Abstract

Data availability and temporal resolution make it challenging to unravel the anatomy (duration and temporal phasing) of the Last Glacial abrupt climate changes. Here, we address these limitations by investigating the anatomy of abrupt changes using sub-decadal-scale records from Greenland ice cores. We highlight the absence of a systematic pattern in the anatomy of abrupt changes as recorded in different ice parameters. This diversity in the sequence of changes seen in ice-core data is also observed in climate parameters derived from numerical simulations which exhibit self-sustained abrupt variability arising from internal atmosphere-ice-ocean interactions. Our analysis of two ice cores shows that the diversity of abrupt warming transitions represents variability inherent to the climate system and not archive-specific noise. Our results hint that during these abrupt events, it may not be possible to infer statistically-robust leads and lags between the different components of the climate system because of their tight coupling.

Highlights

  • Data availability and temporal resolution make it challenging to unravel the anatomy of the Last Glacial abrupt climate changes

  • A simple visual observation of the two records suggests that the variability is slightly smaller in NEEM compared with NGRIP

  • The difference is related to the influence on flow-induced thinning of the presence of bottom melting at NGRIP5,38, which results in NGRIP annual layers being thicker by a factor of 1.5–2 compared with NEEM during most of the Glacial[38]

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Summary

Introduction

Data availability and temporal resolution make it challenging to unravel the anatomy (duration and temporal phasing) of the Last Glacial abrupt climate changes We address these limitations by investigating the anatomy of abrupt changes using sub-decadal-scale records from Greenland ice cores. The mechanisms proposed to explain D-O event dynamics can be confronted with annual-to-decadal-scale observations of climatic changes across the globe over the GS–GI transitions Such data sets provide a basis to map out the sequence of events, infer possible causal relations and evaluate hypothetical sets of governing mechanisms by comparing model output with the spatial expression and relative phasing of the observed changes, hereafter referred to as the “anatomy” of the changes

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