An Automated Method for Polynya Detection Using a Geomorphon Algorithm

Abstract. Polynyas, persistent areas of open water within sea ice, are critical features of polar marine systems, facilitating ocean-atmosphere heat exchange, deep water formation, nutrient cycling, and biological productivity. However, current remote detection methods, typically based on sea ice concentration thresholds, often struggle to capture the complex morphology of polynyas, especially fine-scale coastal features, and can be time-consuming to use and inconsistent across spatial scales. This study presents a novel application of a geomorphon pattern recognition algorithm, originally developed for terrestrial landform classification, to automate polynya detection using sea ice concentration data. Focusing on two key Southern Ocean regions, the Weddell and Amundsen Seas, we assess the algorithm’s performance through a comprehensive sensitivity analysis, involving 96 and 144 parameter combinations respectively, and compare the results to polynyas identified using a traditional sea ice concentration threshold-based method. By identifying morphological analogues, such as depressions and valleys in sea ice concentration data, the geomorphon method effectively captures spatial patterns and areal extents of polynyas, closely aligning with results from traditional threshold-based approaches and literature reports. The method's scalability and self-adaptive lookup distance allows detection of both large-scale open water and small coastal polynyas. Application of analytically rescaled parameters to an independent passive microwave sea ice concentration dataset further demonstrated transferability across datasets and spatial resolutions without additional optimisation. Critically, its automated nature enables rapid processing of time series data, up to two orders of magnitude faster than traditional methods, making it well-suited for investigating long-term polynya dynamics. By enabling consistent detection across large datasets, the method provides a framework to support investigations into climate-sensitive ocean processes, including air-sea fluxes, water mass formation, carbon cycling, and ecosystem dynamics in polar regions.