Extended Categorical Triple Collocation for Evaluating Sea Ice/Open Water Data Sets

A method to extend categorical triple collocation (CTC) to five data sets, three of which must have conditionally independent errors, is presented. The method is shown to enable comparison of three passive microwave sea ice concentration data sets, and can easily be extended to for use with more data sets. The method is evaluated in the Gulf of Saint Lawrence, on the east coast of Canada, during the freeze-up period. It is found that the ice concentration data set from the European space agency sea ice climate change initiative (ESA-SICCI) and the NASA Team 2 (NT2) algorithms have higher balanced accuracy than that from the Artist sea ice (ASI) algorithm.