부산대학교 도서관

We have developed a thin ice detection algorithm for the AMSR2 radiometer data. The algorithm, denoted as AMSR2 thin ice detection algorithm—version 2 (ATIDA2), is targeted for the Arctic Ocean. The detection of thin ice with a maximum thickness of 20 cm is based on the classification of the 36-GHz polarization ratio ( $PR36$ ) and H-polarization 89–36-GHz gradient ratio ( $GR8936H$ ) signatures with a linear discriminant analysis (LDA) and thick ice restoration with $GR3610H$ . The thick ice restoration removes erroneous thin ice detections due to thin and thick ice $PR36$ and $GR8936H$ signature mixing. ATIDA2 is applied only when sea ice concentration (SIC) is ≥70% and the air temperature is ≤−5 °C to decrease misclassification of thick ice as thin ice. For the AMSR2 L1R brightness temperature data, an atmospheric correction is applied following an EUMETSAT OSI SAF correction scheme in SIC retrieval algorithms. ATIDA2 is applied to L1R swath datasets, and then, the results are combined to a daily thin ice chart. ATIDA2 was developed and validated using MODIS ice thickness charts over the Barents and Kara Seas. The average probability for misclassification of thick ice as thin ice in the daily chart is 8.7%, and 37.0% for vice versa. The comparison of the ATIDA2 chart and the SMOS ice thickness chart over the Arctic showed rough correspondence in the thin versus thick ice classification. The ATIDA2 chart is targeted to be used together with SAR imagery for various sea ice classifications.