Preprints
https://doi.org/10.5194/npg-2020-26
https://doi.org/10.5194/npg-2020-26

  20 Jul 2020

20 Jul 2020

Review status: a revised version of this preprint was accepted for the journal NPG and is expected to appear here in due course.

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

Abd AlRahman AlMomani1,2 and Erik Bollt1,2 Abd AlRahman AlMomani and Erik Bollt
  • 1Department of Electrical and Computer Engineering, Clarkson University, Potsdam, NY 6 13699, USA
  • 2Clarkson Center for Complex Systems Science (C3S2), Potsdam, NY 13699, USA

Abstract. 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 reprocess the ice velocity data and 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. We can do so, months earlier before the actual occurrence, and also much earlier than any other previously available methodology, in particular those based on interferometry.

Abd AlRahman AlMomani and Erik Bollt

 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Abd AlRahman AlMomani and Erik Bollt

Abd AlRahman AlMomani and Erik Bollt

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Short summary
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 reprocess the ice velocity data and remote sensing satellite images of the Larsen C ice shelf.