Estimation of thin ice thickness from AMSR-E data in the Chukchi Sea

• Published in: International Journal of Remote Sensing
• Main Authors: Iwamoto, K, Ohshima, KI, Tamura, T, Nihashi, S
• Format: Article in Journal/Newspaper
• Language: English
• Published: Taylor & Francis Ltd 2013
• Subjects: Earth Sciences; Physical Geography and Environmental Geoscience; Glaciology; Arctic; Arctic Ocean; Chukchi Sea; Chukchi
• Online Access: https://doi.org/10.1080/01431161.2012.712229; http://ecite.utas.edu.au/88773

In this study, we have developed an algorithm for estimating thin ice thickness in the Chukchi Sea of the Arctic Ocean using Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) data. The algorithm is based on comparisons between the polarization ratio (PR) of AMSR-E brightness temperatures from the 89 and 36 GHz channels (PR89 and PR36) and the thermal ice thickness. The thermal ice thickness is estimated from a heat budget calculation using the ice surface temperature from clear-sky Moderate-Resolution Imaging Spectroradiometer (MODIS) infrared data. Whereas coastal polynyas have been the main target of previous algorithms, this algorithm is also applicable for marginal ice zones. AMSR-E has twice the spatial resolution of Special Sensor Microwave/Imager (SSM/I) data and can therefore resolve polynyas at a smaller scale. Although the spatial resolution of the 89 GHz data (6.25 km) is twice that of the 36 GHz data (12.5 km), the 89 GHz data can be contaminated by atmospheric water vapour. We propose an exclusion method of data affected by water vapour to resolve this issue. A combined algorithm of thin ice and ice concentration is also discussed, in which the ice thickness can be estimated independently from the open water fraction in grid cells with less than 100% ice concentration. The PRthickness relationship in this study is somewhat different from previous studies, which is likely due to the difference in prevailing ice types caused by background environmental conditions.