Dynamic Greenland ice sheet driven by pCO2 variations across the Pliocene Pleistocene transition

Abstract

It is generally considered that the perennial glaciation of Greenland lasting several orbital cycles began around 2.7 Ma along with the intensification of Northern Hemisphere glaciation (NHG). Both data and model studies have demonstrated that a decline in atmospheric pCO2 was instrumental in establishing a perennial Greenland ice sheet (GrIS), yet models have generally used simplistic pCO2 constraints rather than data-inferred pCO2 evolution. Here, using a method designed for the long-term coupling of climate and cryosphere models and pCO2 scenarios from different studies, we highlight the pivotal role of pCO2 on the GrIS expansion across the Plio-Pleistocene Transition (PPT, 3.0–2.5 Ma), in particular in the range between 280 and 320 ppm. Good qualitative agreement is obtained between various IRD reconstructions and some of the possible evolutions of the GrIS simulated by our model. Our results underline the dynamism of the GrIS waxing and waning under pCO2 levels similar to or lower than today, which supports recent evidence of a dynamic GrIS during the Plio-Pleistocene.

An energy balance model for paleoclimate transitions

“…Even for changes as recent as the mid-Holocene, there is a debate, for example, over whether the abrupt desertification of the Sahara is due to a bifurcation, as suggested in Claussen et al (1999) using an Earth model of intermediate complexity (EMIC), or is a transient response of the AMOC to a sudden termination of freshwater discharge to the North Atlantic, as proposed in Liu et al (2009), using a coupled atmosphere-ocean GCM (AOGCM). Similarly, for the glaciation of Greenland at the Pliocene-Pleistocene transition, recent work in Tan et al (2018), using a coupled GCM-ice-sheet model, shows good agreement with proxy records without the need for bifurcations. The model of this paper does not adapt to these two situations, which are localized and away from the poles where the axis of symmetry restricts the dynamics and facilitates the analysis presented here.…”

“…They concluded that falling CO 2 levels were primarily responsible for the formation of the Greenland ice sheet in the late Pliocene. Recently, Tan et al (2018) have strengthened this conclusion.…”

“…The change from an ice-free to an ice-covered condition in the Arctic occurred abruptly, during the late Pliocene and early Pleistocene. This is sometimes called the Pliocene-Pleistocene transition (PPT 3.0-2.5 Ma; Willeit et al, 2015;Tan et al, 2018). It has been a longstanding challenge to explain this dramatic change in the climate; however, significant progress has been made recently for the case of the Greenland ice sheet (GIS).…”

“…The authors of Willeit et al (2015) have solved the "inverse problem" for the GIS by finding a schematic pCO 2 concentration scenario from an ensemble of transient simulations using an EMIC that gives the best fit to data from 3.2 to 2.4 Ma, taking into account the obliquity cycle. Meanwhile, Tan et al (2018) have used an AOGCM asynchronously coupled with sophisticated ice sheet models to reproduce the waxing and waning of the GIS across the PPT, obtaining good qualitative agreement with ice rafted debris data reconstructions. Currently, there is great interest in the mid-Pliocene climate, because it is the most recent paleoclimate that resembles the future warmer climate now predicted for the Earth.…”

Back to the Future: Using Long-Term Observational and Paleo-Proxy Reconstructions to Improve Model Projections of Antarctic Climate

“…Atmospheric concentrations of CO 2 can be retrieved from Antarctic ice core records back to about 850 ka (e.g., [36]) ( Figure 1). However, a recent study shows that uncertainties in CO 2 reconstruction of the Late Pleistocene are non-negligible [59], leading to large differences between models, especially in the case of ice sheet glaciation and deglaciation thresholds [60]. For pre-ice-core records, CO 2 reconstructions are retrieved from sediment cores, with large uncertainties (Figure 1, e.g., [39]).…”