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

<p>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 (AM...

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Bibliographic Details
Main Authors: H. Nye, A. Condron
Format: Article
Language:English
Published: Copernicus Publications 2021-06-01
Series:Climate of the Past
Online Access:https://cp.copernicus.org/articles/17/1409/2021/cp-17-1409-2021.pdf
Description
Summary:<p>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 <span class="inline-formula">∼</span> 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.</p>
ISSN:1814-9324
1814-9332