An Early Warning Sign of Critical Transition in The Antarctic Ice Sheet. A New Data Driven Tool for Spatiotemporal Tipping Point

In this paper, we introduce a new tool for data-driven discovery of early warning signs of critical transitions in ice shelves, from remote sensing data. Our approach adopts principles of directed spectral clustering methodology considering an asymmetric affinity matrix and the associated directed graph Laplacian. We applied our approach generally to both reprocessed the ice velocity data, and also remote sensing satellite images of the Larsen C ice shelf. Our results allow us to (post-cast) predict fault lines responsible for the critical transitions leading to the break up of the Larsen C ice shelf crack, which resulted in the A68 iceberg, and we are able to do so, months earlier before the actual occurrence, and also much earlier than any other previously available methodology, in particular those based on interferometry.