BLOG

ice sheet

Geothermal Influence on Basal Ice Temperatures

Posted by William Colgan on January 28, 2024
Climate Change, Communicating Science, New Research / No Comments

We have a new open-access study out in the current volume of The Cryosphere that looks at geothermal heat flow beneath the Greenland Ice Sheet. Geothermal heat flow is an important boundary condition for ice flow models because it influences the temperature of the ice-bed interface, which in turn influences how easily ice can deform and flow. Right now, there are about seven widely used estimates of geothermal heat flow beneath the Greenland Ice Sheet (Figure 1). These different heat flow maps come from different research groups, using different methods. It hasn’t been entirely clear what the influence of choice of heat flow map has on modeled ice flow. For example, the ensemble of Greenland ice flow projections within the Ice-Sheet Model Inter-comparison Project for CMIP6 (ISMIP6) used differing heat flow maps. Our new study simply spins up a Greenland ice flow model with all seven heat flow maps and tries to understand the resulting differences in ice thickness and velocity.

Figure 1 – The differences in the magnitude and spatial distribution of geothermal heat flow, relative to ensemble mean, in the seven Greenland geothermal heat flow maps we assessed in this study.

Although the average geothermal heat flow only varies by about ±10 mW/m2 across the seven heat flow maps, there are pronounced variations in the spatial distributions of this heat flow. This means that there can be local heat flow differences of up to ±100 mW/m2 between individual heat flow maps. When the ice sheet model is spun up in a fully transient mode with these different heat flow maps, there are lots of areas where the difference in ice thickness from ensemble mean exceeds ±150 meters (Figure 2). This is due to spatial differences in basal ice temperatures, which strongly influence the viscosity and deformation of ice. Across the seven transient spin ups, the discharge of icebergs into the ocean varies by about ±10 gigatonnes per year, which is equivalent to about ±2.5% of the total ice-sheet iceberg discharge.

Figure 2 – The differences in ice thickness after a fully transient 10,000 year spin up, relative to ensemble mean, associated with the seven Greenland geothermal heat flow maps we assessed in this study.

We also spun up the ice flow model with the seven different heat flow maps under a so-called “nudged” spin up that was a key part of ISMIP6. Unlike a fully transient spin up, a “nudged” spin up constrains modeled ice thicknesses with observed ice thicknesses; it generally ensures a very realistic geometry for the simulated ice sheet. Although the ice geometry is more-or-less constant across these “nudged” simulations, there are still pronounced differences in the magnitude and spatial distribution of ice velocity. This largely results from large differences in the extents of the frozen and thawed ice-bed areas. Depending on choice of heat flow map, between 22 and 54% of the ice-bed area is simulated as thawed (Figure 3). This has strong implications for the proportion of the ice sheet beneath which water-dependent processes, like basal sliding, can occur.

Figure 3 – The differences in temperature at the ice-bed interface after a nudged ISMIP6-style spin up, relative to pressure melting point, associated with the seven Greenland geothermal heat flow maps we assessed in this study.

So, what is the way forward after showing that the choice of heat flow map has a non-trivial impact on Greenland ice sheet simulations? Well, deciding which heat flow map is “the best” is one approach. We highlight a small, but growing, database of in situ temperature measurements against which simulated ice temperatures can be compared. There are also qualitative hints as to which heat flow map might be most appropriate. For example, does it preserve the widespread frozen basal conditions that we find in North Greenland? In terms of community ice-sheet projections, we recommend that it may be prudent to limit the direct inter-comparison of ice-sheet simulations to those using a common heat-flow map. In terms of ISMIP specifically, we suggest that future ensemble should perhaps use a range of basal geothermal forcing scenarios, similar to how it employs a range climate forcing scenarios.

Zhang, T., Colgan, W., Wansing, A., Løkkegaard, A., Leguy, G., Lipscomb, W. H., and Xiao, C.: Evaluating different geothermal heat-flow maps as basal boundary conditions during spin-up of the Greenland ice sheet, The Cryosphere, 18, 387–402, https://doi.org/10.5194/tc-18-387-2024, 2024.

Tags: , , , , , , , , , ,

Bedrock Uplift from Greenland’s Peripheral Glaciers

Posted by William Colgan on January 16, 2024
Climate Change, Communicating Science, New Research / No Comments

We have a new article in the current issue of Geophysical Research Letters that looks at the influence of Greenland’s peripheral glaciers on vertical bedrock motion. Greenland’s bedrock is currently uplifting, due to both slow mantle-deformation processes associated with ice loss at the end of the Last Glacial Period, and fast elastic processes associated with ice loss today. The vertical bedrock uplift being measured in Greenland today ranges from a couple millimeters to a couple centimeters across the country. Understanding the magnitude and spatial distribution of this uplift helps us understand not only recent ice loss, but also properties of the Earth’s mantle beneath Greenland.

Figure 1 – Time series of the observed vertical land motion (VLM) at Mestersvig (MSVG) station in East Greenland. The elastic rebound associated with the Greenland Ice Sheet (GrIS), Greenland Peripheral Glaciers (GrPG) and Canadian Peripheral Glaciers (CanPG) are calculated. The post-Last Glacial Period glacioisostatic adjustment (U_GIA) is then calculated as a residual.

When folks create maps of Greenland’s present-day uplift rate, they typically use a model of changing ice-sheet geometry through time, to incorporate the effect of changing ice load on the Earth’s crust. This captures the main signal, but it ignores the cumulative effect of Greenland’s thousands of peripheral glaciers. These glaciers, which surround the ice sheet, also effect vertical bedrock motion. In this study, we also incorporate the effect of changing peripheral glacier geometry through time into uplift rates calculated at all the GNET bedrock motion sites around Greenland. In the figure above, you can see the vertical land motion budget of MSVG (Mestersvig) GNET station, which calculates post-Last Glacial Period glacioisostatic adjustment (GIA) as the residual of present-day elastic rebound.

Figure 2 – Comparison between post-Last Glacial Period glacioisostatic adjustment (GIA) that we calculate across the 58 GNET stations, compared to four widely used maps of Greenland GIA. A mismatch between the station color and the map color highlights a discrepancy between the previously calculated GIA and the GIA calculated in this study. These four previous studies used different methods, but all ignored the elastic rebound associated with peripheral glaciers.

We find that peripheral glaciers can have a disproportionately large impact on the elastic rebound of GNET sites, especially when they are located relatively far from the ice sheet. In some regions, especially in Greenland’s north and northeast, peripheral glaciers can contribute to over 20% of the total elastic response of regional GNET sites. Simply put, mapping Greenland’s present-day uplift rate with models that only incorporate the ice sheet, and not peripheral glaciers, can really underestimate the elastic rebound associated with present-day ice loss. Under estimating present-day elastic rebound can result in subsequently over estimating the post-Last Glacial Period glacioisostatic adjustment that is used to infer mantle properties.

So, perhaps the main message of this study is that although Greenland’s peripheral glaciers are quite small in comparison to the ice sheet, their recent collective ice loss can influence our understanding of Greenland’s vertical land motion in a disproportionately large way!

Open-Access Study: Berg, D., Barletta, V. R., Hassan, J., Lippert, E. Y. H., Colgan, W., Bevis, M., et al. (2024). Vertical land motion due to present-day ice loss from Greenland’s and Canada’s peripheral glaciers. Geophysical Research Letters, 51, e2023GL104851. https://doi.org/10.1029/2023GL104851

Tags: , , , , , , ,

Rainfall on the Greenland Ice Sheet

Posted by William Colgan on August 04, 2021
Climate Change, New Research / 2 Comments

We have a new open-access study in the current issue of Geophysical Research Letters that looks at rainfall over the Greenland Ice Sheet. In many places around the globe, rainfall is a big player in the water budget. But on the ice sheet, rainfall has traditionally been a small player in ice-sheet mass balance. In fact, virtually all of the automatic weathers stations deployed on the ice sheet today don’t even measure rainfall. These ice-sheet stations are instead optimized to measure accumulation from snowfall and ablation from melt. But, as major rainfall events are pushing higher and higher on to the ice sheet each year, that is starting to change. Today, there are a few research groups experimenting with different ice-sheet rainfall gauges.

Figure 1 – Average annual rainfall (left) and trend in annual rainfall (right) over the 1980 to 2019 period. Evaluation weather stations identified by WMO (World Meteorological Organization) numbers: Aasiaat (04220), Sisimiut (04230), Nuuk (04250), Narsarsuaq (34270), Danmarkshavn (34320), and Ittoqqortoormiit (34339).

In our new study, we simulate rainfall over the ice-sheet using a regional climate model. Specifically a “non-hydrostatic” model. This class of model is supposed to reproduce the continuum mechanics of atmospheric flow better than traditional “hydrostatic” models. The traditional hydrostatic models make some simplifying assumptions that can influence atmospheric flow and precipitation, especially across grid cells with high topographic relief. In the absence of ice-sheet rainfall observations, we compared the simulated rainfall to several weather stations operating in communities around Greenland’s coast. This comparison showed that the model could reasonably simulate the rainfall, including extreme events, that was observed at these weather stations. This gives us some confidence that the model’s rainfall physics are similarly faithful on the ice sheet.

Over the forty-year period 1981–2010, the model simulates increases in both rainfall and rainfall intensity, across the ice sheet and especially in late summer. We specifically find that total September rainfall increased by 224% over this period. The maximum intensity of September rainfall also increased by 54% during this same period. This is consistent with the expectation that the summer melt season will lengthen and intensify in a warming climate. Some of the most pronounced increases in rainfall were seen in Northwest Greenland. There, the rainfall fraction of precipitation is about twice the ice-sheet average. We speculate that this increasing trend in rainfall in Northwest Greenland may be related to a northward shift in the limit to which relatively warm and moist mid-latitude airmasses can penetrate each summer.

Figure 2 – September maximum hourly rainfall rates over the ice sheet and each sector. For the entire ice sheet (GrIS), as well as southeast (SE), south (S), and southwest (SW) sectors, linear trends are indicated together (dashed lines).

A large rainfall event can have a similar influence on ice dynamics as a large melt event. Once liquid meltwater enters the ice sheet, flowing in the en- and sub-glacial hydrology systems, there are myriad of ways it can make ice flow faster. Chief among these is warming and softening the ice (so the ice internally deforms and flow more easily) and pressurizing the subglacial hydrology system (so the ice-sheet slides more easily). For this reason, there is also an ice dynamic interest in big rainfall events. Some of the most pronounced increase in extreme rainfall events (i.e. >5 cm per hour) were in South Greenland. There, the ice sheet is most exposed to mid-latitude storms from the North Atlantic. There is an expectation for the intensity of storms to increase in a warming climate.

We will probably hear a lot more about rainfall on the Greenland Ice Sheet in the coming years. Hopefully, once some of the technical challenges are overcome, we will start to see the systematic collection of continuous rainfall measurements on the ice sheet. Given our current climate trajectory, we will also start to see rainfall comprising a larger portion of the annual ice-sheet water budget, especially in ice-sheet basins in South Greenland. There are already several studies linking rainfall events to ice motion at lower elevations, but presumably these links will also start to be made at higher elevations. There is a lot of research to do on the topic of ice-sheet rainfall!

M. Niwano, J. E. Box, A. Wehrlé, B. Vandecrux, W. T. Colgan and J. Cappelen. 2021. Rainfall on the Greenland Ice Sheet: Present-Day Climatology From a High-Resolution Non-Hydrostatic Polar Regional Climate Model. Geophysical Research Letters. https://doi.org/10.1029/2021GL092942.

Tags: , , , , , , ,

New View on Geothermal Heat Flow in Greenland and Antarctica

Posted by William Colgan on January 15, 2021
New Research / No Comments

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.

Figure 1 – Peering into the drill trench at the NEEM deep ice core site. NEEM is one of only six deep ice core sites in the Greenland Ice Sheet interior where geothermal heat flow has been measured to date.

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.

Figure 2 – Left: An existing regional geothermal heat flow model (Martos2017). Right: Regional geothermal heat flow corrected for local topographic relief.

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%.

Figure 3 – Left: An existing regional geothermal heat flow model (Martos2018). Right: Regional geothermal heat flow corrected for local topographic relief.

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.

Figure 4 – Maps of Antarctica and Greenland identifying areas, illustrated in red, where the influence of local topographic relief on geothermal heat flow is at least as important as the choice of geothermal heat flow model. As subglacial topography is still poorly resolved in both ice sheet interiors. These red areas may be expected to expand with improved mapping of subglacial topography.

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.

Tags: , , , , , , , , ,

28-Year Record of Greenland Ice Sheet Health

Posted by William Colgan on January 14, 2021
Climate Change, New Research, Sea Level Rise / No Comments

We have a new open-access study about Greenland Ice Sheet mass balance – or health – in the current issue of Geophysical Research Letters. In this study, we present a new 28-year record of ice-sheet mass balance. This record is relatively unique for two reasons.

Firstly, because of its length. The most recent ice-sheet mass balance inter-comparison exercise (IMBIE2) clearly highlighted how the availability of ice-sheet mass balance estimates has changed through time. During the GRACE satellite gravimetry era (2003-2017), there are usually more than twenty independent estimates of annual Greenland Ice Sheet mass balance. Prior to 2003, however, there are just two independent estimates. Our new 1992-2020 mass balance record will therefore provide especially welcomed additional insight on ice-sheet mass balance during the 1990s.

Figure 1 – Greenland Ice Sheet mass balance estimated by IMBIE2 between 1992 and 2018. The number of independent estimates comprising each annual estimate is shown. Prior to 2003, there are only 1 or 2 independent estimates of ice-sheet health each year.

Secondly, because of its consistency. This new mass balance record has been constructed by merging radar altimetry measurements from four ESA satellites (ERS-1/2, ENVISAT, CryoSat-2 and Sentinel-3A/B) over nearly three decades into one consistent framework. While all four of these satellites use the same type of Ku-band radar altimeter, to date, their measurements have usually been analyzed independently of each other. This time, however, we use machine learning to merge the elevation changes measured by these similar-but-different satellites into a common mass balance signal through space and time. This makes our new record the only satellite altimetry record that spans the entire IMBIE period.

Figure 2 – Comparison of our new multi-satellite radar-altimetry derived record of ice-sheet health (“Radar-VMB”) with two records estimated by the input-output method (“Colgan-IOMB” and “Mouginot-IOMB”), as well as one record estimated by satellite gravimetry (“GRACE-GMB”).

When we compare our new radar altimetry record of mass balance to two existing input-output records of mass balance, we find good agreement in the capture of Greenland’s high and low mass balance years. These other two multi-decade records are derived from the input-output method, in which estimated iceberg calving into the oceans is differenced from estimated surface mass balance (or net snow accumulation) over the ice sheet. While the input-output method often has limited spatial (and temporal) resolution, our radar altimetry derived record can resolve spatial variability in mass balance across the ice sheet every month since 1992.

Figure 3 – Our multi-satellite radar-altimetry derived map of declining ice-sheet health over the (a) the 1992-1999, (b) the 2000-2009, and (c) the 2010-2020 periods.

While our new long-term record provides a new overview of the health of the Greenland ice sheet, it can also be helpful to understand the processes that influence ice-sheet health. For example, we see a sharp increase in mass balance between 2016 and 2017. When we look at this event in detail, we can attribute it to unusually high snowfall in fall 2016, especially in East Greenland, and unusually little surface melting in summer 2017, throughout the ice-sheet ablation area. We estimate that the 2017 hydrological year was likely the first year during the 21st Century during which the ice sheet was actually in a state of true “mass balance” – or equilibrium – as opposed to mass loss.

The development of this new dataset was primarily funded by the European Space Agency (ESA), with a little help from the Programme for Monitoring of the Greenland Ice Sheet (www.promice.dk). Our multi-satellite Ku-band altimetry mass balance record is now available as tabulated data – both for the ice sheet, as well as the eight major ice-sheet drainage sectors – at https://doi.org/10.11583/DTU.13353062. Within the next two years, the ongoing Sentinel-3A/B satellite missions are clearly poised to extend Greenland’s radar altimetry record to three decades. This will allow us to start assessing ice-sheet health using the statistics of a 30-year climatology record. This keeps us excited at the prospect of updating this record in the near future. Stay tuned!

Simonsen, S., V. Barletta, W. Colgan and L. Sørensen. 2021. Greenland Ice Sheet mass balance (1992-2020) from calibrated radar altimetry. Geophysical Research Letters. L61865. doi:10.1029/2020GL091216.

Tags: , , , , , , , , , , , ,

‘Cold Content’ of Greenland’s Firn Plateau

Posted by William Colgan on April 29, 2020
Climate Change, Communicating Science, New Research / No Comments

We have a new open-access study in the current issue of Journal of Glaciology that investigates the “cold content” of Greenland’s high-elevation firn plateau1. Firn is the relatively low density near-surface ice-sheet layer comprised of snow being compressed into ice. Cold content is one of its quirkier properties. Of course, all firn is literally freezing – meaning below 0°C – but some firn is colder than other firn. Clearly, it takes a lot more energy to warm -30°C firn to 0°C, than it does for -1°C firn. Our study highlights at least one discernible shift in cold content – how much sensible heat energy is required to warm firn to the 0°C melting point – in response to climate change.

Figure 1 – The nine high-elevation ice-sheet sites where we assessed firn cold content in the top 20 m.

There is a strong annual cycle in firn cold content. Generally, cold content is at its maximum each April, after the firn has been cooled by winter air temperatures. Cold content then decreases through summer, as warming air temperatures and meltwater percolation pump energy into the firn, to reach a minimum each September. The magnitude of this annual cycle varies across the ice sheet, primarily as a function of the meltwater production, but also as a function of snowfall-dependent firn density. Firn density is highly sensitive to snowfall rate, and firn cold content is a function of firn density.

Figure 2 – The mean annual cycle in four-component firn cold content assessed at the nine ice-sheet sites over the 1988-2017 period. Note the relatively large latent heat release associated with meltwater at Dye-2, in comparison to other sites.

We find few discernible year-on-year trends in cold content across the highest elevation areas of the firn plateau. For example, there is perhaps a slight decrease at Summit – where we find snowfall is increasing at 24 mm/decade and air temperatures are warming at 0.29°C/decade – but statistically-significant multi-annual trends in cold content are difficult to separate from year-to-year variability. At Dye-2, however, which has the greatest melt rate of the sites that we examine, there is clear evidence of the impact of changing climate. At Dye-2, an exceptional 1-month melt event in 2012 removed ~24% of the cold content in the top 20 m of firn. It took five years for cold content to recover to the pre-2012 level.

Figure 3 – The cumulative four-component firn cold content at the nine ice-sheet sites over the 1998-2017 period. Note the sharp loss of Dye-2 cold content in 2012, and the subsequent multi-year recovery of this cold content.

The refreezing of meltwater within firn is a potential buffer against the contribution of ice-sheet melt to sea-level rise; surface melt can refreeze within porous firn instead of running off into the ocean. But refreezing meltwater requires available firn cold content. The multi-annual reset of cold content that we document at Dye-2 suggests that a single melt event can reduce firn cold content – and thus precondition firn for potentially less meltwater refreezing – for years to follow. This highlights the potential for the cold content of Greenland’s firn plateau to decrease in a non-linear fashion, as climate change pushes melt events to progressively higher elevations of the firn plateau.

1Vandecrux, B., R. Fausto, D. van As, W. Colgan, P. Langen, K. Haubner, T. Ingeman-Nielsen, A. Heilig, C. Stevens, M. MacFerrin, M. Niwano, K. Steffen and J. Box. 2020. Firn cold content evolution at nine sites on the Greenland ice sheet between 1998 and 2017. Journal of Glaciology..

Tags: , , , , , , , , , ,

New Greenland iceberg calving estimate

Posted by William Colgan on June 06, 2019
New Research / No Comments

We have a new – and long awaited! – open-access study out in the current issue of Earth Systems Science Data. In this study, we estimate the ice discharge – meaning transfer of land-ice into the ocean – at 276 tide-water glaciers around the Greenland Ice Sheet between 1986 and 2017. These individual glacier discharge records are now available online. We estimate that ice-sheet-wide discharge – or iceberg calving – increased from less than 450 Gt/yr in the 1980s and 1990s to closer to 500 Gt/yr at present. That increase of 50 Gt/yr is equivalent to an extra 1600 tonnes per second of icebergs – year-round – relative to the 1980s and 1990s.

Figure 1 – Time series of iceberg discharge from the Greenland Ice Sheet. Dots represent when observations occurred. The orange line is the annual average. Coverage denotes the percentage of glaciers from which total discharge is observed at any given time. Total discharge is “estimated”, rather than “observed”, when coverage is <100 %.

Dealing with unknown ice thickness or missing ice velocity data – in a transparent and reproducible fashion – was a huge aspect of making such a dense glacier discharge dataset. Perhaps the most novel aspect of this study is a sensitivity test to quantify just how precisely ice discharge from the entire ice sheet can be estimated at a single point in time. The result of this sensitivity test was a little surprising. We found that – using the same ice thickness and ice velocity information – assessed ice discharge can change tremendously just based on where we placed our “flux gates”.

We examined placing flux gates – meaning the virtual lines across every glacier through which we estimate ice discharge – between 1 and 9 kilometers up-glacier from the glacier tongue, and extending them laterally into minimum ice velocities of between 10 and 150 m/yr. These generally reasonable ranges can influence the apparent ice-sheet-wide discharge we estimate by around 50 Gt/yr. To place this flux gate uncertainty in perspective, we can say it is roughly equivalent to the total uncertainty in ice-sheet-wide discharge – from all sources of uncertainty – assigned in most previous studies. This flux gate uncertainty is also roughly equivalent to the change in ice-sheet-wide discharge since the 1980s.

Figure 2 – Sensitivity test of ice-sheet-wide discharge as a function of flux gate location. The vertical axis denotes the up-glacier distance of flux gates from the glacier tongue. The horizontal axis denotes the minimum ice velocity into which flux gates laterally extend.

A very cool thing about this study is that not only the data, but also the code, is open access. This code-sharing approach is part of the growing “open science” movement. The US National Academies – meaning Science, Engineering and Medicine – recently joined together to publish an open science mandate. Sharing code not only makes complex results reproducible, but also helps different teams move forward. For example, our ice-sheet-wide discharge is slightly different from previous studies. We are not entirely sure how much of this difference in ice discharge is due to differences in flux gate locations. But now – at least moving forward – future teams will be able to use precisely the same flux gates that we used.

Mankoff, K., W. Colgan, A. Solgaard, N. Karlsson, A. Ahlstrøm, D. van As, J. Box, S. Khan, K. Kjeldsen, J. Mouginot and R. Fausto. 2019. Greenland Ice Sheet solid ice discharge from 1986 through 2017. Earth System Science Data. 11: 769-786. https://doi.org/10.5194/essd-11-769-2019.

Tags: , , , , , , ,

Lost Ice-Sheet Porosity and Sea-Level Buffering

Posted by William Colgan on March 12, 2019
New Research, Sea Level Rise / No Comments

We have a new open-access study that investigates the high-elevation firn plateau of the Greenland Ice Sheet in the current issue of The Cryosphere1. Firn is the relatively low density near-surface ice-sheet layer comprised of snow being compressed into ice. Firn is relatively porous, meaning that meltwater can percolate through it. The refreezing of meltwater within firn is a potential buffer against the ice-sheet sea-level contribution from surface melt; surface melt can refreeze within porous firn instead of running off into the ocean. Our study aims to assess how big this sea-level buffer might be, and how much sea-level buffer may have already been used.

We pull together a singularly unique dataset – 340 ice-core measurements of firn density collected over 65 years – to assess the near-surface density across the entire high-elevation firn plateau of the Greenland Ice Sheet. Many of these vertical firn density profiles were digitized and brought together for the first time from historical studies, but twenty are collected by our team and new to science. We analyze this ice-core dataset for empirical relations between firn density and accumulation or air temperature. This allows us to divide the ice sheet into three distinct firn areas, within each of which we can confidently predict the vertical profile of near-surface firn density.

Figure 1 – Left: Firn air content within the top 10 m (FAC10) estimated from ice-core measurements (denoted with ‘x’). The ice sheet is divided into three areas: the Dry Snow Area (DSA), the Low Accumulation Percolation Area (LAPA), and the High Accumulation Percolation Area (HAPA). Right: Change in top 10 m firn air content between 1998–2008 and 2010–2017 within Low Accumulation Percolation Area along the ice sheet’s western flank.

We find that the firn structure at the heart of the ice sheet – the highest, coldest and driest firn known as the Dry Snow Area – appears to have been stable since 1953. There is no trend in firn density within the Dry Snow Area. At lower elevations, however, we find significant changes in response to recent increases in surface melt due to climate change. The area we call the Low Accumulation Percolation Area – an elevation band of relatively low snowfall and high melt along the ice sheet’s west flank – has a marked increase in the firn densities measured pre- and post-2009. This firn density change is equivalent to a sea-level buffer loss of 1.5±1.2 mm sea-level equivalent (540±440 gigatonnes).

We compare the ice-sheet-wide firn density structure that we estimate from ice-core measurements with the firn density structure estimated from three regional climate models. The regional climate models suggest that the decrease in firn porosity initiated in the early 2000s and accelerated with post-2010 climate change. But we also find non-trivial differences between the firn porosities simulated by regional climate models, and that inferred from ice-core measurements, especially in what we call the High Accumulation Percolation Area. Here – the ice sheet’s low elevation southeast flank – modeled firn porosity can be biased the equivalent of between 3 and 7 meters of air distributed over the entire firn column depth.

Figure 2 – Left: Ice-sheet-wide firn air content within the top 10 m of firn (FAC10) simulated by three regional climate models (MAR, HIRHAM and RACMO) and derived from ice-core observations (this study) in different ice-sheet areas. Right: Same for firn air content over the entire depth of the firn column (FACtot).

This study highlights the importance of bringing together firn density measurements to document the response of ice-sheet firn – a non-trivial component of the sea-level budget – to recent climate change. The ice-sheet-wide firn porosity structure we infer from ice-core measurements can also serve as an independent evaluation target for the firn porosity structures simulated by regional climate models. This study also illustrates how new insight can be obtained from the synthesis and re-analysis of historical datasets. This emphasizes the tremendous value of open-access data within the scientific community. This work is part of the Retain project funded by the Danmarks Frie Forskningsfond (grant 4002-00234). The open-access publication is available via the hyperlink below.

1Vandecrux, B., MacFerrin, M., Machguth, H., Colgan, W., van As, D., Heilig, A., Stevens, C., Charalampidis, C., Fausto, R., Morris, E., Mosley-Thompson, E., Koenig, L., Montgomery, L., Miège, C., Simonsen, S., Ingeman-Nielsen, T., and Box, J. 2019. Firn data compilation reveals widespread decrease of firn air content in western Greenland. The Cryosphere. 13: 845-859. https://doi.org/10.5194/tc-13-845-2019.

Tags: , , , , , , ,

Eight trillion tonnes of Arctic ice lost since 1971

Posted by William Colgan on December 20, 2018
Climate Change, New Research, Sea Level Rise / 2 Comments

We have just completed a study that inventories Arctic land ice loss since 1971. It is available open-access in the current issue of Environmental Research Letters1. While we scientists have a pretty good idea of the health — or mass balance — of glaciers and ice sheets — or land ice — since the advent of satellite altimetry in the early 1990s, there is a need for better understanding of land ice health during the pre-satellite era. Our new study estimates the annual ice loss from all glacierized regions north of 55°N between 1971 and 2017.

We use in situ data – mass balance measurements from a handful of continuously monitored glaciers – as indicators for the health of land ice in seven Arctic regions. These hard-fought in situ data are scarce, they are only measured at between 20 and 44 Arctic glaciers every year. Extrapolating these data to entire regions is statistically challenging without additional information. Fortunately, independent estimates of regional mass balance are available from satellite gravimetry during the 2003 to 2015 period. This permits calibrating in situ and satellite-derived mass balance estimates during the satellite era. This makes our pre-satellite era estimates fairly robust.

During the 41 years assessed, we estimate that approximately 8,300 Gt of Arctic land ice was lost. It is difficult to contextualize this magnitude of ice loss. The flow of Niagara Falls – which is approximately 2400 m3 per second or about 75 km3 per year – is only equivalent to about half this volume (3500 km3) over the 1971-2017 period. The total Arctic land ice loss that we document represents 23 mm of sea-level rise since 1971. Greenland is by far the largest contributor (10.6 mm sea-level equivalent), followed by Alaska (5.7 mm sea-level equivalent) and then Arctic Canada (3.2 mm sea-level equivalent).

The UN Intergovernmental Panel on Climate Change (IPCC) now highlights two periods – the “recent past” (1986-2005) and “present day” (2005-2015) – as being of special interest in climate change studies. The Arctic land ice contribution to sea-level rise that we inventory increased from 0.4 to 1.1 mm sea-level equivalent between these periods. In terms of tonnes per second (5,000 to 14,000 t/s), both the magnitude – and the increase – are staggering.

Figure 1 – The cumulative sea-level rise contribution (in mm) from land ice in seven regions of the Arctic between 1971 and 2017. Analogous estimates from satellite gravimetry (GRACE) between 2003 and 2015 shown with open symbols.

The uncertainties associated with extrapolating sparse in situ data over large areas are undeniably large. But, the reality is that climate change was already gearing up as the global satellite observation network came online. So, in the absence of satellite data that can characterize the “pre-climate change” health of Arctic land ice, we need to leverage the extremely precious pre-satellite era observations that are available in creative ways. We hope that the ice loss estimates we present will be useful comparison targets for studies that estimate pre-satellite era mass balance in other ways.

The estimates of annual land ice mass balance — or health — in seven Arctic regions produced by this study are freely available for download here. This study was developed within the Arctic Monitoring and Assessment Program (AMAP) and International Arctic Science Committee (IASC) frameworks, as a direct contribution to the IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC).

Figure 2 – Annual land ice mass balance — or health — in six Arctic regions between 1971 and 2017. Individual glacier mass balance records (blue lines) are combined into a regional composite (black line). Health is expressed both as a normalized score (left axis) and in gigatonnes per year (right axis). The numbers of glaciers comprising each composite is indicated in red text.

1Box, J., W. Colgan, B. Wouters, D. Burgess, S. O’Neel, L. Thomson and S. Mernild. 2018. Global sea-level contribution from Arctic land ice: 1971 to 2017. Environmental Research Letters.

Tags: , , , , , , ,

Changes in Ice-Sheet Density: How and Why?

Posted by William Colgan on October 25, 2018
Climate Change, Communicating Science, New Research, Sea Level Rise / No Comments

We investigate the high-elevation firn plateau of the Greenland Ice Sheet in a new open-access study in the current issue of Journal of Geophysical Research1. This study pulls together singularly unique – and hard fought – ice core observations and weather station data into a super-neat firn model. This relatively porous near-surface ice-sheet layer known as firn is being increasingly scrutinized for two main reasons.

The first reason is sea-level rise. These high regions of the Greenland ice sheet are normally preserved form intense melting, but this is changing, with more melt seen in recent years. Nevertheless, the porosity of the firn can provide a buffer against sea-level rise when meltwater refreezes within the firn instead of running off into the ocean. But exactly how much of this buffering capacity is available – and for how long – is not really understood.

The second reason is satellite altimetry. Repeat observation of ice thickness by satellite altimeter is a primary method by which ice-sheet mass balance – or overall health – is assessed. But since firn is porous, changes in elevation don’t always translate into changes in mass. For example, the firn layer can become thinner – making the ice-sheet appear thinner – when there’s actually just an increase in firn density rather than a change in mass.

Figure 1 – Locations of the four study sites on the Greenland Ice Sheet’s high-elevation firn plateau.

In this study, we were interested in teasing out the climatic controls of firn density: What makes firn porosity grow and shrink over time? So, we simulated the evolution of firn density – and therefore porosity – over time at four ice-sheet sites. These sites were carefully chosen as sites where both in-situ climate and firn measurements were available (Crawford Point, Dye-2, NASA-SE and Summit). The firn simulations used an updated version of the HIRHAM regional climate model’s firn model. At each site, we initiated simulations using firn density profiles observed from ice cores, and then ran the simulations forward in time using in-situ weather station records. We then ensured that simulated firn density also compared well with repeat firn density profiles observed again many years later. The simulations were between 11 and 15 years, depending on the data available at each site.

Figure 2 – Simulated firn density through time at the four study sites. At all sites, the relative depth of a given layer increases over time, as snowfall exceeds meltwater runoff.

A lot of recent ice-sheet research has focused on how increasing air temperatures and meltwater production are increasing firn density. And our simulations definitely confirmed that! But perhaps counterintuitively, we found that the leading driver of changes in firn density was actually year-to-year changes in amount of snowfall. Firn density decreases as snowfall increases, and vice versa. This study therefore highlights that if we want to project time-and-space variability in firn density we really need to project time-and-space variability in snowfall rates.

Figure 3 – Assessing the relative strength of four drivers of firn density change at the four study sites.

It was also satisfying to see that – given observed climate data – our simulations could reproduce the firn conditions as observed in the field. This gives confidence including this firn model in regional climate models. This finding is of course limited to the high-elevation firn plateau of the Greenland Ice Sheet, which admittedly does not experience tremendous melt. But, as the firn plateau covers over 80% of the ice-sheet area, understanding it plays a key role in tackling pressing satellite altimetry and sea-level buffering questions.

This work is part of the Retain project funded by the Danmarks Frie Forskningsfond (grant 4002-00234). The open-access publication is available via the hyperlink below.

1Vandecrux, B., R. Fausto, P. Langen, D. van As, M. MacFerrin, W. Colgan, T. Ingeman‐Nielsen, K. Steffen, N. Jensen, M. Møller and J. Box. 2018. Drivers of firn density on the Greenland ice sheet revealed by weather station observations and modeling. Journal of Geophysical Research: Earth Surface. 123: 10.1029/2017JF004597.

Tags: , , , , , , , ,