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001052666 1001_ $$0P:(DE-HGF)0$$aRiechers, Keno$$b0
001052666 245__ $$aDiscontinuous stochastic forcing in Greenland ice core data
001052666 260__ $$aHeidelberg$$bSpringer$$c2025
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001052666 520__ $$aPaleoclimate 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.
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001052666 536__ $$0G:(DE-Ds200)HGF-ZT-I-0029$$aHGF-ZT-I-0029 - Helmholtz UQ: Uncertainty Quantification - from data to reliable knowledge (HGF-ZT-I-0029)$$cHGF-ZT-I-0029$$x2
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001052666 7001_ $$0P:(DE-HGF)0$$aMorr, Andreas$$b1$$eCorresponding author
001052666 7001_ $$0P:(DE-HGF)0$$aLehnertz, Klaus$$b2
001052666 7001_ $$0P:(DE-HGF)0$$aLind, Pedro G.$$b3
001052666 7001_ $$0P:(DE-HGF)0$$aBoers, Niklas$$b4
001052666 7001_ $$0P:(DE-Juel1)162277$$aWitthaut, Dirk$$b5
001052666 7001_ $$0P:(DE-HGF)0$$aGorjão, Leonardo Rydin$$b6
001052666 773__ $$0PERI:(DE-600)1471747-5$$a10.1007/s00382-025-07880-9$$gVol. 63, no. 12, p. 465$$n12$$p465$$tClimate dynamics$$v63$$x0930-7575$$y2025
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