Data Description

This sea ice concentration data set was derived using measurements from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite and from the Special Sensor Microwave/Imager (SSM/I) sensors on the Defense Meteorological Satellite Program's (DMSP) -F8, -F11, and -F13 satellites. Measurements from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17 are also included. The data set has been generated using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Bootstrap Algorithm with daily varying tie-points. Daily (every other day prior to July 1987) and monthly data are available for both the north and south polar regions. Data are gridded on the SSM/I polar stereographic grid (25 x 25 km) and provided in two-byte integer format.

Parameters

The data set consists of sea ice concentration derived from gridded brightness temperatures. Sea ice concentrations range from 0 to 100 percent. 

Data are stored as two-byte integers representing sea ice concentration values. The sea ice concentration data values are packed into integer format by multiplying the original sea ice concentration values by 10 (divide stored value by 10 to get the percent). The sea ice concentration values range from 0 to 1000. Land is registered as 1200 and the Northern Hemisphere hole (a region of the North Pole that is not measured due to orbit inclination) is registered as 1100. Refer to the Spatial Coverage section of this document.

File Information

Format

Data files are stored in the original Goddard Space Flight Center (GSFC) flat binary two-byte integer format, use the little-endian byte order convention, and are scaled by a factor of 10. An individual image of daily or monthly averaged data constitutes a granule in the Bootstrap sea ice concentration time series.

File Contents

The following is a sample data record from the Northern Hemisphere monthly data.

 837  887  924 971  971 992 980 975 974 964 980 965 936 972 968 986
 982  987  978 984  988 965 980 972 981 985 992 988 989 983 993 986
 985  984  982 983  982 981 974 990 982 983 978 977 983 987 981 992
 985  979  978 982  981 969 966 972 977 984 973 976 980 970 972 977
 980  984  980 982  977 973 973 969 968 972 980 951 887 877 928 936
1200 1200 1200 969 1200 951 956 980 980 980 975 982 982 961 937 863
 791  710  706 706  678

Directory Structure

Data are available via HTTPS, the link for which can be found on the "Download Data" tab. Within the file directory, data are sorted by date. 

File Naming Convention

Daily data files are named according to the following convention and as described in Table 1.

bt_YYYYMMDD_SSS_vV.V_H.bin

Example: bt_20060901_f13_v3.1_n.bin

Monthly data files are named according to the following convention and as described in Table 2.

bt_YYYYMM_SSS_vV.V_H.bin

Example File Name: bt_200609_f13_v3.1_n.bin

File Size

Northern Hemisphere files are approximately 266 KB. Southern Hemisphere files are approximately 205 KB.

Spatial Information

Coverage

Data set coverage includes the northern and southern polar regions. For a detailed description, see the SSM/I Polar Spatial Coverage Maps section of the Polar Stereographic Projections and Grids website.

SSM/I and SSMIS instrument coverage is global, except for circular sectors centered over the North Pole, 311 km in radius, located poleward of 87.2°. 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. For more details, please refer to the SMMR, SSM/I, and SSMIS Sensors page. The measurement footprint size or effective field of view (FOV) varies by frequency, as shown in the following table.

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. For more details, please refer to the SMMR, SSM/I, and SSMIS Sensors page. The measurement footprint size varies by frequency, as shown in the following table.

Resolution

Sea ice concentrations are provided at a resolution of 25 km.

Projection and Grid Description

For more information, see Polar Stereographic Projections and Grids. The grid size varies depending on the region, as shown in the following table.

Temporal Information

Coverage

Bootstrap sea ice concentration data are available for 26 October 1978 through 31 December 2018.

Resolution

SMMR data were collected every other day. (The scanner operated only on alternate days, due to spacecraft power limitations). Major data gaps occurred in August 1982 (4, 8, and 16 August) and 1984 (13 through 23 August) for both polar regions. Monthly means are generated by averaging all available files for each individual month, excluding pixels of missing data. Data were interpolated where missing pixels were present so that no areas of missing data remained.

SSM/I and SSMIS data are collected daily. Ice concentrations are provided for each day of data and as monthly means. Monthly mean files are generated by averaging all available daily files for each individual month, excluding pixels of missing data. A major data gap in the SSM/I data occurs from 03 December 1987 to 13 January 1988.

Data Acquisition and Processing

Background

The SMMR and SSM/I instruments are dual-polarized and multi-frequency microwave radiometers that sense emitted microwave radiation at an incidence angle of about 53° and an altitude of about 800 km. At microwave frequencies, the observed radiance varies linearly with the temperature of the emitting material, according to the Rayleigh-Jeans law, and is usually expressed in terms of brightness temperature. The constant of proportionality in the linear relationship is the emissivity, which provides information about the electrical and physical properties of the material itself. The observed brightness temperatures come primarily from the Earth's surface with some contributions from the atmosphere and outer space. Depending on frequency and polarization, the brightness temperature is affected by changing surface, subsurface, and atmospheric conditions. The multichannel capability allows for the discrimination of different surfaces and atmospheric effects and allows for the development of algorithms that provide a range of geophysical information about the surface.

Acquisition

Four sets of satellite data are used to create the Bootstrap sea ice data stream:

• Nimbus-7 SMMR, data range: 01 November 1978 through 31 July 1987
• DMSP-F08 SSM/I, data range: 01 August 1987 through 17 December 1991
• DMSP-F11 SSM/I, data range: 18 December 1991 through 09 May 1995
• DMSP-F13 SSM/I, data range: 10 May 1995 through 31 December 2007
• DMSP-F17 SSMIS, data range: 01 January 2008 through the most current processing

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

Bootstrap sea ice concentrations were processed at GSFC using DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures from NSIDC. Processing of DMSP-F17 brightness temperatures is ongoing. For more information on the brightness temperatures, see the DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures documentation.

Processing

Sea ice concentrations for this data set were derived from a revised Bootstrap algorithm which uses a different set of tie-points and adjustments. For algorithm background, please see the Enhanced Sea Ice Concentrations from Passive Microwave Data document (Comiso and Nishio 2008). For changes made to this Version 3 data set, see the Positive Trend in the Antarctic Sea Ice Cover and Associated Changes in Surface Temperature document (Comiso, et al. 2017).

Interpolation

Data were interpolated in areas with missing pixels according to the following steps. First, data were spatially interpolated only for isolated empty pixels. An empty pixel was replaced by the average of four good surrounding pixels, or if four good pixels were not available, then a smaller number of pixels was selected. Second, a time interpolation was applied to the spatially interpolated map. Time interpolation was based on a weighting scheme; the closer the good data were in time, the higher the weighted value. For each empty pixel, the algorithm searched forward in time for a good pixel, and backward in time for a second good pixel. The algorithm determined how many days ahead and behind the two good pixels occurred and calculated the weight of each pixel. A weighted average of the two good pixels was then calculated, and the result was used for the empty pixel. During the SSM/I period, most temporal interpolations were conducted using only adjacent days. During the SMMR period, particularly in 1986 when larger gaps were present, temporal interpolations had separations of more days.

Quality, Errors, and Limitations

Assessment of Version Differences

For Version 3.1 data, the differences in total Arctic sea ice area and sea ice extent are usually small (less than ± 0.5%), except in the second half of May when daily sea ice areas are often 0.5-1.5% higher and extents are 1-3% higher in V3.1 than in V3.0.

The staff at the NSIDC DAAC performed an evaluation between Version 2 and Version 3 data to verify any difference between the two versions. Here are their findings:

• The changes introduced in Version 3 have some effect on the total ice covered area and extent.  These differences have some seasonality and appear to be largely due to the use of dynamic open water tie points.
• The majority of pixels show no change in concentration value or less than one percent, although a small fraction have larger differences.  Roughly two percent of pixels show concentration changes of more than 10 percent.

Although most bad data are easily identifiable and removed with little ambiguity, human judgments must be made and applied consistently to the time series data. While efforts were made to minimize errors in judgment and inconsistencies, the resulting data set is not perfect. Nevertheless, the data provider feels that these maps are suitable for some types of research studies, such as basin-scale trend analysis, model inputs, and some regional studies. They are less useful in evaluating conditions on a specific day in a localized region.

NSIDC staff visually checked the entire set of data files, including file structure, comparisons to existing SMMR- and SSM/I-derived sea ice concentration grids, and information files and examination of data quality.

Errors and Limitations

Sensitivity analysis of potential errors associated with the retrieval of sea ice products were discussed previously. For example, see Comiso et al. 1997 and other references associated with the NASA Team Algorithm sea ice products. Sea ice concentration errors are difficult to quantify because sea ice is an evolving ice cover and does not have uniform physical and radiative characteristics throughout the ice pack. The emissivity of sea ice is known to change as the ice cover develops from grease ice to nilas, pancake to young ice, or first year ice to multiyear ice. For definitions of these types of ice, see the NSIDC glossary page. The line AD in the scatter plot that provides the sea ice tie-point in the Bootstrap Algorithm corresponds to 100 percent ice for the relatively thick ice types such as first year or multiyear ice. Areas with 100 percent of thinner ice types are often estimated to have ice concentrations as low as 80 percent due to lower emissivities (Comiso et al. 1992). In the summer, retrievals in the Arctic could have biases caused by meltponding effects (Comiso and Kwok 1996).

Inside the ice pack, observations from helicopter and aircraft flights typically show very high sea ice concentrations with some 5 to 10 percent of the leads covered by nilas or pancake ice. The frequency distribution of sea ice concentration in highly consolidated ice areas has a standard deviation of about 3 percent, which includes sea ice cover with concentrations of less than 100 percent. Overall, retrieval accuracy is estimated to be approximately 5 to 10 percent except in some unusual cases, such as the presence of a large fraction of thin ice or meltponding within the pixel and the presence of stormy weather conditions, especially near the ice edge. Limited comparative analysis with high resolution instruments and other measurements confirm this, but more extensive validation in a greater number of places over all of the seasons would provide more accurate error assessments.

For information describing the rough error/differences between each sensor (F8, F11, F13, F17) during the sensor overlap time period, refer to the following documentation: Comiso et al. 2008, Comiso et al. 2009, and Comiso et al. 2010.

Basic limitations arise from the sensor resolution, temporal coverage, and algorithm assumptions and characteristics. Users should review the information provided on fields of view, temporal sampling, and algorithm characteristics.

Particular care is needed in interpreting the sea ice concentrations during summer when melt is underway and in regions where new sea ice makes up a substantial part of the sea ice cover. As noted, some residual errors remain due to sensor differences and to weather effects along with mixing of ocean and land area within the sensor field of view.

No data coverage is available for regions poleward of 84.5° N for SMMR and 87.2° N for SSM/I or SSMIS due to the inclination of the orbits. SMMR data were acquired every other day, while SSM/I data were acquired daily. SSMIS data are also acquired daily.

Instrumentation

Description

Please refer to the SMMR, SSM/I, and SSMIS Sensors page for details regarding the following sensors and platforms: 

Sensors

Scanning Multi-channel Microwave Radiometer (SMMR)
Special Sensor Microwave Imager (SSM/I)
Special Sensor Microwave Imager (SSMIS)

Platforms

Nimbus 7 Spacecraft System
Defense Meteorological Satellite Program (DMSP) Satellite F8
Defense Meteorological Satellite Program (DMSP) Satellite F11
Defense Meteorological Satellite Program (DMSP) Satellite F13

Software and Tools

Fortran tools are provided which extract the sea ice concentration files and geolocate the data. Sample Fortran code is provided for reading and displaying these sea ice concentration data.

Sample Interactive Data Language (IDL) commands to read and display sea ice grids and latitude/longitude grids are provided via the IDL commands text file. In addition, IDL 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, are provided.

Table 6 lists the tools that can be used with this data set. For a comprehensive list of all polar stereographic tools, see the Polar Stereographic Data Tools web page.

Version History

Table 7 outlines the processing and algorithm history for this product.

Related Data Sets

• Sea Ice Trends and Climatologies from SMMR and SSM/I-SSMIS
  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.
• DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures
  NSIDC produces daily gridded brightness temperature data from orbital (swath) data generated by SSM/I mounted on the DMSP F8, F11, and F13 platforms. The gridded brightness temperatures are distributed in polar stereographic projection.
• Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data
  This data set is generated from brightness temperature data derived from the Nimbus-7 SMMR and DMSP F8, F11, and F13 SSM/I radiances at a grid cell size of 25 x 25 km. The data are provided in the polar stereographic projection.
• Sea Ice Index
  The images in the Sea Ice Index data set depict average ice conditions, estimated using satellite passive microwave data for the most recent month available, as well as snapshots of trends and anomalies that compare these recent conditions with the mean for the month.
• Sea Ice Data
  This site offers a summary of sea ice data derived from passive microwave sensors and other sources and is useful for users who want to compare characteristics of various sea ice products to understand their similarities and differences. This site also provides links to tools for passive microwave data and a list of other sea ice resources.

Related Websites

Contacts and Acknowledgments

Josefino C. Comiso
Oceans and Ice Branch, Code 971
NASA Goddard Space Flight Center
Greenbelt, MD 20771 USA

References

Cho, K., N. Sasaki, H. Shimoda, T. Sakata, and F. Nishio. 1996. Evaluation and Improvement of SSM/I Sea Ice Concentration Algorithms for the Sea of Okhotsk. Journal Remote Sensing of Japan 16(2):47-58.

Comiso, J.C., R.A. Gersten, L.V. Stock, J. Turner, G.J. Perez, and K. Cho. 2017. Positive Trend in the Antarctic Sea Ice Cover and Associated Changes in Surface Temperature. J. Climate, 30, 2251–2267, https://doi.org/10.1175/JCLI-D-16-0408.1

Comiso, J.C. 2010. Polar Oceans from Space, Springer Publishing, New York, doi 10.1007/978-0-387- 68300-3.

Comiso, J. C. 2009. Enhanced sea ice concentration and ice extent from AMSR-E Data, J. Remote Sensing Soc. of Japan, 29(1), 199-215.

Comiso, J. C., and F. Nishio. 2008. Trends in the Sea Ice Cover Using Enhanced and Compatible AMSR-E, SSM/I, and SMMR Data. Journal of Geophysical Research 113, C02S07, doi:10.1029/2007JC0043257.

Comiso, J. C., D. Cavalieri, C. Parkinson, and P. Gloersen. 1997. Passive Microwave Algorithms for Sea Ice Concentrations: A Comparison of Two Techniques. Remote Sensing of the Environment 60(3):357-84.

Comiso, J. C., and R. Kwok. 1996. The Summer Arctic Sea Ice Cover from Satellite Observations. Journal of Geophysical Research 101(C2):28,397-416.

Comiso, J. C. 1995. SSM/I Concentrations Using the Bootstrap Algorithm. NASA Reference Publication 1380. 40 pages.

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. Microwave Remote Sensing of Sea Ice, ed. Frank Carsey. Washington D.C.: American Geophysical Union. 243-59.

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):9,663-81.

Comiso, J. C. 1984. Characteristics of Winter Sea Ice from Satellite Multispectral Microwave Observations. Journal of Geophysical Research 91(C1):975-94.

Comiso, J. C., S. F. Ackley, and A. L. Gordon. 1984. Antarctic Sea Ice Microwave Signature and Their Correlation with In-Situ Ice Observations. Journal of Geophysical Research 89(C1):662-72.

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

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.

National Snow and Ice Data Center. 1992. DMSP SSM/I Brightness Temperature and Sea Ice Concentration Grids for the Polar Regions on CD-ROM - User's Guide. NSIDC Special Report - 1. 222 pp.

Parkinson, C. L., D. J. Cavalieri, P. Gloersen, H. J. Zwally, and J. C. Comiso, 1999.  Arctic Sea Ice Extents, Areas, and Trends, 1978-1996. Journal of Geophysical Research 104(C9), 20,837-20,856.

Parkinson, C. L., J. C. Comiso, H. J. Zwally, D. J. Cavalieri, P. Gloersen, and W. J. Campbell. 1987. Arctic Sea Ice 1973-1976 from Satellite Passive Microwave Observations. NASA Special Publication 489.

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

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

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

Zwally, H. J., J. C. Comiso, C. L. Parkinson, W. J. Campbell, F. D. Carsey, and P. Gloersen. 1983. Antarctic Sea Ice 1973-1976 from Satellite Passive Microwave Observations. NASA Special Publication 459.