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We have a new study out that looks at the fate of East Rongbuk Glacier under the current range of IPCC Shared Socioeconomic Pathways (SSPs). East Rongbuk Glacier is located on the north slope of Mount Everest, also called Chomolungma, where the climate is very cold and dry. The relatively little snowfall at East Rongbuk Glacier makes it sensitive to small increases in surface melt associated with climate change. Many different glaciological observations, including surface mass balance, ice thickness and ice temperature, have been collected at East Rongbuk Glacier by different teams working at the site over many years. This makes it a relatively data rich glacier site within high mountain Asia.

In this study, we simulate East Rongbuk Glacier with an ice flow model. The surface forcing of the ice flow model is the magnitude and spatial distribution of accumulation and ablation, as well as surface temperatures. We use climate data from ten different CIMP6 ensemble members as surface forcing. The model then simulates the thickness, temperature and velocity of the glacier that fits with this surface forcing. Once we ensure that the model simulates the present-day glacier thickness, temperature and velocity, as well as recently observed ice loss, we apply the SSP-126 (low emissions), SSP-370 (middle of the road) and SSP-585 (high emissions) climate projections of the CIMP6 ensemble. The model then simulates the changing form and flow of the glacier under these future scenarios.

Although we use ten CMIP6 climate forcings, we generally focus on the pattern revealed by the ensemble mean, rather than any one particular CMIP6 climate projection. We find that under the SSP-126 scenario, East Rongbuk Glacier will likely experience maximum, or peak, meltwater runoff around 2030. About 55% of the glacier volume will remain at the end of this century. Under the SSP-370 and SSP-585 scenarios, the peak water will likely occur around 2060. Under these scenarios, less than 30% of the glacier volume will remain at the end of this century. While glacier volume less per year is decreasing by the end of the century under SSP-126, it is still decreasing quite rapidly under SSP-370 and SSP-585. This suggests that adopting SSP-126 would have a significant impact on stabilizing the volume of East Rongbuk Glacier. This may be characteristic of broadly similar glaciers in high mountain Asia.

We do a variety of simulations to test the sensitivity of these projections against assumptions of the model. These sensitivity simulations highlight the importance of including ice dynamics, which change glacier geometry, when projecting meltwater runoff decades into the future. Many projections of glacier runoff in high mountain Asia do not yet include changes in ice geometry over time. While important, however, the impact of incorporating ice dynamics into glacier projections is still limited in comparison to the choice of climate forcing. Individual members of the CMIP6 climate forcing ensemble can yield very different projections. For example, a “high sensitivity” CMIP6 member suggests that East Rongbuk Glacier may disappear completely by the end of the century under SSP370, while a “low sensitivity” CMIP6 member suggests that 40% of the glacier may remain at the end of the century under SSP585. This highlights the substantial uncertainty in our present understanding of the fate of East Rongbuk Glacier.

Zhang, T., Wang, Y., Leng, W., Zhao, H., Colgan, W., Wang, C., Ding, M., Sun, W., Yang, W., Li, X., Ren, J., and Xiao, C. 2024. Projections of Peak Water Timing From the East Rongbuk Glacier, Mt. Everest, Using a Higher-Order Ice Flow Model. Earth’s Future. 12, e2024EF004545. https://doi.org/10.1029/2024EF004545

We have a new open-access study about geothermal heat flow beneath the Greenland and Antarctic ice sheets in the Journal of Geophysical Research: Earth Surface. 

Presently, there’s a lot of uncertainty about the magnitude and pattern of geothermal heat flow beneath both ice sheets. That’s because it has only been sampled at a handful of widely spaced deep ice cores (Figure 1). While the average value of geothermal heat flow is relatively small, getting it right is essential for ice-flow models. If you run a computer simulation of an ice sheet with a severe over- or under-estimation of the geothermal heat flow, you can easily end up generating an ice sheet that is either too warm or too cold. Ice flow is very sensitive to temperature – particularly near the bed – so geothermal heat flow is a critical variable for simulating the form and flow of Earth’s ice sheets.

Our study took a fresh look at changes in geothermal heat flow across space, but not those due to the subtle variations in Earth’s crust and mantle properties over tens of km. Instead, we examined the effect of the ice-sheet bed’s topographic relief on geothermal heat flow to generate the first comprehensive snapshot of changes in geothermal heat flow at scales of hundreds of meters due to that relief. It’s been known for over a century that geothermal heat flow is greater in valleys and smaller on ridges. Basically, if the heat escaping Earth’s interior is looking for the quickest way to radiate into the atmosphere, a deeply incised valley provides the fastest exit. This effect is readily observable from the fact that geotherms – surfaces of constant temperature – are packed more closely together beneath valleys, indicating a stronger temperature gradient there (and hence heat flow) in comparison to ridges.

We created a simple statistical model to estimate this topographic influence on geothermal heat flow. This model essentially uses a digital elevation model of the bedrock topography to assess local topographic relief and then converts this local relief into a fractional correction for geothermal heat flow. It produces a positive correction – an increase – for valleys, and vice versa for ridges. Our approach is admittedly simple and empirical – a literal “first-order” approximation – but it seems to reliably reproduce the topographic variability in geothermal heat flow in all the settings for which we could find previous studies. So, we applied this statistical model to digital elevation models for Greenland and Antarctica. This revealed much more detail in a geothermal heat flow map than we are used to seeing.

Across both Greenland and Antarctica, we see patterns of increased geothermal heat flow within deeply incised glacier valleys and decreased geothermal heat flow along ridges and mountains. In many regions, most notably the Antarctic Peninsula (Figure 2) and Central East Greenland (Figure 3), we find that local topography routinely modifies regional geothermal heat flow by more than ~50%.

In Greenland, we estimate that there are ~100 outlet glaciers that are both sufficiently narrow and deeply incised to more than double local geothermal heat flow relative to that of the regional average value. The model also suggests that – especially deep within the interior of the Greenland Ice Sheet – local geothermal heat flow may be sufficiently suppressed along prominent subglacial ridges to cause subglacial water to refreeze. (At least, in ice-sheet areas where the ice-bed interface is near the freezing point.) 

The topographic correction for geothermal heat flow that we model is only as a good as the topographic relief that we derive from subglacial digital elevation models. Generally, in areas where subglacial topography is best resolved, the effect of the topography on the local geothermal heat flow is greater than uncertainty in the underlying regional geothermal heat flow model (Figure 4). There are still large swaths of the ice sheets where subglacial topography remains poorly resolved. In these areas, our model is not tremendously useful; the existing uncertainties between regional geothermal heat flow models are still larger than any local topographic correction that we can estimate.

The topographic corrections for geothermal heat flow in Greenland and Antarctica that we have calculated are now available as dimensionless fields in NetCDF format, with grids that are the same resolution as BedMachine, for each region via the PROMICE data portal (www.promice.dk). This means that they can be anonymously downloaded and applied to any regional geothermal heat flow model of the user’s choice. We hope that these topographic corrections for geothermal heat flow will be adopted into ice-flow models to improve both present-day ice-sheet simulations, as well as our understanding of the role of geothermal heat flow in the feedback between ice flow and topography on geologic timescales.

It has certainly been a long and winding road to this publication – the original draft of this article was first submitted in June 2019 – and we are grateful for Noah Finnegan (University of California Santa Cruz) and Olga Sergienko (Princeton University) for serving as editors to four very helpful peer-reviewers. Interdisciplinary projects can clearly provide a bumpier ride than staying in your own lane, but – in this instance – the journey seems to have taken us to a very different view of geothermal heat flow in Greenland and Antarctica.

Development of this data product was funded by the award “HOTROD: Prototype for Rapid Sampling of Ice-Sheet Basal Temperatures” provided by the Experiment Programme of the Villum Foundation. Improved understanding of the spatial variability in subglacial geothermal heat flow helps us optimize drill site selection and analyze ice temperature measurements. This data product was also supported by the Danish Ministry for Climate, Energy and Supplies through the Programme for Monitoring of the Greenland Ice Sheet (PROMICE).

Colgan, W., J. MacGregor, K. Mankoff, R. Haagenson, H. Rajaram, Y. Martos, M. Morlighem, M. Fahnestock and K. Kjeldsen. 2021. Topographic Correction of Geothermal Heat Flux in Greenland and Antarctica. Journal of Geophysical Research. 125: e2020JF005598. doi:10.1029/2020JF005598.