The cryosphere exists at all latitudes and in about one hundred countries. It has profound socio-economic value due to its role in water resources and its impact on transportation, fisheries, hunting, herding, and agriculture. The cryosphere not only plays a significant role in climate; its characterization and distribution are critical for accurate weather forecasts. A number of ice characterization algorithms have been improved and/or developed for the next generation Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager (ABI), including ice identification and concentration, ice extent, ice thickness and age, and ice motion. An overview of the ice characterization algorithms, their accuracy, and their limitations will be provided here.

Current operational GOES imager algorithms utilize heritage channels and those from both the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) for the estimation of sea and lake ice characteristics. Mature algorithms exist for ice identification and ice surface temperature, but others such as ice concentration, ice thickness, ice age, and ice motion are experimental or under development. Errors in existing algorithms must be determined by intercomparing products from other sensors and comparing those products to surface-based observations. Potential solutions to problems have been sought and new algorithms for estimating ice concentration, ice thickness/age, and ice motion have been developed as necessary. This work will serve as a testbed of the current and developing algorithms for sea and lake ice products. Preliminary tests are promising, and we expect that accuracy specifications will be met for most of the cryosphere products in the 2009-2010 timeframe.