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 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. Plain Language Summary Chunks of ice regularly break off glaciers floating in the ocean. These icebergs contain rock fragments and mineral grains picked up during the journey from land to water. As icebergs drift into warmer waters and melt, this rubble sinks to the bottom and settles on the ocean floor. Detection of these particles in marine sediments thus provides evidence that glacial ice reached down to sea level. The flux of this ice‐rafted debris (IRD) gives researchers information about the past behavior of glaciers. As our planet warms, melting glaciers have become important drivers of sea‐level rise. IRD studies can therefore help us better adapt to rising sea levels. But to do so on timescales relevant for humans, researchers have to extract thousands of samples from meters of sediment and sieve out IRD grains before manually counting them. Faster approaches would greatly ease the workload. In this study, we present a promising way to do so with the help of a medical technique: computed tom