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@ARTICLE{Riechers:1052666,
author = {Riechers, Keno and Morr, Andreas and Lehnertz, Klaus and
Lind, Pedro G. and Boers, Niklas and Witthaut, Dirk and
Gorjão, Leonardo Rydin},
title = {{D}iscontinuous stochastic forcing in {G}reenland ice core
data},
journal = {Climate dynamics},
volume = {63},
number = {12},
issn = {0930-7575},
address = {Heidelberg},
publisher = {Springer},
reportid = {FZJ-2026-01038},
pages = {465},
year = {2025},
abstract = {Paleoclimate proxy records from Greenland ice cores,
archiving e.g. d18O as a proxy for surface temperature, show
that sudden climatic shifts called Dansgaard–Oeschger
events (DO) occurred repeatedly during the last glacial
interval. They comprised substantial warming of the Arctic
region from cold to milder conditions. Concomitant abrupt
changes in the dust concentrations of the same ice cores
suggest that sudden reorganisations of the hemispheric-scale
atmospheric circulation have accompanied the warming events.
Genuine bistability of the North Atlantic climate system is
commonly hypothesised to explain the existence of stadial
(cold) and interstadial (milder) periods in Greenland.
However, the physical mechanisms that drove abrupt
transitions from the stadial to the interstadial state, and
more gradual yet still abrupt reverse transitions, remain
debated. Here, we conduct a one-dimensional data-driven
analysis of the Greenland temperature and atmospheric
circulation proxies under the purview of stochastic
processes. We take the Kramers–Moyal equation to estimate
each proxy’s drift and diffusion terms within a Markovian
model framework. We then assess noise contributions beyond
Gaussian white noise. The resulting stochastic differential
equation (SDE) models feature a monostable drift for the
Greenland temperature proxy and a bistable one for the
atmospheric circulation proxy. Indicators of discontinuity
in stochastic processes suggest to include higher-order
terms of the Kramers–Moyal equation when modelling the
Greenland temperature proxy’s evolution. This constitutes
a qualitative difference in the characteristics of the two
time series, which should be further investigated from the
standpoint of climate dynamics.},
cin = {ICE-1},
ddc = {550},
cid = {I:(DE-Juel1)ICE-1-20170217},
pnm = {1121 - Digitalization and Systems Technology for
Flexibility Solutions (POF4-112) / HDS LEE - Helmholtz
School for Data Science in Life, Earth and Energy (HDS LEE)
(HDS-LEE-20190612) / HGF-ZT-I-0029 - Helmholtz UQ:
Uncertainty Quantification - from data to reliable knowledge
(HGF-ZT-I-0029)},
pid = {G:(DE-HGF)POF4-1121 / G:(DE-Juel1)HDS-LEE-20190612 /
G:(DE-Ds200)HGF-ZT-I-0029},
typ = {PUB:(DE-HGF)16},
doi = {10.1007/s00382-025-07880-9},
url = {https://juser.fz-juelich.de/record/1052666},
}