Exploring Sea Ice Data from SatellitesNSIDC Sea Ice Index, Images and summaries, Raw data. Access browse images and monthly summary files (total extent and area) from the Sea Ice Index page. Access the raw data (gridded daily/monthly fields of sea ice) at the data product page.
The browse and summary data provide imagery of monthly sea ice conditions and anomalies, as well as text files with monthly total extent and area values. The raw data are 2-dimensional gridded fields with daily and monthly sea ice concentration at 25-km spatial resolution.
http://nsidc.org/data/seaice_index/ Latest monthly browse images of sea ice conditions. National Snow and Ice Data Center, Boulder, CO.
Use and Relevance
The Sea Ice Index provides easy-to-access and use browse imagery and text formatted data, providing information on monthly sea ice conditions since 1978. The text data can be imported into spreadsheet software to investigate anomalies and trend. Raw data can be used to analyze daily conditions and daily/monthly regional trends and anomalies.
Use in Teaching
The browse images and summaries can be used to understand the seasonal cycle of Arctic and Antarctic sea ice, the interannual variability and recent trends. These trends provide an example of observed climate change due to anthropogenically-induced climate change. The raw data can be used to give students experience working with real scientific satellite data and to look more in depth at regional and daily changes in the sea ice to investigate impacts of ice conditions on polar bears, fisheries, and native communities.
- Image processing
- Assessing change in sea ice
Exploring the Data
Data Type and Presentation
Browse images are in PNG format. Data summaries are tab-delimited text files. Raw data are 2-dimensional 1-byte gridded arrays with a 300-byte header file; array size is 304 (cols) x 448 (rows) for Northern Hemisphere and 316 x 332 for Southern Hemisphere.
Accessing the Data
Data are accessible via ftp through a web browser or ftp server. Data summaries can be imported into spreadsheets. Raw data can be input into image processing software (e.g., ImageJ, ENVI, etc.).
Manipulating Data and Creating Visualizations
ImageJ can produce images from raw data.
Tools for Data Manipulation
ImageJ can be used to import, display, and analyze raw data fields.
Acronyms, Initials, and Jargon
SSM/I = Special Sensor Microwave Imager
Sea Ice Concentration = % of a given area (e.g., a 25x25 km pixel) covered by ice (0-100%)
Sea Ice Extent = total area covered by at least 15% ice (sum of areas of all pixels with concentrations ≥ 15%)
Sea Ice Area = total ice-covered area (sum of areas of all pixels with concentration ≥ 15% * concentration of each pixel)
About the Data
The data is archived and distributed by NSIDC.
Limitations and Sources of Error
The accuracy near the ice edge is limited because of the low spatial resolution of the sensor (25-50 km). Errors occur in summer because of melt water on the surface of the ice—this causes an underestimation in concentration at a given pixel; however, ice extent is less affected by this error. Recently-formed thin ice also tends to be underestimated. Atmospheric emission from thick clouds or rain, though passive microwave signals are minimally affected by most clouds and can retrieve data in the absence of sunlight. Waves from strong winds over the open ocean can be detected by ice, but most such artifacts have been filtered out during the data processing. Overall, errors can be high at any given location (e.g., at a pixel) at a given time, but hemispheric monthly averages are accurate (<5% error).
References and Resources
Scientific References that Use this Dataset
- Review of Arctic sea ice: Serreze, M.C., M.M. Holland, J. Stroeve, 2007. Perspectives on the Arctic's shrinking sea-ice cover, Science, 315(5818), 1533-1536, doi:10.1116/science.1139426.
- Monthly sea ice data summaries and browse images: Fetterer, F., and K. Knowles, 2004. Sea ice index monitors polar ice extent, Eos: Trans. of the Amer. Geophys. Union, vol. 85, p. 163.
- Derivation of the data set: 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, J. Geophys. Res., 104(C7), 15,803-15,814.
Education Resources that Use this Dataset
NSIDC "All About Sea Ice"
Canadian Ice Service
Antarctic Sea Ice Processes and Climate