Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

Abstract

Arctic sea ice leads play a major role in exchanging heat and momentum between the Arctic atmosphere and ocean as well as in the retrieval of sea ice thickness. Although leads cover only a small portion of the Arctic Ocean, they affect the heat budget in the Arctic region considerably. In this study, we propose a waveform mixture analysis to detect leads, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture analysis adopts the concept of linear mixture analysis that is widely used in the field of hyperspectral image analysis. This lead detection method based on the waveform mixture analysis was evaluated with high resolution (250m) MODIS images and showed better performance in detecting leads than previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters, as it directly uses L1B waveform data unlike the existing threshold-based methods. Monthly lead fraction maps derived by the waveform mixture analysis were produced, which show a strong inter-annualvariability of recent sea ice cover during 2006-2011 excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from the literature, resulting in similar spatiotemporal patterns.