Sea ice concentration is both an indicator and driver of high-latitude climate change with strong societal and ecological importance. It is a key boundary condition for atmospheric models (including those used in atmospheric reanalyses) and a benchmark for coupled climate models. As such, numerous methods have been developed to estimate sea ice concentration. The most widely used sea ice data sets for climate research are derived from passive microwave instruments, including SMMR, SSMI, SSMIS, AMSR-E and AMSR-2, flying on various satellite platforms. The algorithms applied to the microwave brightness temperatures use different combinations of channels, making different corrections for weather, satellite drift, and other factors. Users of sea ice data should be aware of the different algorithms and their attributes, the different spatial footprints of the satellite instruments and channels, and the methods for combining different source data into long-term data sets. The table and links below provide a starting point for understanding and locating the appropriate data sets. The focus is on long-term data sets rather than near-real-time products.
- Comiso, J. C., D. J. Cavalieri, C. L. Parkinson, and P. Gloersen (1997), Passive microwave algorithms for sea ice concentration: A comparison of two techniques, Remote Sens. Environ., 60, 357–384.
- Andersen, S., R. Tonboe, L. Kaleschke, G. Heygster, and L. T. Pedersen (2007), Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice, J. Geophys. Res., 112, C08004, doi:10.1029/2006JC003543.
- Kattsov, V.M and coauthors (2010), Arctic sea ice change: a grand challenge of climate science, J. Glaciology 200(56), 1115-1121.
- Meier, W. (2005), Comparison of passive microwave ice concentration algorithm retrievals with AVHRR imagery in arctic peripheral seas, IEEE Transactions on Geosciences and Remote Sensing, 43(6), 1324-1337.