x 5 box centered on the near-shore pixel; and the "neighborhood" of a shore pixel was defined as containing the 48 other pixels in the 7 x 7 box centered on the shore pixel. At any time when the neighborhood of an offshore, near-shore, or shore pixel contains three or more open-water pixels (sea ice concentration less than 15%), then the calculated sea ice concentration at the offshore, near-shore, or shore pixel is reduced by the value for that pixel in the matrix CMIN. Wherever the subtraction leads to negative sea ice concentrations, the concentrations are set to 0%. This land-spillover correction algorithm is clearly a rough approximation, as the contaminated amount does not stay constant over time; but the scheme has been found to reduce substantially the spurious sea ice concentrations on the grids.

Residual Weather-Related Effects
A correction is made for residual weather effects that were missed by the automatic weather filters. This correction is made based on monthly climatological sea surface temperatures (SSTs) from the NOAA Ocean Atlas (Levitus and Boyer 1994). These data, originally on a two-degree by two-degree grid, were remapped onto the SSM/I grid. Because the SST data did not extend to the SSM/I coastline, the data were extrapolated to the coastline once they were mapped onto the SSM/I grid. The SST maps are used as follows:

  • In the Northern Hemisphere, in any pixel where the monthly SST is greater than 278 K, the sea ice concentration is set to zero throughout the month.
  • In the Southern Hemisphere, in any pixel where the monthly SST is greater than 275 K, the sea ice concentration is set to zero throughout the month.
  • The higher threshold SST value was needed in the Northern Hemisphere because the 275 K isotherm used in the south was too close to the sea ice edge in the north. In a few instances, corrections to the regridded SST data were needed, because otherwise actual sea ice was being lost.

Filling Data Gaps

There are instances of missing data. In some cases whole days (or weeks or months) are missing. In other cases, large swaths or wedges of missing data exist within an image, along with scattered pixels of missing data throughout the grid. The scattered pixels of missing data, resulting generally from mapping the orbital data to the SSM/I grid, were filled by applying a spatial linear interpolation scheme on the brightness temperature maps. The larger areas of missing data, resulting from gaps between orbital swaths (generally at low latitudes on daily maps) or from partial coverage or missing days, were filled by temporal interpolation on the sea ice concentration maps. No data at all were available for the period from 02 December 1987 through 12 January 1988. This gap was not filled by temporal linear interpolation; instead it was left as missing data.

Monthly Data Generation

Once daily data have been processed as previously described, monthly data are generated. Monthly averaged sea ice concentration grids are produced from an average of the daily sea ice concentration grids available for each month. Monthly files for both hemispheres are provided for every month beginning October 1978. However, for October 1978, December 1987 and January 1988, the time series was incomplete: only three days of data were available during October 1978 to generate the monthly mean, only two days were available for December 1987, and only 19 days were available for January 1988. Therefore, the monthly means for these months do not represent the "true" monthly means.

In most cases, GSFC used all daily data to compute monthly averaged sea ice concentrations from a particular instrument until the data were no longer available. For example, SMMR data were used to compute monthly sea ice concentrations until the instrument stopped collecting data on 20 August 1987. Beginning 21 August 1987, SSM/I data were used. In 1991, DMSP-F8 SSM/I data were used through December 18; beginning December 19, DMSP-F11 SSM/I data were used.

Note: It is recommended that sea ice extent and area be computed from daily maps of ice concentrations that are then used to compute monthly averages of those parameters. Computations of sea ice extents and sea ice areas should not be made from the monthly-averaged ice concentration maps because that may result in a biased time series.

Error Sources

In January 2013, NSIDC applied corrections to 29 files that showed errors in a previous release of these data. The errors occurred in files from both SMMR (1983 – 1985) and SSM/I (1995 – 1996). NSIDC recommends data users download the corrected files for these dates. Table 12 lists the affected files and the types of errors that were corrected.

Table 12. Description of Corrected Files
Date File Name Type of Correction
1983-07-30 nt_19830730_n07_v01_n.bin Weather correction
1984-07-26 nt_19840726_n07_v01_n.bin Weather correction
1984-07-28 nt_19840728_n07_v01_n.bin Weather correction
1984-07-30 nt_19840730_n07_v01_n.bin Weather correction
1985-07-01 nt_19850701_n07_v01_n.bin Coastal/weather correction
1985-07 nt_198507_n07_v01_n.bin Coastal/weather correction
1987-07-21 nt_19870721_f08_v01_n.bin Weather correction
1987-12-01 nt_19871201_f08_v01_n.bin Ambiguous; not a clear source of error
1987-12-01 nt_19871201_f08_v01_s.bin Ambiguous; not a clear source of error
1995-11-02 nt_19951102_f13_v01_n.bin Ambiguous; not a clear source of error
1995-11-14 nt_19951114_f13_v01_n.bin Ambiguous; not a clear source of error
1995-11 nt_199511_f13_v01_n.bin Ambiguous; not a clear source of error
1995-12-07 nt_19951207_f13_v01_n.bin Land/coastal correction
1996-04-10 nt_19960410_f13_v01_n.bin Land/coastal correction
1996-04-23 nt_19960423_f13_v01_n.bin Land/coastal correction
1996-05-09 nt_19960509_f13_v01_s.bin Land/coastal correction
1996-05 nt_199605_f13_v01_s.bin Land/coastal correction
1996-06-12 nt_19960612_f13_v01_n.bin Land/coastal correction
1996-06-18 nt_19960618_f13_v01_n.bin Land/coastal correction; same pixels as 1996-06-12
1996-06-19 nt_19960619_f13_v01_n.bin Ambiguous; not a clear source of error
1996-06-20 nt_19960620_f13_v01_n.bin Land/coastal correction
1996-06 nt_199606_f13_v01_n.bin Land/coastal correction
1996-10-06 nt_19961006_f13_v01_s.bin Land/coastal correction
1996-10 nt_199610_f13_v01_s.bin Land/coastal correction
1996-11-01 nt_19961101_f13_v01_n.bin Land/coastal correction
1996-11-06 nt_19961106_f13_v01_n.bin Land/coastal correction
1996-11-14 nt_19961114_f13_v01_n.bin Ambiguous; not a clear source of error
1996-12-05 nt_19961205_f13_v01_n.bin Land/coastal correction; same pixels as 1996-06-12
1996-12-23 nt_19961223_f13_v01_n.bin Land/coastal correction; same pixels as 1996-06-12

Version History

Table 13 outlines the processing and algorithm history for this product.

Table 13. Description of Version Changes
Version Date Description
V1 June 2014 The browse images for the entire record have been reprocessed to include a title and simplified color bar; the data were not affected.
V1 January 1996 Original version of data.

5. References and Related Publications

See the following for background information pertaining to the instruments and sensor-level products used to generate this data set. Other references, particularly for sea ice characteristics and algorithm performance, are available in journals from the NSIDC library. Also, see the Selected Bibliography: SSM/I Brightness Temperatures for the Polar Regions.

Background on the Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I Passive Microwave Data Set

Cavalieri et al. (1997)

Background on the SMMR and SSM/I Sensors

NSIDC Brightness Temperature User's Guide (1992), Gloersen and Barath (1977), Gloersen et al. (1992), Hollinger (1989), Hollinger and Lo (1983), Hollinger et al. (1990), Poe and Conway (1990), Svendsen et al. (1983), and Wentz (1991, 1992, 1993).

Raw Sensor Data and Brightness Temperatures

See references above, Abdalati et al. (1995), and Goodberlet (1990).

Sea Ice Physics and Characteristics

Ackley (1979), Ackley et al. (1980), Wadhams et al. (1987), Carsey (1982), Gloersen et al. (1992). Also see the algorithm references below.

Passive Microwave Algorithms for Sea Ice

Gloersen and Cavalieri (1986), Cavalieri et al. (1992), Cavalieri et al. (1984), Cavalieri (1994), Comiso (1983), Comiso (1990), Comiso et al. (1992), Comiso et al. (1984), Emery et al. (1994), Gloersen and Cavalieri (1986), Gloersen et al. (1992), Grenfell and Comiso (1986), Hollinger et al. (1984), Maslanik (1992), Massom (1991), Steffen and Schweiger (1991), Steffen et al. (1992), Svendsen et al. (1983), Swift and Cavalieri (1985), and Swift et al. (1985).

Applications of Passive Microwave-Derived Sea Ice Data

Campbell et al. (1974, 1975a, 1975b, 1976a, 1976b, 1978, 1980a, 1980b, 1981, 1984, 1987), Carsey (1982, 1985), Cavalieri et al. (1983, 1986, 1990, 1991), Cavalieri and Parkinson (1981, 1987), Cavalieri and Martin (1985), Cavalieri and Zwally (1985), Comiso (1986, 1991), Comiso et al. (1992), Comiso and Sullivan (1986), Comiso et al. (1991), Gloersen et al. (1973, 1974a, 1974b, 1975a, 1975b, 1978, 1984, 1989, 1992), Gloersen and Campbell (1988a, 1988b, 1991a, 1991b), Maslanik et al. (1996), Massom (1991), Zwally (1984), Zwally et al. (1976, 1983a, 1983b, 1985), Zwally and Gloersen (1977), and Zwally and Walsh (1987).

Other Algorithm, Format, and Processing Issues

Martino et al. (1995), NCSA (1993), Poe and Conway (1990), and Snyder (1982).

Abdalati, W., K. Steffen, C. Otto, and K. C. Jezek. 1995. Comparison of Brightness Temperatures from SSM/I 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. 1979. Mass Balance Aspects of Weddell Sea Pack Ice. Journal of Glaciology 24(90):391-406.

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, 50 pp.

Campbell, W. J. 1973. NASA Remote Sensing of Sea Ice in AIDJEX. Proceedings of the World Meteorological Organization Technical Conference, Tokyo, Japan, WMO No. 350:55-66.

Campbell, W. J., P. Gloersen, and H. J. Zwally. 1994. Short- and Long-term Temporal Behavior of Polar Sea-Ice Covers from Satellite Passive-Microwave Observations. Geophysical Monograph 85. Editors O. M. Johannessen, R. D. Muench, and J. E. Overland. American Geophysical Union, Washington, D. C.

Campbell, W. J., P. Gloersen, and H. J. Zwally. 1984. Aspects of Arctic Sea Ice Observable by Sequential Passive-Microwave Observations from the Nimbus-5 Satellite, in Arctic Technology and Policy, I. Dyer and C. Chryslers, eds., Hemisphere Publishing, New York, 197-222.

Campbell, W. J., P. Gloersen, and R. O. Ramseier. 1975. Synoptic Ice Dynamics and Atmospheric Circulation During the Bering Sea Experiment. Proceedings of the Final Symposium on the Results of the Joint Soviet-American Expedition, K. Ya. Kondratyev, Yu. I. Rabinovich, and W. Nordberg, eds., Gidrometeoizdat, Leningrad, 196-218. (Republished as USSR/USA Bering Sea Experiment by A. A. Balkema, Rotterdam, 307 pp., 1982.)

Campbell, W. J., P. Gloersen, E. G. Josberger, O. M. Johannessen, P. S. Guest, N. Mognard, R. Shuchman, B. A. Burns, N. Lannelongue, and K. L. Davidson. 1987. Variations of Mesoscale and Large-scale Sea Ice Morphology in the 1984 Marginal Ice Zone Experiment as Observed by Microwave Remote Sensing. Journal of Geophysical Research 92:6805-6824.

Campbell, W. J., P. Gloersen, W. Nordberg, and T. T. Wilheit. 1974. Dynamics and Morphology of Beaufort Sea Ice Determined from Satellite, Aircraft, and Drifting Stations, in Proc. of the Symp. on Approaches to Earth Survey Problems Through Use of Space Techniques, Akademie-Verlag, Berlin, 311-327.

Campbell, W. J., P. Gloersen, R. O. Ramseier, and H. J. Zwally. 1980. Arctic Sea Ice Variations from Time-lapse Microwave Imagery. Boundary-Layer Meteorology 18:99-106.

Campbell, W. J., P. Gloersen, W. J. Webster, T. T. Wilheit, and R. O. Ramseier. 1976. Beaufort Sea Ice Zones as Delineated by Microwave Imagery. Journal of Geophysical Research 81:1103-1110.

Campbell, W. J., R. O. Ramseier, H. J. Zwally, and P. Gloersen. 1981. Structure and Variability of Bering and Okhotsk Sea Ice Cover by Satellite Microwave Imagery, in Energy Resources of the Pacific, M. T. Halbouty, ed., American Association of Petroleum Geologists, Tulsa, Oklahoma, 343-354.

Campbell, W. J., P. Gloersen, H. J. Zwally, R. O. Ramseier, and C. Elachi. 1980. Simultaneous Passive and Active Microwave Observations of Near-shore Beaufort Sea Ice. Journal of Petroleum Technology 21:1105-1112.

Campbell, W. J., R. O. Ramseier, W. F. Weeks, and P. Gloersen. 1976. An Integrated Approach to the Remote Sensing of Floating Ice. Proceedings of the XXVI International Astronautical Congress, Lisbon, Portugal, L. G. Napolitano, ed. 445-487.

Campbell, W. J., J. Wayenberg, J. B. Ramseyer, R. O. Ramseier, M. R. Vant, R. Weaver, A. Redmond, L. Arsenault, P. Gloersen, H. J. Zwally, T. T. Wilheit, T. C. Chang, D. Hall, L. Gray, D. C. Meeks, M. L. Bryan, F. T. Barath, C. Elachi, F. Leberl, and T. Farr. 1978. Microwave Remote Sensing of Sea Ice in the AIDJEX Main Experiment. Boundary-Layer Meteorology 13:309-337.

Campbell, W. J., W. F. Weeks, R. O. Ramseier, and P. Gloersen. 1975. Geophysical Studies of Floating Ice by Remote Sensing. Journal of Glaciology 15:305-328.

Carsey, F. D. 1985. Summer Arctic Sea Ice Character from Satellite Microwave Data. Journal of Geophysical Research 90(C3):5015-5034.

Carsey, F. D. 1982. Arctic Sea Ice Distribution at End of Summer 1973-1976 from Satellite Microwave Data. Journal of Geophysical Research 87:5809-5835.

Cavalieri, D. J. 1994. A Microwave Technique for Mapping Thin Sea Ice. Journal of Geophysical Research 99(C6):12,561-12,572.

Cavalieri, D. J., P. Gloersen, C. l. Parkinson, J. C. Comiso, and H. J. Zwally. 1997. Observed Hemispheric Asymmetry in Global Sea Ice Changes. Science 278(5340): 1104-1106.

Cavalieri, D. J. and S. Martin. 1994. The Contribution of Alaskan, Siberian, and Canadian Coastal Polynyas to the Cold Halocline Layer of the Arctic Ocean. Journal of Geophysical Research 99:18,343-18,362.

Cavalieri, D. J., and S. Martin. 1985. A Passive-microwave Study of Polynyas Along the Antarctic Wilkes Land coast, in Oceanology of the Antarctic Continental Shelf, S. S. Jacobs, ed., Antarctic Research Series, American Geophysical Union, Washington, D. C. vol. 43:227-252.

Cavalieri, D. J., Parkinson, C. L., DiGirolamo, N. and A. Ivanoff. 2011. Intersensor Calibration between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records. Geoscience and Remote Sensing Letters, in press.

Cavalieri, D. J., C. l. Parkinson, P. Gloersen, J. C. Comiso, and H. J. Zwally. 1999. Deriving Long-term Time Series of Sea Ice Cover from Satellite Passive-Microwave Multisensor Data Sets. Journal of Geophysical Research 104(7): 15,803-15,814.

Cavalieri, D. J., and C. L. Parkinson. 1987. On the Relationship Between Atmospheric Circulation and the Fluctuations in the Sea Ice Extents of the Bering and Okhotsk Seas. Journal of Geophysical Research 92: 7141-7162.

Cavalieri, D. J., and C. l. Parkinson. 1981. Large-scale Variations in Observed Antarctic Sea Ice Extent and Associated Atmospheric Circulation. Monthly Weather Review 109(11):2323-2336.

Cavalieri, D. J., and H. J. Zwally. 1985. Satellite Observations of Sea Ice. Advanced Space Research 5:247-255.

Cavalieri, D. J., B. a. Burns, and R. G. Onstott. 1990. Investigation of the Effects of Summer Melt on the Calculation of Sea Ice Concentration Using Active and Passive-microwave Data. Journal of Geophysical Research 95:5359-5369.

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.

Cavalieri, D. J., P. Gloersen, and T. T. Wilheit. 1986. Aircraft and Satellite Passive-microwave Observations of the Bering Sea Ice Cover During MIZEX West. IEEE Transactions on Geosciences and Remote Sensing GE-24: 368-377.

Cavalieri, D. J., S. Martin, and P. Gloersen. 1983. Nimbus-7 SMMR Observations of the Bering Sea Ice Cover During March 1979. Journal of Geophysical Research 88:2743-2754.

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. Drinkwater, W. J. Emery, D. T. Eppler, L. D. Farmer, M. Goodberlet, R. Jentz, A. Milman, C. Morris, R. Onstott, A. Schweiger, R. Shuchman, K. Steffen, C. T. Swift, C. Wackerman, and R. L. Weaver. 1992. NASA Sea Ice Validation Program for the DMSP SSM/I: Final Report. NASA Technical Memorandum 104559. National Aeronautics and Space Administration, Washington, D. C. 126 pages.

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., C. l. Parkinson, P. Gloersen, and H. J. Zwally. 1997. Arctic and Antarctic Sea Ice Concentrations from Multichannel Passive-microwave Satellite Data Sets: October 1978 to December 1996, User's Guide. NASA Technical Memorandum 104647. 17 pages.

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. 1986. Characteristics of Arctic Winter Sea Ice from Satellite Multispectral Microwave Observations. Journal of Geophysical Research 91(C1): 975-994.

Comiso, J. C. 1983. Sea Ice Effective Microwave Emissivities from Satellite Passive Microwave and Infrared Observations. Journal of Geophysical Research 88(C12):7686-7704.

Comiso, J. C., and A. L. Gordon. 1987. Recurring Polynyas over the Cosmonaut Sea and the Maud Rise. Journal of Geophysical Research 92:2819-2833.

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., and H. J. Zwally. 1989. Polar Microwave Brightness Temperatures from Nimbus-7 SMMR, NASA RP-1223, 82 pages.

Comiso, J. C., and H. J. Zwally. 1984. Concentration Gradients and Growth/Decay Characteristics of the Seasonal Sea Ice Cover. Journal of Geophysical Research 89:8081-8103.

Comiso, J. C., and H. J. Zwally. 1982. Antarctic Sea Ice Concentrations Inferred from Nimbus-5 ESMR and Landsat Imagery. Journal of Geophysical Research 87:5836-5844.

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.

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., 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., and K. Steffen. 2001. Studies of Antarctic Sea Ice Concentrations from Satellite Data and their Applications. Journal of Geophysical Research 106(12): 31,361-31,385.

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.

Emery, W. J., C. Fowler, J. A. Maslanik. 1994. Arctic Sea Ice Concentrations from SSM/I and AVHRR Satellite Data. Journal of Geophysical Research 99(C9):18,329-18,342.

Eppler, D. T., L. D. Farmer, A. W. Lohanick, M. A. Anderson, D. J. Cavalieri, J. C. Comiso, P. Gloersen, C. Garrity, T. C. Grenfell, M. Hallikainen, J. A. Maslanik, C. Matzler, R. A. Melloh, I. Rubenstein, C. T. Swift. 1992. Passive Microwave Signatures of Sea Ice. In Microwave Remote Sensing of Sea Ice, ed. F. Carsey, Geophysical Monograph 68 (AGU).

Gloersen, P. 1995. Modulation of Hemispheric Sea Ice Covers by ENSO Events. Nature 373:503-508.

Gloersen, P. 1983. Calibration of the Nimbus-7 SMMR: II Polarization Mixing Corrections. NASA Technical Memorandum 84976.

Gloersen, P. and F. T. Barath. 1977. A Scanning Multichannel Microwave Radiometer for Nimbus G and Seasat A. IEEE Journal of Oceanic EngineeringOE-2:172-178.

Gloersen, P., and W. J. Campbell. 1991a. Variations of Extent, Area, and Open Water of the Polar Sea Ice Covers: 1978-1987, Proc. of the Int. Conf. on the Role of the Polar Regions in Global Change, G. Weller, C. L. Wilson, and B. A. B. Severin, eds., Geophysical Institute, University of Fairbanks, Alaska. 778 pages.

Gloersen, P., and W. J. Campbell. 1991b. Recent Variations in Arctic and Antarctic Sea Ice Covers. Nature 352:33-36.

Gloersen, P., and W. J. Campbell. 1988a. Variations in the Arctic, Antarctic, and Global Sea Ice Covers During 1978-1987 as Observed with the Nimbus-7 Scanning Multichannel Microwave Radiometer. Journal of Geophysical Research 93:10,666-10,674.

Gloersen, P. and W. J. Campbell. 1988b. Satellite and Aircraft Passive-microwave Observations During the Marginal Ice Zone Experiment in 1984. Journal of Geophysical Research 93:6837-6846.

Gloersen P. and D. J. Cavalieri. 1986. Reduction of Weather Effects in the Calculation of Sea Ice Concentration from Microwave Radiances. Journal of Geophysical Research 91(C3):3913-3919.

Gloersen, P, and A. Mernicky. 1997. Oscillatory Behavior in Antarctic Sea Ice Concentrations. In AGU Antarctic Research Series: Antarctic Sea Ice Physical Properties and Processes. Editor M. O. Jeffries. In press.

Gloersen, P., E. Mollo-Christensen, and P. Hubanks. 1989. Observations of Arctic Polar Lows with the Nimbus-7 Scanning Multichannel Microwave Radiometer, in Polar and Arctic Lows, P. F. Twitchell, E. A. Rasmussen, and K. L. Davidson, eds., A. Deepak, Hampton, Virginia, 359-371.

Gloersen, P., C. l. Parkinson, D. J. Cavalieri, J. C. Comiso, and H. J. Zwally. 1999. Spatial Distribution of Trends and Seasonality in the Hemispheric Sea Ice Covers: 1978-1996. Journal of Geophysical Research 104(9): 20,827-20,835.

Gloersen, P., J. Yu, and E. Mollo-Christensen. 1996. Oscillatory Behavior in Arctic Sea Ice Concentrations. Journal of Geophysical Research 101:6641-6650.

Gloersen, P., W. J. Campbell, D. J. Cavalieri, J. C. Comiso, C. l. Parkinson, and H. J. Zwally. 1993. Satellite Passive Microwave Observations and Analysis of Arctic and Antarctic Sea Ice, 1978-1987. Annals of Glaciology 17:149-154.

Gloersen P., W. J. Campbell, D. J. Cavalieri, J. C. Comiso, C. L. Parkinson, H. J. Zwally. 1992. Arctic and Antarctic Sea Ice, 1978-1987: Satellite Passive Microwave Observations and Analysis. NASA Special Publication 511.

Gloersen, P., D. J. Cavalieri, A. T. C. Chang, T. T. Wilheit, W. J. Campbell, O. M. Johannessen, K. B. Katsaros, K. F. Kunzi, D. B. Ross, D. Staelin, E. P. L. Windsor, F. T. Barath, P. Gudmandsen, E. Langham, and R. O. Ramseier. 1984. A Summary of Results from the first Nimbus-7 SMMR Observations. Journal of Geophysical Research 89:5335-5344.

Gloersen, P., T. C. Chang, T. T. Wilheit, and W. J. Campbell. 1974. Polar Sea Ice Observations by Means of Microwave Radiometry, in Advanced Concepts and Techniques in the Study of Snow and Ice, H. S. Santeford and J. L. Smith, eds., National Academy of Science 541-550.

Gloersen, P., W. Nordberg, T. J. Schmugge, T. T. Wilheit, and W. J. Campbell. 1973. Microwave Signatures of First-year and Multiyear Sea Ice. Journal of Geophysical Research 78:3564-3572.

Gloersen, P., R. O. Ramseier, W. J. Campbell, T. C. Chang, and T. T. Wilheit. 1975. Variations of Ice Morphology of Selected Mesoscale Test Areas During the Bering Sea Experiment, in Proceedings of the Final Symposium on the Results of the Joint Soviet-American Expedition, K. Ya. Kondratyev, Yu. I. Rabinovich, and W. Nordberg, eds., Gidrometeoizdat, Leningrad, 196-218. (Republished as USSR/USA Bering Sea Experiment by A. A. Balkema, Rotterdam, 307 pages. 1982.)

Gloersen, P., R. Ramseier, W. J. Campbell, P. M. Kuhn, and W. J. Webster, Jr. 1975. Ice Thickness Distribution as Inferred from Infrared and Microwave Remote Sensing During the Bering Sea Experiment, in Proceedings of the Final Symposium on the Results of the Joint Soviet-American Expedition, K. Ya. Kondratyev, Yu. I. Rabinovich, and W. Nordberg, eds., Gidrometeoizdat, Leningrad, 282-293. (Republished as USSR/USA Bering Sea Experiment by A. A. Balkema, Rotterdam, 307 pages. 1982.)

Gloersen, P., T. T. Wilheit, T. C. Chang, W. Nordberg, and W. J. Campbell. 1974. Microwave Maps of the Polar Ice of the Earth. Bulletin of the American Meteorological Society 55:1442-1448.

Gloersen, P., H. J. Zwally, A. T. C. Chang, D. K. Hall, W. J. Campbell, and R. O. Ramseier. 1978. Time-dependence of Sea Ice Concentration and Multiyear Ice Fraction in the Arctic Basin. Boundary-Layer Meteorology 13:339-359.

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. 1989. DMSP Special Sensor Microwave/Imager Calibration/Validation. Naval Research Laboratory, Washington, D. C.

Hollinger, J. P. and R. C. Lo. 1983. SSM/I Project Summary Report. Naval Research Laboratory. NRL Memorandum Report 5055. 106 pages.

Hollinger, J. P., J. L. Pierce, and 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.

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).

Johannessen, O. M., W. J. Campbell, R. Shuchman, S. Sandven, P. Gloersen, E. G. Jospberger, J. A. Johannessen, and P. M. Haugan. 1992. Microwave Study Programs of Air-Ice-Ocean Interactive Processes in the Seasonal Ice Zone of the Greenland and Barents Seas. In Microwave Remote Sensing of Sea Ice, ed. F. Carsey. Geophysical Monograph 68 (AGU).

Josberger, E. G., W. J. Campbell, P. Gloersen, A. T. C. Chang, and A. Rango. 1993. A Hydrology of the Upper Colorado River Basin Derived from Satellite Passive-microwave Observation. Annals of Glaciology 17:322-331.

Josberger, E. G., P. Gloersen, A. T. C. Chang, A. Rango. 1996. The Effects of Snowpack Grain Size on the Passive Microwave Signatures from the Upper Colorado River Basin Snowpack. Journal of Geophysical Research 101:6679-6688.

Levitus, S. and Boyer, T. P. 1994. World Ocean Atlas 1994, Volume 4: Temperature, NOAA National Oceanographic Data Center, Ocean Climate Laboratory, U.S. Department of Commerce, Washington D. C.

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.

Maslanik, J. A., M. C. Serreze, and R. G. Barry. 1996. Recent Decreases in Arctic Summer Sea Ice Cover and Linkages to Atmospheric Circulation Anomalies. Geophysical Research Letters 23(13):1677-1680.

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. page 44.

Parkinson, C. l. 1995. Recent Sea-Ice Advances in Baffin Bay/Davis Strait and Retreats in the Bellingshausen Sea. Annals of Glaciology 21:348-352.

Parkinson, C. l. 1994. Spatial Patterns of Increases and Decreases in the Length of the Sea Ice Season in the Southern Ocean, 1979-1986. Journal of Geophysical Research 99:16,327-16,339.

Parkinson, C. l. 1992a. Spatial Patterns of Increases and Decreases in the Length of the Sea Ice Season in the North Polar Region, 1979-1986. Journal of Geophysical Research 97:14,377-14,388.

Parkinson, C. l. 1992b. Interannual Variability of Monthly Southern Ocean Sea Ice Distributions. Journal of Geophysical Research 97:5349-5363.

Parkinson, C. l. 1991. Interannual Variability of the Spatial Distribution of Sea Ice in the North Polar Region. Journal of Geophysical Research 96:4791-4801.

Parkinson, C. l. 1990. The Impact of the Siberian High and Aleutian Low on the Sea Ice Cover of the Sea of Okhotsk. Annals of Glaciology 14:226-229.

Parkinson, C. l. 1983. On the Development and Cause of the Weddell Polynya in a Sea Ice Simulation. Journal of Physical Oceanography 13:501-511.

Parkinson, C. l., and R. A. Bindschadler. 1984. Response of Antarctic Sea Ice to Uniform Atmospheric Temperature Increases, in Climate Processes and Climate Sensitivity, J. E. Hansen and T. Takahashi, eds., Maurice Ewing Series, Vol. 5, American Geophysical Union, Washington, D. C., pp. 254-264.

Parkinson, C. L., and D. J. Cavalieri. 2002. A 21-year Record of Arctic Sea-Ice Extents and their Regional, Seasonal, and Monthly Variability and Trends. Annals of Glaciology 34: 441-446.

Parkinson, C. L., D. J. Cavalieri, P. Gloersen, H. J. Zwally, and C. Comiso. 1999. Arctic Sea Ice Extents, Areas, and Trends, 1978-1996. Journal of Geophysical Research 104(9): 20,837-20,856.

Parkinson, C. l., and D. J. Cavalieri. 1989. Arctic Sea Ice, 1973-1987: Seasonal, Regional, and Interannual Variability. Journal of Geophysical Research 94:14,499-14,523.

Parkinson, C. l., and D. J. Cavalieri. 1982. Interannual Sea Ice Variations and Sea Ice/Atmosphere Interactions in the Southern Ocean, 1973-1975. Annals of Glaciology 3:249-254.

Parkinson, C. l., and P. Gloersen. 1993. Global Sea Ice Coverage. In Atlas of Satellite Observations Relate to Global Change. Editors R. Gurney, J. Foster, and C. Parkinson. Cambridge University Press.

Parkinson, C. l., and A. J. Gratz. 1983. On the Seasonal Sea Ice Cover of the Sea of Okhotsk. Journal of Geophysical Research 88:2793-2802.

Parkinson, C. l., J. C. Comiso, H. J. Zwally, D. J. Cavalieri, P. Gloersen, and W. J. Campbell. 1987. Arctic Sea Ice, 1973-1976: Satellite Passive-Microwave Observations, NASA SP-489, National Aeronautics and Space Administration, Washington, D. C. 296 pages.

Pearson, F. 1990. Map Projections: Theory and Applications. CRC Press. Boca Raton, Florida. 372 pages.

Poe, G. A. and R. W. Conway. 1990. A Study of the Geolocation Errors for the Special Sensor Microwave/Imager (SSM/I). IEEE Transactions on Geoscience and Remote Sensing 28(5):791-799.

Rothrock, D. A., D. R. Thomas, and A. S. Thorndike. 1988. Principal Component Analysis of Satellite Passive-microwave Data over Sea Ice. Journal of Geophysical Research 93:2321-2332.

Shuchman, R. A., B. Burns, O. M. Johannessen, E. G. Josberger, W. J. Campbell, T. Manley, and N. Lannelongue. 1987. Remote Sensing of the Fram Strait Marginal Ice Zone. Science 236:429-431.

Shuchman, R. A., W. J. Campbell, B. Burns, E. Ellingsen, B. Farrelly, P. Gloersen, T. Grenfell, J. Hollinger, D. Horn, J. Johannessen, O. Johannessen, E. Josberger, C. Livingstone, C. Luther, T. Manley, R. Markson, C. Mätzler, E. Mollo-Christensen, R. Onstott, D. Ross, S. Sandven, C. Schgoun, A. Stiffey, E. Svendsen, G. Simmonds, and Z. Top. 1984. Remote Sensing of the Marginal Ice Zone Experiment, in Proceedings of the IGARSS'84 Symposium, Strasbourg, France, European Space Agency, ESA SP-215, 404-409.

Snyder, J. P. 1987. Map Projections - A Working Manual. U.S. Geological Survey Professional Paper 1395. U.S. Government Printing Office. Washington, D. C. 383 pages.

Snyder, J. P. 1982. Map Projections Used by the U.S. Geological Survey. U.S. Geological Survey Bulletin 1532.

Steffen, K. and A. Schwieger. 1991. NASA Team Algorithm for Sea Ice Concentration Retrieval from Defense Meteorological Satellite Program Special Sensor Microwave/Imager: Comparison with Landsat satellite imagery. Journal of Geophysical Research 96(C12):21,971-21,988.

Steffen, K., D. J. Cavalieri, J. C. Comiso, K. St. Germain, P. Gloersen, J. Key, and I. Rubinstein. 1992. The Estimation of Geophysical Parameters Using Passive Microwave Algorithms. Chapt 10 In Microwave remote sensing of sea ice. Frank Carsey, editor. American Geophysical Union. Washington, D. C. 243-259.

Sullivan, C. W., C. R. McClain, J. C. Comiso, and W. O. Smith, Jr. 1988. Phytoplankton Standing Crops within an Antarctic Ice Edge Assessed by Satellite Remote Sensing. Journal of Geophysical Research 93:12,487-12,498.

Svendsen, E., K. Kloster, B. Farrelly, O. M. Johannessen, J. A. Johannessen, W. J. Campbell, P. Gloersen, D. Cavalieri, and C. Matzler. 1983. Norwegian Remote Sensing Experiment: Evaluation of the Nimbus-7 Scanning Multichannel Microwave Radiometer for Sea Ice Research. Journal of Geophysical Research 88(C5):2781-2791.

Swift, C. T. 1980. Passive-microwave Remote Sensing of Ocean-A Review. Boundary-Layer Meteorology 18:25-54.

Swift, C. T., D. J. Cavalieri. 1985. Passive Microwave Remote Sensing for Sea Ice Research. EOS 66(49):1210-1212.

Swift, C. T., Fedor, L. S. and Ramseier, R. O. 1985. An Algorithm to Measure Sea Ice Concentration with Microwave Radiometers. Journal of Geophysical Research 90(C1):1087-1099.

Wadhams, P., M. A. Lange, and S. F. Ackley. 1987. The Ice Thickness Distribution across the Atlantic Sector of the Antarctic Ocean in Midwinter. Journal of Geophysical Research 92(C13):14,535-14, 552.

Walsh, J. E., and C. M. Johnson. 1979. Interannual Atmospheric Variability and Associated Fluctuations in Arctic Sea Ice Extent. Journal of Geophysical Research 84:6915-6928.

Walsh, J. E., and H. J. Zwally. 1990. Multiyear Sea Ice in the Arctic: Model- and Satellite-derived. Journal of Geophysical Research 95:11,613-11,628.

Wentz, F. J. 1993. User's Manual: SSM/I Antenna Temperature Tapes: Rev. 2. Remote Sensing Systems, Inc. Santa Rosa, CA. RSS Technical Report 120193.

Wentz, F. J. 1992. Final Report, Production of SSM/I Data Sets. Remote Sensing Systems, Inc., Santa Rosa, CA. RSS Technical Report 090192.

Wentz, F. J. 1991. User's Manual: SSM/I Antenna Temperature Tapes. Remote Sensing Systems, Inc., Santa Rosa, CA. RSS Technical Report 032588.

Zwally, H. J. 1984. Observing Polar-ice Variability. Annals of Glaciology 5:191-198.

Zwally, H. J., and P. Gloersen. 1993. Variability of the Arctic Perennial Ice Pack. In Proceedings of the International Symposium on ISY Polar Ice Extent, February 1993. Editor F. Nishio. 127-132. National Space Development Agency, Mombetsu, Japan.

Zwally, H. J., and P. Gloersen. 1977. Passive-microwave Images of the Polar Regions and Research Applications. Polar Records 18:431-450.

Zwally, H. J., and J. E. Walsh. 1987. Comparison of Observed and Modeled Ice Motion in the Arctic Ocean. Annals of Glaciology 9:136-144.

Zwally, H. J., J. C. Comiso, and A. l. Gordon. 1985. Antarctic Offshore Open Water within the Pack and Oceanographic Effects, in Oceanology of the Antarctic Continental Shelf, S. S. Jacobs, ed., Antarctic Research Series vol. 43, American Geophysical Union, Washington, D. C. 203-226.

Zwally, H. J., C. l. Parkinson, and J. C. Comiso. 1983. Variability of Antarctic Sea Ice and Changes in Carbon Dioxide. Science 220:1005-1012.

Zwally, H. J., J. C. Comiso, C. l. Parkinson, W. J. Campbell, F. D. Carsey, and P. Gloersen. 1983. Antarctic Sea Ice, 1973-1976: Satellite Passive-microwave Observations, NASA SP-459, National Aeronautics and Space Administration, Washington, D. C. 206 pages.

Zwally, H. J., T. T. Wilheit, P. Gloersen, and J. l. Mueller. 1976. Characteristics of Antarctic Sea Ice as Determined by Satellite-borne Microwave Imagers, in Proceedings of the Symposium on Meteorological Observations from Space: Their Contribution to the First GARP Global Experiment, Committee on Space Research of the International Council of Scientific Unions, Philadelphia, 94-97.

Related Data Collections

5. Contacts and Acknowledgments

Investigator(s) Name and Title

Donald J. Cavalieri, Claire L. Parkinson, Per Gloersen, and H. Jay Zwally
NASA Goddard Space Flight Center (GSFC)
Greenbelt, Maryland USA

Walt Meier, Florence Fetterer, Ken Knowles, Matt Savoie, Mary Jo Brodzik
National Snow and Ice Data Center (NSIDC)
Boulder, Colorado USA

Technical Contact

NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449 USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
e-mail: nsidc@nsidc.org

6. Document Information

Acronyms and Abbreviations

The acronyms used in this document are listed in Table 14.

Table 14. Acronyms and Abbreviations
Acronym Description
ANSI American National Standards Institute
ASCII American Standard Code for Information Interchange
CIRES Cooperative Institute for Research in Environmental Sciences
DMSP Defense Meteorological Satellite Program
DOS Disk Operating System
ESMR Electrically Scanning Microwave Radiometer
FNMOC Fleet Numerical Meteorology and Oceanography Center
FTP File Transfer Protocol
GIF Graphical Interchange Format
GSFC Goddard Space Flight Center
H-pol Horizontally polarized
IDL Interactive Data Language
NASA National Aeronautics and Space Administration
NEMS Nimbus-E Microwave Spectrometer
NOAA National Oceanic and Atmospheric Administration
NSIDC National Snow and Ice Data Center
PNG Portable Network Graphics
RSS Remote Sensing Systems, Inc.
SCAMS Scanning Microwave Spectrometer
SMMR Scanning Multichannel Microwave Radiometer
SSM/I Special Sensor Microwave/Imager
SST Sea surface temperature
URL Uniform Resource Locator
V-pol Vertically polarized

Document Creation Date

January 1996

Document Revision Date

June 2014
October 2011
March 2011
April 2008
October 2006

Document URL

http://nsidc.org/data/docs/daac/nsidc0051_gsfc_seaice.gd.html