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Summary

Note: As of 10 May 2009, NSIDC has switched its processing stream from the SSM/I instrument on the DMSP-F13 satellite to the SSMIS instrument on the DMSP-F17 satellite. This is due to a failing recorder on F13, which has been operational since 1995. For more information, see the Data Acquistion and Processing section of this document.

The Sea Ice Index provides a quick look at sea ice changes in spatial and historical context and gives a consistent, up-to-date source of sea ice extent and sea ice concentration values and images. The NSIDC Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations and the Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data data sets are used to generate the monthly records of sea ice extent and sea ice concentration for the Arctic and Antarctica from satellite passive microwave data.

Data files tabulate monthly mean extent and area, in millions of square kilometers, by year for a given month. Plots of monthly sea ice extent anomalies with trend lines and significance intervals are available. Monthly images show sea ice extent (with an outline of the median extent for that month for comparison), sea ice concentration, trends in sea ice concentration, and anomalies in sea ice concentration. Anomalies and median extent are calculated using a reference period of 1979 through 2000.

Daily images of sea ice extent and concentration, along with a time series plot of extent for the most recent four months, can be viewed and downloaded on the data product site but are not archived. Some products are available as GIS compatible shapefiles and KML files. The Browse Image Spreadsheet Tool (BIST) can be used for animated images and for displaying archived images of extent and trends side by side, to make it easy to compare images from different years and months.

Data are stored in ASCII text, Portable Network Graphics (PNG), Keyhole Markup Language (KML), and Geospatial Vector Data format and are available from November 1978 to present via FTP or the Sea Ice Index Web site.

Citing These Data

To broaden awareness of our services, NSIDC requests that you acknowledge the use of data sets distributed by NSIDC. Please refer to the citation below for the suggested form, or contact NSIDC User Services for further information. We also request that you send us one reprint of any publication that cites the use of data received from our Center. This helps us to determine the level of use of the data we distribute. Thank you.

The following example shows how to cite the use of these data sets in a publication. List the principal investigators, year of data set release, data set title and version number, dates of the data you used (for example, March to June 2004), publisher: NSIDC, and digital media.

Fetterer, F., K. Knowles, W. Meier, and M. Savoie. 2002, updated 2009. Sea Ice Index, [list the dates of the data used]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media.

Note: You may download and use any images from the Sea Ice Index; however, please credit NSIDC.

Overview Table
 

Table of Contents

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

1. Contacts and Acknowledgments

Investigators

Fetterer, Florence, Walt Meier, and Matt Savoie
National Snow and Ice Data Center
University of Colorado
Boulder, CO 80309

Technical Contact

Acknowledgements

The Sea Ice Index was developed with financial support from NOAA NESDIS and in cooperation with NOAA NGDC. This site is maintained with assistance from the NSIDC NASA DAAC.

2. Detailed Data Description

Format

Data Files: ASCII text

Monthly and Daily Browse Images: Portable Network Graphics (PNG)

Virtual Globe Files: Keyhole Markup Language (KML) and KMZ files. KMZ files are zipped KML files with a .kmz extension. When a KMZ file is unzipped, a single doc.kml file is found along with any overlay and icon images referenced in the KML file. To access the KML or KMZ files, use an earth browser such as Google Earth™.

Shapefiles: Geospatial Vector Data

File Naming Convention

This section explains the file naming conventions used for this product with examples.

Data Files Using Variables:

h_mm_area.txt
h_mm_area.txt

Where:

Example Data Files:
N_04_area.txt
S_04_area.txt

Monthly Image Files Using Variables:

h_mm_plot.png
h_mm_trend.png
h_yyyymm_anom.png
h_yyyymm_conc.png
h_yyyymm_extn.png

Where:

Example Monthly Image Files:
N_04_plot.png
N_04_trend.png
N_200303_anom.png
N_200303_conc.png
N_200303_extn.png
S_04_plot.png
S_04_trend.png
S_200303_anom.png
S_200303_conc.png
S_200303_extn.png

Extent Shapefiles Using Variables:

extent_h_yyyymm_polyline.zip
extent_h_yyyymm_polygon.zip

Where:

Example Extent Shapefiles:
extent_N_197904_polyline.zip
extent_N_197904_polygon.zip
extent_S_197904_polyline.zip
extent_S_197904_polygon.zip

Median Shapefiles Using Variables:

median_h_mm_yyyy_yyyy_polyline.zip
median_h_mm_yyyy_yyyy_polyline.zip

Where:

Example Median Shapefiles:
median_N_04_1979_2000_polyline.zip
median_S_04_1979_2000_polyline.zip

Directory Structure

Data files, monthly image files, and shapefiles are available on the FTP site in the ftp://sidads.colorado.edu/DATASETS/NOAA/G02135 directory. The top directory is divided up into months. Within each month there is a data file with extent and area numbers and all the images for the entire temporal coverage for that month. There is also a folder for the shapefiles. Refer to Figure 1.

Figure 1. Top Directory Structure

The sub directory for each month contains a comprehensive data file for both the northern and southern hemisphere, N_mm_area.txt and S_mm_area.txt, which contains information for the entire temporal coverage and all the monthly browse images for the entire temporal coverage for a given month, which is from November 1978 to present. Refer to Figure 2.

Figure 2. Sub Directory Structure for the Month of April

File Size

Refer to Table 5 for a listing of file types and sizes.

Spatial Coverage

North and south polar regions.

Spatial Resolution

The spatial resolution is 25 km.

Projection

Data are in a polar stereographic projection. For information, see the Polar Stereographic Projections and Grids Web page.

Grid Description

Grid size varies by region:

North: 304 columns x 448 rows
South: 316 columns x 332 rows

Temporal Coverage

Temporal coverage is from November 1978 to present.

Data files have a temporal coverage from November 1978 to present.

Daily browse images are not archived and only the previous day can be found on the product Web site. However, you can access the daily sea ice concentration images for the Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I Passive Microwave Data set.

Monthly browse images have a temporal coverage from November 1978 to present.

Monthly sea ice extent shapefiles have a temporal coverage from November 1978 to present. Shapefiles are available for Northern and Southern hemispheres, both polygons and polylines.

Monthly sea ice median shapefiles have a temporal coverage from November 1978 to 2000. Shapefiles are available for Northern and Southern hemispheres, polylines only.

Temporal Resolution

The temporal resolution is daily and monthly.

Parameter or Variable

The following list are the parameters for this data set.

• Sea Ice Extent
• Sea Ice Concentration
• Sea Ice Concentration Trends
• Sea Ice Concentration Anomalies
• Sea Ice Extent Anomalies

Paremeter Description

The values for ice extent are obtained by summing the area covered by all pixels that have 15 percent or greater ice concentration.Ice extent anomalies are plotted as a time series of percent differences between the total extent for the month in question, and the mean for that month, where the mean is based on the January 1979 - December 2000 portion of the data set.

The trend, in percent change per decade, is obtained using least squares regression, and a 95 percent confidence interval for the resulting slope is given.

To produce concentration anomaly images, monthly concentration images are subtracted from an image of the mean for the month in question from the 1979 - 2000 portion of the data set. A least squares regression is performed on the time series of concentrations at each pixel. The time period covered by the trend analysis is from November 1978 to the present month.

Paremeter Range

Concentration = 0 to 100 percent

Extent Area = 4 million square km in summer to 16 million square km in winter for the Arctic, and 3 million square km in summer to 18 million square km in winter for the Antarctic (unbounded)

Extent Anomalies = -100 to 100 percent

Extent Area Anomalies = percent

Trend - 0 percent per decade (unbounded)

Sample Data Record

Figure 3 is an example of the data file, N_04_area.txt, that is located in the April folder in the top directory. Each month listed in the top directory has a data file.

Figure 3. Sample Data File

Error Sources

There are a number of algorithms in use that convert channel brightness temperatures to sea ice concentration. All perform slightly differently under varying weather and ice conditions. Relatively few papers were published that compare algorithms or compare results with validation data. These include Comiso and Steffen (2001), Meier et al. (2001), Steffen and Schweiger (1991) and Emery et al. (1994). The Sea Ice Index is based on the NASA Team algorithm (Cavalieri et al. 1984) because the NRTSI product uses this algorithm. It is possible to make some generalizations about the accuracy of passive microwave sea ice concentrations. Gloerson and Campbell (1991) estimate that ice concentration retrievals are accurate to within five to nine percent, depending on the ice being imaged. Passive microwave algorithms generally cannot detect thin ice reliably (Cavalieri 1994). Based on comparisons with analyses of synthetic aperture radar data, passive microwave overestimates open water by three to five times in winter (Kwok 2002). The winter coverage of open water is only about 0.3 percent. New openings in the ice, that appear as linear leads, freeze over almost immediately.

In summer, passive microwave overestimates open water by a larger amount, as the instrument cannot distinguish open water between ice floes with melt ponds on the floes, and other factors such as the ice-snow interface come into play (Comiso and Kwok 1996) and (Fetterer and Untersteiner 1998). This makes it difficult to interpret trends and anomalies for the summer months. The statistically significant negative trend in the Beaufort Sea in June and July, for example, may reflect a real trend towards more open water, but is also likely to reflect a trend in ice surface conditions that masquerades as a trend in ice concentration.

Probably the best validation data for passive microwave ice retrievals are charts from operational ice centers. These charts are drawn by analysts based on satellite data from a number of sources as well as, in some cases, ship or aerial surveys. A study based on digital versions of the U.S. National Ice Center's (NIC) charts covering the Arctic every week from 1972-1994 (Partington et al. 2003), shows that NIC charts consistently report about four percent more ice per unit area than passive microwave retrievals from the NASA Team algorithm. This holds for November through May. Beginning in June, the difference rises to about 23 percent, and falls off gradually over the summer and into fall freeze-up. The difference after freeze-up, which begins in September over most of the Arctic, is probably due to the insensitivity of the passive microwave algorithm to thin ice. Both chart data and passive microwave data show a negative trend in integrated arctic-wide concentration over the period 1979-1994. The difference between the passive microwave and chart trends is statistically significant only in the summer, where it is about two percent per decade steeper in passive microwave data.

A comparison of ice-covered area from the NASA Team algorithm with 18 years of Canadian Ice Service charts showed that passive microwave data markedly underestimate ice area by 30 to 40 percent during spring melt and fall freeze-up, for the Hudson Bay and East Coast regions. There is considerable scatter in the differences rather than a consistent pattern (Agnew and Howell 2002a) and (Agnew and Howell 2002b). The difference between chart and passive microwave-derived ice areas is greater for the Canadian charts than the U.S. charts. This is likely a reflection of the fact that the U.S. National Ice Center uses passive microwave when other data are not available, which is often the case for the central Arctic and other remote areas, while the Canadian Ice Service only rarely uses passive microwave data, relying instead on airborne and satellite radar, satellite optical, and visual observations for charts of the Canadian Arctic. These methods detect thin ice, lower concentrations of ice, and flooded ice much better than passive microwave data allows (personal communication, J. Falkingham, Chief of Operations, Canadian Ice Service, December 2002).

Spot checks of the ice edge position using a 15 percent concentration cutoff against NIC ice charts show that when there is a broad, diffuse ice edge, the NRTSI and Standard Team products sometimes do not detect ice where the concentration can be as high as 60 percent. When the ice edge is more compact, the 15 percent concentration cutoff reflects its location fairly well. The large footprint of the 19 GHz channel means that a compact ice edge is smeared out in passive microwave imagery.

A study comparing passive microwave sea ice concentration data with approximately 1 km resolution imagery from the Advanced Very High Resolution Radiometer (Meier 2005) focuses on the ice edge. Four SSM/I algorithms are used. The work illustrates how algorithms often underestimate concentration. The NASA Team underestimates concentration by about 10 percent on average, and by much more in some circumstances.

Newer algorithms were developed that perform better than the NASA Team algorithm. An enhanced version of the NASA Team algorithm, NT2, incorporates the SSM/I 85 GHz channel and applies a forward-radiative transfer model to correct for weather effects that are exacerbated by use of the 85 GHz channel. This algorithm is the standard algorithm for arctic sea ice concentration retrievals with the AMSR-E instrument (Markus and Dokken 2002).

We have considered using one of the newer algorithms for the Sea Ice Index, but this would require research and reprocessing in order to ensure that the record is consistent over the entire time series. The SMMR instrument did not include a high frequency channel like that used in newer SSM/I and AMSR-E sea ice algorithms.

Quality Assessment

When the image data files are created, the most recent data available is initially used, and then it is replaced with final, high quality control data when it becomes available. Quality fo sea ice index data is depended on the source data whose error sorces are discussed in the previous section.

3. Data Access and Tools

Data Access

Data are available via FTP or from the Sea Ice Index Web site.

Software and Tools

Tools for browsing and comparing images from the Sea Ice Index are available on the Browse Image Spreadsheet Tool (BIST) Web page.

Related Data Collections

• Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data
• Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations (NRTSI)

4. Data Acquisition and Processing

As of 10 May 2009, NSIDC has switched its processing stream from the SSM/I DMSP-F13 satellite to the SSMIS DMSP-F17 satellite. This is due to a failing recorder on F13, which has been operational since 1995.

NSIDC has done preliminary inter-calibration between F13 and F17 to correct for sensor differences in the Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations and the Sea Ice Index data products, using an overlap period of 01 April 2008 to 31 March 2009. They retain reasonable consistency, though differences of approximately 28,000 sq km may be possible in daily total extents. For data continuity, F17 data has been acquired back to 26 March 2008. Near-real-time F13 data will remain available upon request for the period 01 July 2008 to 10 May 2009. Further information about these changes can be found on the Arctic Sea Ice News & Analysis Web site.

Records of sea ice extent and sea ice concentration from satellite passive microwave data are available for October 1978 through June 1987 from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), from July 1987 to May 2009 from its successor, the DMSP Special Sensor Microwave/Imager (SSM/I), and since May 2009 from the DMSP Special Sensor Microwave Imager/Sounder (SSMIS), the next generation SSM/I instrument. Sea ice concentration can be estimated from brightness temperature data because sea ice and water have differing passive microwave signatures.

Interpreting the Data

To help interpret the images and figures within the Sea Ice Index correctly, the Sea Ice Index: Interpretation Resources for Sea Ice Trends and Anomalies document (Fetterer 2004) discusses the variability of sea ice, the applicability of statistical methods for trend detection, and the validity of passive microwave images of sea ice.

Data Source

The Sea Ice Index is produced primarily from Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data, produced at the Goddard Space Flight Center (GSFC). This product contains daily and monthly grids of sea ice concentrations derived to provide a consistent long-term time series beginning with the SMMR instrument in October 1978. These data are produced and periodically updated by GSFC investigators using brightness temperatures from NSIDC. Final Sea Ice Index fields are produced from the final versions of the GSFC product.

The most recent data used in the Sea Ice Index are processed from NSIDC’s Near-Real-Time SSM/I Polar Gridded Sea Ice Concentrations (NRTSI) data set. The NRTSI fields are processed in a similar manner to the GSFC product, but the input brightness temperature data have a lower quality-control level; therefore, there may be missing data.

Each Sea Ice Index monthly update uses the highest processing level available for that given month. Thus, fields produced from NRTSI data will later be replaced with values from GSFC data. These changes in data source can result in slight changes in the total extent, concentration, and anomaly values; the changes are generally less than 20,000 km² (30-40 grid points).

To create the images for the Sea Ice Index, daily data are used to obtain each month’s average sea ice concentrations. The averages are then appended to a time series of that month’s means before estimating trends and differenced with the long term (1979 - 2000) average for that month to estimate anomalies. Consistency between NRTSI and GSFC-derived data was checked by processing NRTSI data for 2002 using both brightness temperature data from NSIDC and near-real-time brightness temperature data from NASA Marshall Space Flight Center (MSFC) as input, and then differencing monthly Sea Ice Index grids with monthly grids derived from GSFC daily grids for 2002. We found that the brightness temperature source made little difference in overall extent and area. The differences in the NRTSI and the GSFC derived monthly area and extent values for the year 2002 are at most 1.6 percent (the area difference in June with Remote Sensing Systems (RSS) brightness temperatures) with most differences much lower or negligible. Yearly average differences in ice extent of 0.38 percentage area of 0.42 percent are on the same order as reported by the GSFC series. See Section 2 of the Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data guide documentation. Note that while these small differences show that overall summaries of ice extent within the Sea Ice Index data set are consistent over time, significant regional differences in ice concentration may be present across changes in instrumentation within the GSFC data set and across the GSFC/NRTSI change in the Sea Ice Index data set.

For imformation regarding theory of measurements, sensor or instrument descriptions, data acquisition methods, and derivation techniques and alogorithms, please see the following source documents:

• Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data
• Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations (NRTSI).

Processing Steps

Monthly Mean Ice Concentration

GSFC daily grids are averaged at NSIDC into monthly grids, to create a monthly mean concentration series and to obtain standard deviations. Note: There may be differences in these monthly mean concentration grids derived from daily data and the monthly mean concentration fields available as part of the GSFC data set. These result from differences in processing discussed in the Data Sources secton of this document. For NRTSI, monthly averages are computed from gridded daily products. The nominal pixel size of the gridded products is 25 km. Occasionally, data from one or more days within the month is missing. Averages are computed only if there are at least 20 days of data. SMMR only operated every other day, resulting in half as much data as for SSM/I; thus, a period of 10 days is required each month for SMMR.

In constructing monthly mean ice concentrations, a temporal and spatial average are conflated. That is, a mean concentration of 50 percent for a pixel in September could be the result of 100 percent concentration for 15 days and 0 percent concentration for 15 days, or 50 percent concentration for 30 days, or some other combination. The meaning of average concentration can therefore be ambiguous, especially near the ice edge, where wind can move ice rapidly into and out of the area covered by a pixel.

The total area at the bottom of the ice concentration image is the sum of the area covered by ice, not including the open water area within the margins of the pack or the area near the pole that is not imaged by the sensor, called the pole hole. The total area is always less than total extent.

Ice Extent and Ice Area Values

The values for ice extent are obtained by summing the area covered by all pixels that have 15 percent or greater ice concentration. It is assume that the area not imaged by the sensor at the North Pole is entirely ice-covered. Each pixel’s area is calculated individually, and is obtained by multiplying the nominal pixel size (625 km²) by the square of the map scale at the center of the pixel. Pixel areas range from 382 to 664 square kilometers for the Northern Hemisphere and 443 to 664 square kilometers for the Southern Hemisphere, under the polar stereographic projection and grid used for the input data sets. The extent values are useful in a temporal series, but caution should be used citing the numbers apart from the time series or comparing with values derived from other studies. Ice concentrations are sensitive to the algorithm used, and resulting numbers for extent depend not only on algorithms but on other processing steps as well. The extent values have uncertain significance when taken individually. For example, the 15 percent concentration cutoff for extent is somewhat arbitrary. Using a 20 percent or 30 percent cutoff gives different numbers, although similar trends, for extent. For examples, see Parkinson et al (1999). The values for ice area are obtained by summing the concentration of ice within each pixel over the entire ice extent. For example, if a pixel's area was 600 km² and its ice concentration was 75 percent, then the ice area for that pixel would be 450 km². Note that unlike ice extent, the Arctic values for ice area do not include the area near the pole not imaged by the sensor, called the pole hole. This area is 1.19 million square kilometers for SMMR (from the beginning of the series through June 1987) and 0.31 million square kilometers for SSM/I (from July 1987 to present). Therefore, there is a discontinuity in the area data values in this file at the June/July 1987 boundary.

Average Ice Edge and Ice Extent Anomalies

On monthly mean images, the ice edge is where concentration drops below 15 percent, although a mean ice edge is a somewhat ambiguous concept. How does this edge position compare with what is typical for the month, based on the January 1979 - December 2000 portion of the data set? To help answer this question, a median edge for the month was computed by showing those pixels for which there is a 50 percent probability of ice occurring at 15 percent concentration or greater.

Alternatively, we could have computed an average edge by averaging the mean concentrations and using the 15 percent cutoff in the average concentration image as the mean edge. However, this method results in a mean edge that is unlikely to resemble any typical ice edge because the location of the edge varies considerably from year to year.

Images of anomalies in ice extent show the difference between the location of the median ice edge for the month, as described above, and the ice edge location for a particular month. The total extent of sea ice for that month is also shown.

Trends in Ice Extent

Ice extent anomalies are plotted as a time series of percent differences between the total extent for the month in question, and the mean for that month, where the mean is based on the January 1979 - December 2000 portion of the data set. The trend, in percent change per decade, is obtained using least squares regression, and a 95 percent confidence interval for the resulting slope is given.

Anomalies in Concentration

To produce concentration anomaly images, monthly concentration images are subtracted from an image of the mean for the month in question from the 1979 - 2000 portion of the data set. The color bar shows, in percent, how much the ice concentration for the month differs from the mean calculated for that month over the 1979 - 2000 portion of the data set.

Note: An area may have a positive anomaly for a given month while at the same time showing a negative trend in concentration over time.

Trends in Concentration

A least squares regression is performed on the time series of concentrations at each pixel. The time period covered by the trend analysis is from November 1978 to the present month. Pixels that have zero concentration are left out of the time series when calculating trends. Generally, these pixels are near the ice edge. The slope of the linear fit gives the trend in concentration for that pixel. A 95 percent confidence interval is used for significance. The null hypothesis that the slope of the fit line is zero is rejected with 95 percent confidence. Trends are shown in percent change in concentration per decade. If the null hypothesis of no slope (no trend in concentration) cannot be rejected, the pixel is shown in white.

Daily Images

Daily extent and concentration images are produced from the NASA Team algorithm using Near-Real-Time DMSP SSM/I Daily Polar Gridded Brightness Temperatures. The processing includes quality control features such as two weather filters based on brightness temperature ratios to screen out erroneous ice over open water, an ocean mask to eliminate any remaining sea ice in regions where sea ice is not expected, and a coastal filter to eliminate most false ice due to mixed land/ocean grid cells. It does not include any spatial or temporal interpolation to fill in missing data.

There is greater uncertainty in daily fields than in the monthly average fields and greater uncertainty in the concentration fields than the extent fields. Reduced sea ice concentrations may be an indication of less ice but often reflect atmospheric and surface changes, including clouds and water vapor, melt on the ice surface, and changes in the character of the snow and ice surface. Thus, any changes seen in the concentration images should be viewed in this light. Extent fields are more reliable and more stable as they merely register the presence of at least 15 percent sea ice in a grid cell. The extent images include a median extent line, based on a 1979 to 2000 climatology for the given day.

Sea ice extent time series images are produced by summing the area of all grid cells with at least 15 percent sea ice. On daily scales, these extent values can have fairly large variations, both due to real changes in ice extent (growth/melt and motion of the ice edge) and due to ephemeral weather and surface effects. To reduce any erroneous artifacts and produce a more stable trend line, a 5-day running mean is used in the plot. Occasionally, there may be days with large data gaps due to satellite or sensor outages. Such days are removed from the time series and replaced with an interpolated value based on the total extent of the surrounding days.

Spatial Coverage: The Pole Hole

The SMMR and SSM/I instruments do not image a circular sector over the poles, due to orbit inclination. In the GSFC data set, the area of this pole hole is 0.31 x 106 km² for SSM/I and 1.19 x 106 km² for SMMR. In calculating Northern hemisphere ice extent, it is assumed that the entire area is ice covered. The Northern hemisphere ice concentration anomaly and trend images have no data for the area covered by the larger SMMR hole, because the time series upon which these derived values are based includes the SMMR instrument.

5. References and Related Publications

Agnew, T. A., and S. Howell. 2002a. The use of operational i ce charts for evaluating passive microwave ice concentration data. Internal Report of the Meteorological Service of Canada. 34 pp.

Agnew, T. A., and S. Howell. 2002b. Comparison of digitized Canadian ice charts and passive microwave sea-ice concentrations. Procedures of the International Geoscience and Remote Sensing Symposium, July 24-28. Toronto: Canada.

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., 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: 455-464.

Cavalieri, D., P. Gloerson, and J. Zwally. 1990. DMSP SSM/I daily polar gridded sea ice concentrations. Edited by J. Maslanik and J. Stroeve. Boulder, CO: National Snow and Ice Data Center. Digital media.

Cavalieri, D., C. Parkinson, P. Gloerson, and H.J. Zwally. 1997, updated 2005. Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I passive microwave data, June to September 2001. Boulder, CO: National Snow and Ice Data Center. Digital media and CD-ROM.

Cavalieri, D., P. Gloerson, and J. Zwally. 2002, updated daily. Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations. Edited by J. Maslanik and J. Stroeve. Boulder, CO: National Snow and Ice Data Center. Digital media.

Comiso, J. C., and R. Kwok. 1996. Surface and radiative characteristics of the summer arctic sea ice cover from multi-sensor satellite observations. Journal of Geophysical Research 101 (C12): 28, 397-28, 416.

Comiso, J. C., and K. Steffen. 2001. Studies of Antarctic sea ice concentrations from satellite data and their applications. Journal of Geophysical Research 106 (C12): 31, 361-31, 386.

Emery, W. J., C. Fowler, and J. Maslanik. 1994. Arctic sea ice concentration from Special Sensor Microwave Imager and Advanced Very High Resolution Radiometer satellite data. Journal of Geophysical Research 99: 18,329-18,342.

Eppler, D.T., L.D. Farmer, A.W. Lohanick, M.A. Anderson, D. Cavalieri, J. Comiso, P. Gloersen, C. Garrity, T.C. Grenfell, M. Hallikainen, J.A. Maslanik, C. Mätzler, R.A. Melloh, I. Rubinstein, and C.T. Swift. 1992. Passive microwave signatures of sea ice. In Microwave remote sensing of sea ice. Edited by F.D. Carsey. Washington, D.C.: American Geophysical Union. 47-71.

Fetterer, F., and N. Untersteiner. 1998. Observations of melt ponds on arctic sea ice. Journal of Geophysical Research 103 (C11): 24,821-24,835.

Hollinger, J.P., J.L. Peirce, and G.A. Poe. 1990. SSM/I Instrument Evaluation. IEEE Transactions on Geoscience and Remote Sensing 28 (5): 781-790.

Kwok, R. 2002. Sea ice concentration estimates from satellite passive microwave radiometry and openings from SAR ice motion. Geophysical Research Letters 29 (9): 10.1029/202GL014787.

Markus, T., and S. T. Dokken. 2002. Evaluation of late summer passive microwave arctic sea ice retrievals. IEEE Transactions on Geoscience and Remote Sensing 40 (2): 348-356.

Meier, W. N., M .L. V. Woert, and C. Bertoia. 2001. Evaluation of operational SSM/I algorithms. Annals of Glaciology 33: 102-108.

Meier, W. N. 2005. Comparison of passive microwave retrievals with AVHRR imagery in arctic peripheral seas. IEEE Transactions on Geoscience and Remote Sensing 43 (6): 1324-1337.

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.

Partington, K., T. Flynn, D. Lamb, C. Bertoia, and K. Dedrick. 2003. Late twentieth century Northern Hemisphere sea-ice record from U.S. National Ice Center ice charts. J. Geophys. Res. 108(C11): 3343. doi:10.1029/2002JC001623.

Steffen, K., and A. Schweiger. 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): 21,971-21,987.

Steffen, K., J. Key, D. Cavalieri, J. Comiso, P. Gloersen, K.S. Germain, and I. Rubinstein. 1992. The estimation of geophysical parameters using passive microwave algorithms in microwave remote sensing of sea ice. Edited by F.D. Carsey. Washington, D.C.: American Geophysical Union. 201-231.

Sea Ice Index References

Meier, W., J. Stroeve, F. Fetterer, K. Knowles. 2005. Reductions in arctic sea ice cover no longer limited to summer. Eos: Transactions of the American Geophysical Society 86, 326.

Fetterer, F., and K. Knowles. 2004. Sea ice index monitors polar ice extent. Eos: Transactions of the American Geophysical Society 85, 163.

6. Document Information

Acronyms

The following acronyms are used in this document.

Document Creation Date

October 2008

Document Creation Date

June 2009: A. Windnagel added note about transition from F13 to F17.

Document URL

http://nsidc.org/data/docs/noaa/g02135_seaice_index/index.html