An early warning sign of critical transition in the Antarctic ice sheet – a data-driven tool for a spatiotemporal tipping point

Abstract

Our recently developed tool, called Directed Affinity Segmentation (DAS), was originally designed for the data-driven discovery of coherent sets in fluidic systems. Here we interpret that it can also be used to indicate early warning signs of critical transitions in ice shelves as seen from remote sensing data. We apply a directed spectral clustering methodology, including an asymmetric affinity matrix and the associated directed graph Laplacian, to reprocess the ice velocity data and remote sensing satellite images of the Larsen C ice shelf. Our tool has enabled the simulated prediction of historical events from historical data and fault lines responsible for the critical transitions leading to the breakup of the Larsen C ice shelf crack, which resulted in the A-68 iceberg. Such benchmarking of methods, using data from the past to forecast events that are now also in the past, is sometimes called post-casting, analogous to forecasting into the future. Our method indicated the coming crisis months before the actual occurrence.