Assessing the statistical uniqueness of the Younger Dryas: a robust multivariate analysis

• Published in: Climate of the Past
• Main Authors: Nye, Henry, Condron, Alan
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: European Geosciences Union 2021
• Subjects: Greenland; Reu; Ice Sheet; North Atlantic
• Online Access: https://hdl.handle.net/1912/27633

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nye, H., & Condron, A. Assessing the statistical uniqueness of the Younger Dryas: a robust multivariate analysis. Climate of the Past, 17(3), (2021): 1409–1421, https://doi.org/10.5194/cp-17-1409-2021. During the last glacial period (ca. 120–11 kyr BP), dramatic temperature swings, known as Dansgaard–Oeschger (D–O) events, are clearly manifest in high-resolution oxygen isotope records from the Greenland Ice Sheet. Although variability in the Atlantic Meridional Overturning Circulation (AMOC) is often invoked, a unified explanation for what caused these “sawtooth-shaped” climate patterns has yet to be accepted. Of particular interest is the most recent D–O-shaped climate pattern that occurred from ∼ 14 600 to 11 500 years ago – the Bølling–Allerød (BA) warm interstadial and the subsequent Younger Dryas (YD) cold stadial. Unlike earlier D–O stadials, the YD is frequently considered a unique event, potentially resulting from a rerouting and/or flood of glacial meltwater into the North Atlantic or a meteorite impact. Yet, these mechanisms are less frequently considered as the cause of the earlier stadials. Using a robust multivariate outlier detection scheme – a novel approach for traditional paleoclimate research – we show that the pattern of climate change during the BA/YD is not statistically different from the other D–O events in the Greenland record and that it should not necessarily be considered unique when investigating the drivers of abrupt climate change. In so doing, our results present a novel statistical framework for paleoclimatic data analysis. This research has been supported by the National Science Foundation (grant no. NSF REU OCE-1852460).