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Geosciences Column: The best spots to hunt for ancient ice cores

Geosciences Column: The best spots to hunt for ancient ice cores

Where in the world can you find some of Earth’s oldest ice? That is the question a team of French and US scientists aimed to answer. They recently identified spots in East Antarctica that likely have the right conditions to harbor ice that formed 1.5 million years ago. Scientists hope that obtaining and analysing an undisturbed sample of ice this old will give them clues about Earth’s ancient climate.

The team published their findings in The Cryosphere, an open access journal of the European Geosciences Union (EGU).

Why study ancient ice?

When snow falls and covers an ice sheet, it forms a fluffy airy layer of frozen mass. Over time, this snowy layer is compacted into solid ice under the weight of new snowfall, trapping pockets of air, like amber trapping prehistoric insects. For today’s scientists, these air bubbles, some sealed off thousands to millions of years ago, are snapshots of what the Earth’s atmosphere looked like at the time these pockets were locked in ice. Researchers can tap into these bubbles to understand how the proportion of greenhouse gases in our atmosphere have changed throughout time.

As of now, the oldest ice archive available to scientists only goes back 800,000 years, according to the authors of the study. While pretty ancient, this ice record missed out on some major climate events in Earth’s recent history. Scientists are particularly interested in studying the time between 1.2 million years ago and 900,000 years ago, a period scientifically referred to as the mid-Pleistocene transition.

In the last few million years leading up to this transition, the Earth’s climate would experience a period of variation, from cold glacial periods to warmer periods, every 40,000 years. However, after the mid-Pleistocene transition, Earth’s climate cycle lengthened in time, with each period of variation occurring every 100,000 years.  

Currently, there isn’t a scientific consensus on the origin of this transition or what factors were involved. By examining old ice samples and studying the composition of the atmospheric gases present throughout this transition, scientist hope to paint a clearer picture of this influential time. “Locating a future 1.5 [million-year]-old ice drill site was identified as one of the main goals of the ice-core community,” wrote the authors of the study.  

The quest for old ice

Finding ice older than 800,000 years is difficult since the Earth’s deepest, oldest ice are the most at risk of melting due to the planet’s internal heat. Places where an ice sheet’s layers are very thick have an even greater risk of melting.

Mesh, bedrock dataset (Fretwell et al., 2013; Young et al., 2017) and basal melt rate (Passalacqua et al., 2017) used for the simulation. Credit: O. Passalacqua et al. 2018.

“If the ice thickness is too high the old ice at the bottom is getting so warm by geothermal heating that it is melted away,” said Hubertus Fischer, a climate physics researcher from the University of Bern in Switzerland not involved in the study, in an earlier EGU press release.

Last summer, a team of researchers from Princeton University announced that they had unearthed an ice core that dates back 2.7 million years, but the sample’s layers of ice aren’t in chronological order, with ice less than 800,000 years old intermingling with the older frozen strata. Rather than presenting a seamless record of Earth’s climate history, the core can only offer ‘climate snapshots.’

Finding the best of the rest

The authors of the recent The Cryosphere study used a series of criteria to guide their search for sites that likely could produce ice cores that are both old and undisturbed. They established that potential sites should of course contain ice as old as 1.5 million years, but also have a high enough resolution for scientists to study frequent changes in Earth’s climate.

Additionally, the researchers established that sites should not be prone to folding or wrinkling, as these kinds of disturbances can interfere with the order of ice layers.

Lastly, they noted that the bedrock on which the ice sheet sits should be higher than any nearby subglacial lakes, since the lake water could increase the risk of ice melt.

Magenta boxes A, B and C correspond to areas that could be considered as our best oldest-ice targets. Colored points locate possible drill sites. Credit: O. Passalacqua et al. 2018.

 

Using these criteria, the researchers evaluated one region of East Antarctica, the Dome C summit, which scientists in the past have considered a good candidate site for finding old ice. They ran three-dimensional ice flow simulations to locate parts of the region that are the most likely to contain ancient ice, based on their established parameters.

By narrowing down the list of eligible sites, the researchers were able to pinpoint regions just a few square kilometres in size where intact 1.5 million-year-old ice are very likely to be found, according to their models. Their results revealed that some promising areas are situated a little less than 40 kilometres southwest of the Dome C summit.

The researchers hope their new findings will bring scientists one step closer towards finding Earth’s ancient ice.

By Olivia Trani, EGU Communications Officer

Geosciences Column: Landslide risk in a changing climate, and what that means for Europe’s roads

Geosciences Column: Landslide risk in a changing climate, and what that means for Europe’s roads

If your morning commute is already frustrating, get ready to buckle up. Our climate is changing, and that may increasingly affect some of central Europe’s major roads and railways, according to new research published in the EGU’s open access journal Natural Hazards and Earth System Sciences. The study found that, in the face of climate change, landslide-inducing rainfall events will increase in frequency over the century, putting central Europe’s transport infrastructure more at risk.  

How do landslides affect us?

Landslides that block off transportation corridors present many direct and indirect issues. Not only can these disruptions cause injuries and heavy delays, but in broader terms, they can negatively affect a region’s economic wellbeing.

One study for instance, published in Procedia Engineering in 2016, examined the economic impact of four landslides on Scotland’s road network and estimated that the direct cost of the hazards was between £400,000 and £1,700,000. Furthermore the study concluded that the consequential cost of the landslides was around £180,000 to £1,400,000.

Such landslides can have a societal impact on European communities as well, as disruptions to road and railway networks can impact access to daily goods, community services, and healthcare, the authors of the EGU study explain.

Modelling climate risk

To analyse climate patterns and how they might affect hazard risk in central Europe, the researchers first ran a set of global climate models, simulations that predict how the climate system will respond to different greenhouse gas emission scenarios. Specifically, the scientists ran climate projections based on the Intergovernmental Panel on Climate Change’s A1B socio-economic pathway, a scenario defined by rapid economic growth, technological advances, reduced cultural and economic inequality, a population peak by 2050, and a balanced reliance on different energy sources.

They then determined how often the conditions in their climate projections would trigger landslide events specifically in central Europe using a climate index that estimates landslide potential from the duration and intensity of rainfall events. The index, established by Fausto Guzzetti of National Research Council of Italy and his colleagues, suggests that landslide activity most likely occurs when a rainfall event satisfies the following three conditions: the event lasts more than three days, total downpour is more than 37.3 mm and at least one day of the rainfall period experiences more than 25.6 mm.

The researchers also incorporated into their models data on central Europe’s road infrastructure as well as the region’s geology, including topography, sensitivity to erosion, soil properties and land cover.

Overview of a particularly risk-prone region along the lowlands of Alsace and the Black Forest mountain range: (a) location of the region in central Europe and median of the increase in landslide-triggering climate events for (b) the near future and (c) the remote future.

The fate of Europe’s roadways

The results of the researchers’ models suggest that the number of landslide-triggering rainfall events will increase from now up until 2100. Their simulations also find while that these hazardous rainfall events slightly increase in frequency between 2021 and 2050, the number of these occurrences will be more significant between 2050 and 2100.  

While the flat, low-altitude areas of central Europe will only experience minor increases in landslide-inducing rainfall activity, regions with high elevation, like uplands and Alpine forests, are most at risk, their findings suggest.

The study found that many locations along the north side of the Alps in France, Germany, Austria and the Czech Republic may face up to seven additional landslide-triggering rainfall events as our climate changes. This includes the Vosges, the Black Forest, the Swabian Jura, the Bergisches Land, the Jura Mountains, the Northern Limestone Alps foothills, the Bohemian Forest, and the Austrian and Bavarian Alpine forestlands.

The researchers go on to explain that much of the Trans-European Transport Networks’ main corridors will be more exposed to landslide-inducing rainfall activity, especially the Rhine-Danube, the Scandinavian-Mediterranean, the Rhine-Alpine, the North Sea-Mediterranean, and the North Sea-Baltic corridors.

The scientists involved with the study hope that their findings will help European policy makers make informed plans and strategies when developing and maintaining the continents’ infrastructure.  

Geosciences Column: Extreme snowfall potentially worsened Nepal’s 2015 earthquake-triggered avalanche

Geosciences Column: Extreme snowfall potentially worsened Nepal’s 2015 earthquake-triggered avalanche

Three years ago, an earthquake-induced avalanche and rockfalls buried an entire Nepalese village in ice, stone, and snow. Researchers now think the region’s heavy snowfall from the preceding winter may have intensified the avalanche’s disastrous effect.

The Langtang village, just 70 kilometres from Nepal’s capital Kathmandu, is nestled within a valley under the shadow of the Himalayas. The town was popular amongst trekking tourists, as the surrounding mountains offer breathtaking hiking opportunities.

But in April 2015, a 7.8-magnitude earthquake, also known as the Gorkha earthquake, triggered a massive avalanche and landslides, engulfing the village in debris.

Scientists estimate that the force of the avalanche was half as powerful the Hiroshima atomic bomb. The blast of air generated from the avalanche rushed through the site at more than 300 kilometres per hour, blowing down buildings and uprooting forests.

By the time the debris and wind had settled, only one village structure was left standing. The disaster claimed the lives of 350 people, with more than 100 bodies never located.

Before-and-after photographs of Nepal’s Langtang Valley showing the near-complete destruction of Langtang village. Photos from 2012 (pre-quake) and 2015 (post-quake) by David Breashears/GlacierWorks. Distributed via NASA Goddard on Flickr.

Since then, scientists have been trying to reconstruct the disaster’s timeline and determine what factors contributed to the village’s tragic demise.

Recently, researchers discovered that the region’s unusually heavy winter snowfall could have amplified the avalanche’s devastation. The research team, made up of scientists from Japan, Nepal, the Netherlands, Canada and the US, published their findings last year in the EGU’s open access journal Natural Hazards and Earth System Sciences.

To reach their conclusions, the team drew from various observational sources. For example, the researchers created three-dimensional models and orthomosaic maps, showing the region both before it was hit by the coseismic events and afterwards. The models and maps were pieced together using data collected before the earthquake and aerial images of the affected area taken by helicopter and drones in the months following the avalanche.

They also interviewed 20 villagers local to the Langtang valley, questioning each person on where he or she was during the earthquake and how much time had passed between the earthquake and the first avalanche event. In addition, the researchers asked the village residents to describe the ice, snow and rock that blanketed Langtang, including details on the colour, wetness, and surface condition of the debris.  

Based on their own visual ice cliff observations by the Langtang river and the villager interviews, the scientists believe that the earthquake-triggered avalanche hit Langtang first, followed then by multiple rockfalls, which were possibly triggered by the earthquake’s aftershocks.

A three-dimensional view of the Langtang mountain and village surveyed in this study. Image: K. Fujita et al.

According to the researchers’ models, the primary avalanche event unleashed 6,810,000 cubic metres of ice and snow onto the village and the surrounding area, a frozen flood about two and a half times greater in volume than the Egyptian Great Pyramid of Giza. The following rockfalls then contributed 840,000 cubic metres of debris.  

The researchers discovered that the avalanche was made up mostly of snow, and furthermore realized that there was an unusually large amount of snow. They estimated that the average snow depth of the avalanche’s mountainous source was about 1.82 metres, which was similar to snow depth found on a neighboring glacier (1.28-1.52 metres).

A deeper analysis of the area’s long-term meteorological data revealed that the winter snowfall preceding the avalanche was an extreme event, likely only to occur once every 100 to 500 years. This uncommonly massive amount of snow accumulated from four major snowfall events in mid-October, mid-December, early January and early March.

From these lines of evidence, the team concluded that the region’s anomalous snowfall may have worsened the earthquake’s destructive impact on the village.

The researchers believe their results could help improve future avalanche dynamics models. According to the study, they also plan to provide the Langtang community with a avalanche hazard map based on their research findings.  

Further reading

Qiu, J. When mountains collapse… Geolog (2016).

Roberts Artal, L. Geosciences Column: An international effort to understand the hazard risk posed by Nepal’s 2015 Gorkha earthquake. Geolog (2016).

Geosciences Column: The science behind snow farming

Geosciences Column: The science behind snow farming

For roughly the last decade, some ski resorts and other winter sport facilities have been using a pretty unusual method to ensure white slopes in winter. It’s called snow farming. The practice involves collecting natural or artificially made snow towards the end of winter, then storing the frozen mass in bulk over the summer under a thick layer of sawdust, woodchips, mulch, or other insulating material.

Many winter sport destinations have adopted the practice. In preparation for the 2014 Winter Olympics, Sochi, Russia stockpiled about 800,000 cubic metres of human-made snow during the warmer season, enough snow to fill 320 Olympic-size swimming pools.

Despite the growing trend, there still is little research on snow farming techniques. Recently, a team of scientists from the Institute for Snow and Avalanche Research (SLF) and the CRYOS Laboratory at the École Polytechnique Fédérale in Switzerland examined the success of snow conservation practices and used models to estimate what factors influence covered snow. Their findings were published in the EGU’s open access journal The Cryosphere.

Why store snow for the winter?

The ski industry has been storing snow for many reasons. The practice is a way for winter sports facilities to accommodate training athletes, start ski seasons earlier, and guarantee snow for major sports events. Snow farming can also be seen as a way to adapt to Earth’s changing climate, according to the authors of the study. Indeed, research published last year in The Cryosphere, found that the Alps may lose as much as 70 percent of snow cover by the end of the century if global warming continues unchecked. Snow loss to this degree could severely threaten the $70 billion dollar (57 billion EUR) industry and the alpine communities that depend on ski tourism.

For some ski resorts, the effects of climate change are already visible. For example, in Davos, Switzerland, a popular venue of the International Ski Federation Cross-Country World Cup, winter temperatures have risen over the last century while snow depth in turn has steadily declined.

Snow heap study

The research team studied two snow heaps: one near Davos, Switzerland (pictured here) and another in South Tyrol. Credit: Grünewald et al.

To better understand snow conservation techniques, the research team studied two artificially made snow heaps: one sitting near Davos and another located in South Tyrol. Each pile contained approximately 7,000 cubic metres of snow, about enough ice and powder to build 13,000 1.8-metre tall snowmen. The piles were also each covered with a 40 cm thick layer of sawdust and chipped wood.

Throughout the 2015 spring and summer season, the researchers measured changes in snow volume and density, as well as recorded the two sites’ meteorological data, including air temperature, humidity, wind speed and wind direction. The research team also fed this data to SNOWPACK, a model that simulates snow pile evolution and helps determine what environmental processes likely impacted the snow.

Cool under heat

From their observations, the researchers found that the sawdust and chipped wood layering conserved more than 75 percent of the Davos snow volume and about two thirds of the snow in South Tyrol. Given the high proportion of remaining snow, the researchers conclude that snow farming appears to be an effective tool for preparing for winter.

According to the SNOWPACK model, while sunlight was the biggest source of snow melt, most of this solar radiation was absorbed by the layer of sawdust and wood chips. The simulations suggest that the snow’s covering layer took in the sun’s heat during the day, then released this energy at night, creating a cooling effect on the snow underneath. Even more, the model found that, when the thick layer was moist, the evaporating water cooled the snow as well. The researchers estimate that only nine percent of the sun’s energy melted the snow heaps. Without the insulating layer, the snow would have melted far more rapidly, receiving 12 times as much energy from the sun if uncovered, according to the study.

Images of the South Tyrol snow heap from (a) 19 May and (b) 28 October. The snow depth (HS) is featured in c & d and snow height change (dHS) is shown in e. Credit: Grünewald et al.

The researchers found that the thickness of the covering layer was an important factor for snow conservation. When the team modelled potential snow melt under a 20 cm thick cover, the insulating and cooling effects from the layer had greatly diminished.

The simulations also revealed that, while higher air temperatures and wind speed increased snow melt, this effect was not very significant, suggesting that subalpine areas could also benefit from snow farming practices.

In the face of changing climates and disappearing snow, snow farming may be one solution for keeping winters white and skiers happy.

References

Grünewald, T., Wolfsperger, F., and Lehning, M.: Snow farming: conserving snow over the summer season, The Cryosphere, 12, 385-400, https://doi.org/10.5194/tc-12-385-2018, 2018.

Marty, C., Schlögl, S., Bavay, M., and Lehning, M.: How much can we save? Impact of different emission scenarios on future snow cover in the Alps, The Cryosphere, 11, 517-529, https://doi.org/10.5194/tc-11-517-2017, 2017.