‘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..

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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.

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What’s the density of snow on the Greenland Ice Sheet?

Posted by William Colgan on May 07, 2018
New Research / No Comments

We have a new open-access study in the current volume of Frontiers in Earth Science that tries to estimate snow density across the Greenland Ice Sheet1. Snow density might seem like an unexciting topic, but it is fundamental to blending ice-sheet thinning or thickening observations with surface mass balance simulations to assess ice-sheet health. Clearly, assuming a snow density of 400 kg/m3 makes a snowfall event observed by satellite altimeter twice as massive as assuming a snow density of 200 kg/m3 (and vice versa). There are several mathematical formulations presently being used to estimate snow density. These existing approaches generally estimate snow density as a function of more accessible geographic or climatic parameters.


Figure 1 – Locations of the surface snow density measurements collected in this public dataset. Contours lines indicate elevations in meters above sea level.

In this study, we assembled a large database of snow density measurements from the Greenland Ice Sheet. These measurements were collected from a variety of scientific expeditions going back to 1954, and provide the most complete spatial coverage of the ice sheet that is presently possible. Despite running a lot of statistics on this database, we could not find a compelling proxy for snow density. Our analysis indicates that snow density cannot be reliably predicted by common geographic (i.e. elevation, latitude or longitude) or climatic (i.e. air temperature or accumulation rate) variables. As existing approaches to estimate snow density rely on these common geographic and climatic variables, this was a somewhat unexpected finding.


Figure 2 – Snow density (0 to 10 cm depth) plotted against: (a) measurement year, (b) site latitude, (c) site longitude, (d) site elevation, (e) mean annual air temperature, and (f) accumulation rate.

Our study therefore recommends that the average measured density of 315 ± 44 kg/m3 (± standard deviation) is the most statistically defensible assumption for snow density. This recommendation of a constant, or zero-order approximation, differs from previous studies that have recommended estimating snow density as a second-order polynomial function of near-surface ice-sheet temperature. We show that these previous approaches may systematically overestimate snow density by 17 to 19 %. This is partially due to their mathematical formulations, but mainly due to previously considering measurement depths of up to 1 m as characteristic of “snow density”. As density increases with depth in the relatively porous near-surface layers of the ice sheet, we are instead careful to only include density measurements to a depth of 10 cm.


Figure 3 – Snow density (0-10 cm depth) versus mean annual air temperature. Solid line indicates the regression of this study, while the dotted and dashed lines indicate previously published temperature-dependent formulations for estimating snow density.

We hope that the approach of estimating snow density that we are proposing, which is mathematically less complex but statistically more robust, will be useful to researchers working with both surface mass balance simulations and satellite altimetry observations, as well as researchers modelling process-level studies of snow compaction and meltwater percolation in the near-surface ice-sheet layers. This study was supported by the Danish Research Council and the Programme for Monitoring of the Greenland Ice Sheet. Our database of 254 snow density measurements is freely available in the supplementary material of the study.

1Fausto R., J. Box, B. Vandecrux, D. van As, K. Steffen, M. MacFerrin, H. Machguth, W. Colgan, L. Koenig, D. McGrath, C. Charalampidis and R. Braithwaite. 2018. A Snow Density Dataset for Improving Surface Boundary Conditions in Greenland Ice Sheet Firn Modeling. Frontiers in Earth Science 6:51. doi:10.3389/feart.2018.00051.

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