The contribution of Humboldt Glacier, North Greenland, to sea-level rise through 2100 constrained by recent observations of speedup and retreat

Hillebrand, Trevor R.; Hoffman, Matthew J.; Perego, Mauro; Price, Stephen F.; Howat, Ian M.

doi:https://doi.org/10.5194/tc-2022-20

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https://doi.org/10.5194/tc-2022-20

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23 Mar 2022

Status: this preprint is currently under review for the journal TC.

The contribution of Humboldt Glacier, North Greenland, to sea-level rise through 2100 constrained by recent observations of speedup and retreat

Trevor R. Hillebrand¹, Matthew J. Hoffman¹, Mauro Perego², Stephen F. Price¹, and Ian M. Howat^3,4 Trevor R. Hillebrand et al.

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¹Fluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
²Center for Computing Research, Sandia National Laboratories, Albuquerque, NM 87185, USA
³Byrd Polar and Climate Research Center, Columbus, OH, 43210, USA
⁴School of Earth Sciences, Ohio State University, Columbus, OH, 43210, USA

Received: 02 Feb 2022 – Discussion started: 23 Mar 2022

Abstract. Humboldt Glacier, North Greenland, has retreated and accelerated through the 21st century, raising concerns that it could be a significant contributor to future sea-level rise. We use a data-constrained ensemble of three-dimensional higher-order ice sheet model simulations to estimate the likely range of sea-level rise from the continued retreat of Humboldt Glacier. We first solve for basal traction using observed ice thickness, bed topography, and ice surface velocity from the year 2007 in a partial differential equation constrained optimization. Next, we impose calving rates to match mean observed 2007–2017 retreat rates in a transient calibration of the exponent in the power-law basal friction relationship. We find that power law exponents in the range of 1/7–1/5 — rather than the commonly used 1/3–1 — are necessary to reproduce the observed speedup over this period. We then tune an iceberg calving parameterization based on the von Mises stress yield criterion in another transient calibration step from 2007–2017 to approximate both observed ice velocities and terminus position in 2017. Finally, we use the range of basal friction relationship exponents and calving parameter values to generate the ensemble of model simulations from 2007–2100 under three climate forcing scenarios from CMIP5 (two RCP 8.5 forcings) and CMIP6 (one SSP5-8.5 forcing). Our simulations predict 5.5–9.2 mm of sea-level rise from Humboldt Glacier, significantly higher than a previous estimate (~3.5 mm) and equivalent to a substantial fraction of the 40–140 mm predicted by ISMIP6 from the whole Greenland Ice Sheet. Our larger future sea-level rise prediction results from the transient calibration of our basal friction law to match the observed 2007–2017 speedup, which requires a semi-plastic bed rheology. In many simulations, our model predicts the growth of a sizable ice shelf in the middle of the 21st century. Thus, atmospheric warming could lead to more retreat than predicted here if increased surface melt promotes hydrofracture of the ice shelf. Our data-constrained simulations of Humboldt Glacier underscore the sensitivity of model predictions of Greenland outlet glacier response to warming to choices of basal shear stress and iceberg calving parameterizations. Further, transient calibration of these parameterizations, which has not typically been performed, is necessary to reproduce observed behavior. Current estimates of future sea-level rise from the Greenland Ice Sheet could, therefore, contain significant biases.

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RC1: 'Comment on tc-2022-20', Anonymous Referee #1, 09 May 2022 reply

Authors present numerical simulations of mass loss from Humboldt Glacier. Historical runs and observations (2007-2017) are used to constrain parameters in the description of basal rheology and the calving law. Optimal model parameters are used to produce projections of mass loss for a range of future forcing scenarios (2017-2100). Results highlight the importance of the basal sliding exponent, and best estimates of mass loss exceed previous projections by about a factor of 2.

The objectives and methodology of this study are clear; the results novel and well-presented; the conclusions well-supported, and overall this work is a good fit to The Cryosphere. I recommend publications with scope for some minor revisions, as outlined below.

The experimental design is mostly straightforward and easy to follow, though I wonder about the need to distinguish between the perturbed parameter ensemble, and the additional sensitivity experiments. After all, these are all sensitivity experiments, and personally I think the distinction overcomplicates the structure of the paper. An overview of the sensitivity to all physical parameters in a single Table would be nice. Some experiments that do not test the significance of physical parameters, such as the mesh resolution and potentially, bed topo, could be included in an Appendix to reduce the amount of information in the main text.

The validation approach is interesting, though I miss a more in-depth description/motivation of the validation criteria. Fig3b suggests that the optimal choice of q is critically dependent on the velocity itself, so why choose 1/5-1/7, which only provides a best match for u>600m/yr? In this regard, you might find the discussion in section 3.3 of [De Rydt et al. 2021] of interest, where authors show that the optimal sliding exponent for Pine Island Glacier is spatially heterogeneous. On a related note, I wonder if you can show the difference between observations and model in Fig3a, rather than the absolute model speed.

I think some further details about the melting and calving paramterization would be instructive for readers less familiar with the different (model) approaches. For example, in line 151: can you be more explicit about what you mean by ‘if there is no floating ice’, line 146-150 and 160-170: how does this discussion relate to quantities displayed in figure 2 (e.g. I’m unsure how ‘mean ocean thermal forcing’ is translated into a depth-dependent parameterization of melt), section 2.5: how is the calving front tracked in the model, and what happens to ice that has calved – is a minimum ice thickness applied?

Line 274 you refer to Table 1 here, but this table does not contain any information on SLR. Also, is there a reason why \sigma_max for q=1/7 in Table 1 is different between MIROC5 and the other forcing scenarios?

Line 427 I assume you are using annually averaged velocities, rather than seasonal products, for the 2007 initialization and 2017 validation? Given the large amplitude of seasonal speed-up/slow-down along this section of Greenland’s margin, how important is the choice of velocity product? In lines 590-595 you allude to possible important implications, but can you provide quantitative insights in how alternative intialization approaches (e.g. by using summer-only values of surface speed) might alter/bias your results?

FigS1. Can you provide a legend for the different colours please?

Ref.

De Rydt, J., Reese, R., Paolo, F. S., and Gudmundsson, G. H.: Drivers of Pine Island Glacier speed-up between 1996 and 2016, The Cryosphere, 15, 113–132, https://doi.org/10.5194/tc-15-113-2021, 2021

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Citation: https://doi.org/10.5194/tc-2022-20-RC1

Trevor R. Hillebrand et al.

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https://doi.org/10.5194/tc-2022-20-supplement

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MPAS-Albany Land Ice model simulations of Humboldt Glacier, North Greenland, from 2007–2100 Trevor R. Hillebrand, Matthew J. Hoffman, Mauro Perego, Stephen F. Price https://doi.org/10.5281/zenodo.6338400

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Trevor R. Hillebrand et al.

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Short summary

We estimate that Humboldt Glacier, North Greenland, will contribute 5.5–9 mm to global sea-level from 2007–2100, using an ensemble of model simulations constrained by observations of glacier retreat and speedup. This is a significant fraction of the 40–140 mm from the whole Greenland Ice Sheet predicted by the recent ISMIP6 multi-model ensemble, suggesting that calibrating models against observed velocity changes could result in higher estimates of 21st century sea-level rise from Greenland.


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