| 25 Jun 2026
Ensemble reconstruction of the Greenland Ice Sheet evolution through the last deglaciation
Abstract. The last deglaciation offers valuable insights into ice-climate interactions, as extensive paleoclimatic records document the retreat of ice sheets through a period of major climate changes. During this interval, the Greenland Ice Sheet (GrIS) retreated from its extensive Last Glacial Maximum (LGM) configuration to its present state, passing through the Holocene Thermal Maximum (HTM), when temperatures exceeded present-day values. Despite the large amount of paleoclimatic data available, ice-sheet models struggle to reproduce key aspects of the observational record, and the magnitude of the GrIS contribution to sea level throughout this period, in particular during the LGM and the HTM, remains highly uncertain. In this study, we evaluate an ensemble of 3,000 simulations of the GrIS performed with the Yelmo ice-sheet model against different observational constraints. These include: (1) the LGM ice-sheet extent, (2) ice-core-derived surface elevations, (3) an ice-extent retreat chronology based on the recent PaleoGrIS dataset, and (4) the present-day ice-sheet configuration (ice thickness, ice cover, ice-surface velocity, and bedrock elevation). We characterize the impact of the parameters perturbed along the ensemble on the GrIS evolution using an emulator based on the XGBoost algorithm combined with the SHAP (SHapley Additive exPlanations) framework. This analysis reveals that the climatic parameters (surface melting corrections and ocean thermal sensitivity) dominate the impact. By identifying the simulation that best matches these observables, we provide a constrained reconstruction of the GrIS during the last deglaciation that substantially improves upon previous reconstructions. We obtain a GrIS contribution to global sea level with respect to present of -5.75 m of sea-level equivalent (SLE) at the LGM (with an uncertainty range of -3.93 to -6.31 m) and +0.45 m after the HTM warming (with an uncertainty range of 0.43 to 1.18 m). This is in the upper range of previously existing estimates, indicating a comparatively mid-to-high GrIS sensitivity to climate changes over the last deglaciation.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Climate of the Past.
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This manuscript by Gutiérrez-González presents a large ensemble of simulations of Greenland Ice Sheet deglaciation and regrowth from the Last Glacial Maximum (LGM) through present. From the large ensemble (original simulations are actually from Tabone et al., 2024 which many of the authors here are also on), the authors single out the best-fit simulation against a suite a metrics used to assess to model performance while at the same appropriately highlighting the range of ensemble results and the specific model parameters controlling the full range of results. The authors use their best-fit simulation and exploration of model parameter space to highlight 1) surface melting corrections and ocean thermal sensitivity as having the most dominant control on model output, 2) estimate of the ice sheet’s sea-level equivalent (SLE) at the LGM, and 3) SLE at its minimum Holocene extent. These latter points, arguably, being of particular importance as they are values that are often discussed and debated in the literature.
This is an excellent paper. A very thorough piece of work that was a pleasure to read. Paper is well written and the figures are excellent. Figures do a great job at conveying information while being aesthetically pleasing. And, as a paleo person (I am not a modeler) I found the LGM and mid-Holocene reconstructions particularly interesting and commend the authors for doing a great job and discussing their results within the context of the geological record. Excellent stuff.
This paper is obviously suitable for Climate of the Past and I can’t imagine the authors receiving much resistance in publishing this. Below I have a number of light to moderate comments and suggestions for the authors but, again, this is an excellent manuscript.
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Lines 25-27: I found these two sentences oddly structured. Perhaps the word “nevertheless” is making this seem like a bigger mystery than it really is? The authors could even think about just starting with the second sentence minus “nevertheless”
Line 49: I don’t think you need to start a new paragraph here.
Line 71-73: Yes, I agree, but this also seems like a slightly too negative way to cast this. There are tradeoffs with every simulation and no simulation hits all the benchmarks, including the author’s own here.
Modelling framework section:
The ensemble combines atmospheric temperature anomalies from Buizert et al. (2018) with precipitation
anomalies from Badgeley et al. (2020). Could the authors elaborate on the rationale for selecting the Buizert temperature reconstruction rather than the Badgeley temperature reconstruction, given that the precipitation forcing is taken from Badgeley? The two temperature reconstructions differ during climatically important intervals, including the Younger Dryas and the early Holocene, which could influence the simulated timing and magnitude of deglaciation. To what extent might the inferred ice-sheet evolution and best-fit simulation depend on the choice of temperature reconstruction? Related, what is the rationale behind the “high-precipitation” scenario from Badgeley vs. the moderate or low scenarios?
The best-performing parameter set is identified using a single prescribed climate forcing (Buizert temperature anomalies and Badgeley precipitation anomalies). Because several perturbed parameters directly modulate the ice sheet response to climate (e.g., melt corrections, precipitation scaling, and ocean sensitivity), to what extent are the inferred optimal parameter values specific to this forcing? If an alternative paleoclimate reconstruction were adopted, would the calibrated parameter values shift substantially? Additionally, because the SHAP analysis identifies parameter importance within the context of the prescribed forcing, it is unclear whether the inferred parameter sensitivities and perhaps even the SHAP importance rankings themselves would be transferable across alternative climate reconstructions. A brief discussion of this limitation would help clarify the robustness and generality of the conclusions. More broadly, I think it’s worth mentioning or highlighting that the authors here have essentially taken fixed climatology and then sampled model parameter space to achieve a best-fit to the observations while there is also the near-opposite approach of sampling climate space to see of that alone can produce a good fit to the observations (i.e., Briner et al., 2020; Cuzzone et al., pre-print/in review; https://doi.org/10.21203/rs.3.rs-9962320/v1)
Figure 1: Did you want the HTM blue box to come all the way down to the x-axis? Double check
Line 252: Slightly confused here. I don’t think the fit to the Leger product was weighted more heavily, but here makes it sound like it is? Not entirely sure, very possible it is weighted more towards a Leger fit (which is fine) and I missed it.
Line 264-265 and Figure 3: I found the relative poorness of fit in SW Greenland extremely interesting as 1) SW Greenland has the most paleo observations in all of Greenland by a comfortable margin (authors might actually mention this) and 2) it’s probably the region of Greenland least affected by dynamical processes (primarily land-based, KNS region excluded, at least relative to other regions) and mostly controlled by SMB (which is partly why the fit in Briner et al., 2020 is good)…and yet the fit here is relatively poor. Authors could highlight this point, possibly expanded on this with a few sentences. Or maybe at the very least point to section below where they speculate that the climate input is too warm in this region?
Table 4: Likely due to my lack of model knowledge…how “reasonable” are these parameter fits? Is there any single value(s) that are pushing the limits of what is typically accepted/used for each of these parameters?
Figure 5: Why not change the timing of panel G to the actual minimum you reconstruct? I know the difference between the 5 ka and the actual minimum at 4.8 ka is negligible, but it seems odd to me to have 5 ka instead of the 4.8 ka that most people are going to care about.
Line 331: Could add the Sbarra reference in here, and probably Jennings et al., 2017 (v. 472; EPSL) and Ó Cofaigh et al., 2013 (v. 41 (2) Geology). All of these pretty strongly support LGM ice at the shelf edge.
Line 353-355: I don’t think this is necessarily the best way to cast this. I think it’s fairly well known that the minimum extent, whenever it is, falls after peak HTM temperatures but…of course it does? The ice sheet is still so large and has so much inertia that the minimum almost must fall after the HTM. And, of course the ice sheet was indeed retreating/losing mass during the HTM. A more appropriate way to think about this might be looking at the ***rate*** of mass loss. Rates are almost certainly higher during the actual HTM.
Line 359: You can just start this paragraph with ‘At 4.8 ka..”
Line 400-403: Does this suggest the best-fit LGM sea-level equivalent is not a robust estimate?
Line 529-530: Could add Cuzzone et al., 2022 (The Cryosphere, v. 16) here. They investigated this very idea in the KNS system and still couldn’t achieve a great fit with the observations.
Line 563-564: See the last 1/3 of my second modeling framework comment above.
Figure 14 (and related text): It seems like the authors’ model is perhaps more sensitive than other set-ups? Their LGM SLE is towards the higher end of the range of estimates and, conversely, their SLE for the Holocene minimum is also towards the high end? Best fit = both “big” LGM ice and “small” mid Holocene ice.
Line 595-597 and again down ~619-622 and ~635: I might couch all of this a bit differently. I think the authors reconstructions are consistent with all other simulations, that is, they tend to show quite a bit of retreat in SW Greenland during the Holocene. But I also think all of the geological benchmarks over the last ~15 years point to rather limited retreat. So if the question is how far exactly did the ice margin retreat, then it’s a bit unknown, but if the question is did it retreat “a lot” (models) or “not that much” (paleo observations) then I’m not sure I’d call it an “open question” (its not that much).
Holocene minimum SLE – if the best-fit simulation likely overshoots SW Greenland inland retreat, the same region thought to be the primary contributor to SLE during this interval (which the authors fully acknowledge), is the 0.45m SLE itself too high then? Should this (and the full range presented by the authors) be considered a maximum value?