Semi‐automatic Ice Rafted Debris quantification with Computed Tomography

Sedimentary ice-rafted debris (IRD) provides critical information about the climate sensitivity and dynamics of ice sheets. In recent decades, high-resolution investigations have revelated ice rafting events in response to rapid warming: such reconstructions help us constrain the near-future stabili...

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Bibliographic Details
Published in:Paleoceanography and Paleoclimatology
Main Authors: Cederstrøm, Jan Magne, Bilt, Willem Godert Maria van der, Støren, Eivind Wilhelm Nagel, Rutledal, Sunniva
Format: Article in Journal/Newspaper
Language:English
Published: American Geophysical Union 2021
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Online Access:https://hdl.handle.net/11250/2832045
https://doi.org/10.1029/2021PA004293
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Summary:Sedimentary ice-rafted debris (IRD) provides critical information about the climate sensitivity and dynamics of ice sheets. In recent decades, high-resolution investigations have revelated ice rafting events in response to rapid warming: such reconstructions help us constrain the near-future stability of our planet's fast-changing cryosphere. However, similar efforts require laborious and destructive analytical procedures to separate and count IRD. Computed tomography (CT) holds great promise to overcome these impediments to progress by enabling the micrometer-scale (max. ∼21 μm) visualization of individual IRD grains. This study demonstrates the potential of this emerging approach by (a) validating CT counts in synthetic sediment archives (phantoms) spiked with a known number of grains, (b) replicating published IRD stratigraphies, and (c) improving sampling resolution. Our results show that semi-automated CT counting of grains in the often analyzed 150–500 μm size fraction reproduces grain numbers and tracks manually counted trends. We also find that differences between manual and CT-counted data are explained by image processing artifacts, offsets in sampling resolution, and bioturbation. By acquiring these promising results using basic image processing tools, we argue that our work advances and broadens the applicability of ultra-high resolution IRD counting with CT to deepen our understanding of ice sheet-climate interactions on human-relevant timescales. publishedVersion