New paper: investigations on debris-covered glaciers

Glaciers covered by debris – rocks, dirt, silt, and sand – are common in the Himalayas. Depending on who’s counting (and where you are looking), debris covers nearly 25% of the total glacierized area in the region.  Experiments and previous studies have shown that really thin debris enhances melt, but that anything over 2 cm thick insulates the ice melt.  But what is the net effect of debris cover on glacier melt rates? Our recently published (open access) paper in the Cryosphere tries to answer this question.


Khumbu Glacier (center) is debris covered. So is the bottom 2/3 of Changri Nup Glacier, located to the west. Everest is at the far right of this Landsat scene.

Unfortunately, the answer is not so easy to obtain. Traditional mass balance stake measurements are (a) difficult to install and maintain on debris-covered glaciers, and (b) impossibly biased towards locations where it is possible to drill. You could look at surface elevation changes over part of the glacier with either photogrammetry, UAV, or satellite (we use all three), but if you do this you also need to consider the emergence velocity (or increase in elevation) of the glacier as it flows downhill. On any given point in the ablation zone, the total surface elevation change is a function of both emergence and melt. And to estimate the mean emergence velocity, you need to measure the ice flux through a cross-section of the glacier.


Rates of surface elevation change at Changri Nup Glacier for different periods and data sources: (A) 2011 – 2014 (photogrammetry); (B) 2011 – 2015 (photogrammetry and UAV); (C) 2009 – 2014 (satellite and photogrammetry)

Christian Vincent and Patrick Wagnon, French glaciologists from Laboratoire de Glaciologie et Geophysique (LGGE) and Institut de Recherche pour le Development (IRD), have collected multiple datasets over 4 years to estimate the mass gain and loss over the debris-covered Changri Nup Glacier. I’d remind you that debris-covered glaciers at 5400 m of elevation are not among the easiest places to work.

But together with a team of co-authors they have measured surface velocities and surface melt rates with ablation stakes; developed digital elevation models from photogrammetry in 2011 and 2014, from unmanned aerial vehicle surveys in 2015, and from high-resolution satellite data in 2009; measured ice depths with ground-penetrating radar, and mapped ground control points and elevation profiles with differential GPS.


The lead author C. Vincent uses a differential GPS to measure a ground control point for UAV flights over the clean Changri Nup.

And the overall result: melt rates on the debris-covered glacier are about 60% less than what they would be if the glacier was free of debris. Ice cliffs and ponds enhanced melt locally, but not enough to offset the overall reduction in melt caused by the debris. The surface mass balance (in m of water equivalent, or m w.e.) over the debris-covered tongue, inferred from average surface lowering of -0.81 m w.e./yr and an average emergence velocity of +0.37 m w.e./yr, is -1.21 m w.e./yr. If the glacier were debris-free, we would expect to see an average mass balance rate of -3.00 m w.e./yr.

This field-based study provides strong evidence that the ‘debris-cover anomaly’ (where satellite data show that debris-covered glaciers appear to be lowering at the same rate as clean-ice glaciers) is an artifact. It also shows that, in this location at least, the effects of ponds and ice cliffs are minimal.

Why is this important? If debris-covered ice (low-angle and thick) occupies 25% of the total glacierized area, it probably contains an even greater percentage of the total ice volume. Better estimates of the net insulating effect of debris will help us improve simulations of future ice loss, and its impacts on water resources downstream.




AWS on Ice

True fact: there have been not one but two workshops dedicated specifically to the installation of automatic weather stations (AWS) on glaciers.


The newly-installed AWS at Yala Glacier. We didn’t get these views when we did the work. (Photo credit: Jitendra Bajracharya)

One of the biggest unknowns in how glaciers will respond to climate change are the meteorological conditions and melt rates at the glacier surface, and how these conditions relate to data from standard observation networks and/or climate reanalysis products. But setting up precise sensors on a surface that can move, melt, and be buried by snow – sometimes all of these in the same day – is a big challenge.  Unfortunately, for all challenges (including drinking milk upside down through a straw) you either learn by experience (AKA “mistakes”), or you learn from the experiences of others. For some reason I’ve tended to go with the former.

Our recent AWS installation at Yala Glacier is another attempt to obtain a year-long record of meteorological conditions at 5350 m in the Himalayas. At this altitude, temperatures are rarely above zero and the melt of snow or ice is basically controlled by the radiation balance at the surface (see below for a more technical discussion). So our station will record radiation received and emitted or reflected by the surface, air temperature and relative humidity, wind speed and direction, and surface height changes from melt and snowfall.

Experience tells us that ‘floating’ weather stations, such as tripods that simply sit on the top of the surface, don’t work so well on glaciers. The surface melts down unevenly, the station can be buried and damaged by heavy snowfall, and there is no way to get a record of surface lowering: the surface height sensor needs to be mounted at a fixed height in order to get information that makes any sense.


Our first attempt to measure conditions on Yala Glacier, found after typhoon HudHud in October 2014.

For the new station, we used a slick tower design that can be built up in the field (full credit to  Alex Jarosch and Faron Anslow; tower recipe below or see P. 52-55 here). Essentially, we connect three 2.0 m aluminum pipes vertically to make a 6.0 m tall triangular structure. Horizontal supports brace the top 2.0 m of the tower, and the bottom 4.0 m of each leg is drilled in to the ice. If you’re going to try this at home, don’t forget to stick small plastic caps on the bottom of the pipes that go in the ice. Without these, the weight of the tower would be supported on a very small surface area and it would melt into the ice – probably due to heat conduction through the aluminum. If the tower sinks into the ice during the experiment, the surface height measurements are meaningless.  (Thanks, experience!)


Pulling the 4 m auger out of the ice. The top two meters of the tower sits ready for installation on to the 4 m anchors.

Once the base and the tower are installed and leveled, the waterproof enclosure (which contains the battery, solar charge controller, and the datalogger) and all sensors were mounted to the tower. In the time-lapse animation shown below, you can see the clouds rolling up and down over us as we mount the sensors. In response, we shed layers and then put them back on, because the thickness of the cloud layer really affects the ‘felt’ temperature at the surface (you should really read the technical explanation below). Air temperatures during the setup hovered around 0C.



The tower from above: logger box and temperature/humidity sensor is on the left, wind sensor is top right, and it looks like three people are required to mount the net radiometer  (which measures shortwave and longwave radiation – really, there is no longer an excuse to not read just a little bit more in depth below).

The full installation took only half a day, and we were back drinking tea in camp by mid-afternoon (though thankfully not upside down and with straws). But getting the equipment and the tower components up there literally took a small army. We have nothing but huge gratitude and respect for Dawa Sherpa and Ngawang Sherpa who helped haul everything up the glacier, and to all the trekking agency staff who carried everything up from the trailhead at 1600 m to the basecamp at 5000 m.

[Thanks to Maxime Litt and Desiree Treichler for their help in the field, but also for the pre-field testing and programming. This is a critical step in the recipe.]


Glacier Station Recipe

  • 9 x 2.0 m aluminum pipe (48.25 mm OD)
  • 9 x 0.50 m aluminum pipe (48.25 mm OD)
  • 3 internal pipe connectors
  • 3 external pipe connectors
  • 3 plastic cap ends (large corks also approved)
  • 18 x 90 degree joints (48.25 mm OD)
  • Ice auger (4-5 m)
  • Plumber’s level
  • Tools
  • AWS components and all mounting hardware (!)
  • Patience
  • Reasonably good weather
  • Preparation, preparation, preparation

Radiation Balance Details

The net radiation at the surface (Q*) can be calculated from incoming and outgoing shortwave and longwave radiation:

Q* = Sin – Sout + Lin – Lout

Shortwave radiation comes from the sun: its highest at solar noon, and zero at night. But the amount of radiation reaching the surface depends on clouds and the atmospheric conditions, and the amount of shortwave radiation absorbed at the surface depends on the reflectivity (or albedo) of the surface. Brighter surfaces reflect more radiation, and have a higher albedo, which means less energy available for melt.

Longwave radiation is a mainly function of temperature: incoming longwave radiation is emitted by the atmosphere, and the earth’s surface emits longwave radiation upwards. Temperatures near the surface will be warmer on cloudy nights because the clouds both (a) emit greater longwave radiation towards the surface than a clear sky and (b) trap some of the longwave radiation emitted by the ground. Incoming longwave radiation is also a function of water vapour in the atmosphere, which affects the temperature profile.


Daily Oil Production as Ice Melt


The old Humble Oil ad popped up again on my Twitter feed:

I used this image a few years ago in an undergraduate lecture for irony, and thought a quick update based on daily global oil production might be interesting. So, here goes:

  • 1 barrel of oil contains approximately 6 gigajoules of energy (6.1178632 × 109 J to be precise; Wikipedia)
  • The energy required to melt one kilogram of ice at 0C is 33,500 J
  • So one barrel of oil can melt 6.1178632 × 109/335000 = 18,262 kg of ice

Daily global oil production passed 97 million barrels/day in 2015, which means that you are looking at daily global icemelt totals of 1.771441 x 10^12 kg, or 1,771,440,986 metric tons. (Compare with Humble’s relatively humble 7 million tons.)

If you converted that to a volume of water, assuming an ice density of 917 kg/m3, you wind up with 1,931,778,611 m3 of water. I can already hear my brain – and yours – crying for an analog, so here’s the last conversion:

  • Average water flows at Niagara Falls are 168,000 m3/minute (during tourist season; lower in off-season)
  • This corresponds to nearly 8 days of continuous thundering outflow, and a whole bunch of Maid of The Mist rides.

[NB: this is all completely irrelevant, as it is not the actual energy in the barrel of oil that melts glaciers. Its the steady increase in climate forcing from the CO2 produced in combustion of fossil fuels that is resulting in the current global glacier mass loss. But thanks for reading to the end!]

So you’re giving a scientific talk…

Some general tips to keep your audience happy:

  • One minute per slide
  • One graph per slide. If you put up a graph, take the time to explain the axes.
  • No more than 17 words per slide
  • Conceptual diagrams are great; hand drawn conceptual diagrams are fantastic
  • Keep fonts simple, consistent, and large
  • Acknowledge co-authors and funders up front
  • Leave up a slide of your conclusions when you are finished
  • Practice the talk for your roommate, partner, dog.


Himalayan fieldwork: what’s it really like?

As a glaciologist working in the Himalayas, I am fortunate: I get to travel to some incredible places and work with fantastic people. But the majestic photos of 7000 m peaks, impossible glaciers, lush valleys, and inquisitive yaks tell a story that is potentially misleading. For the most part, Himalayan fieldwork is about putting one foot in front of the other, over, and over, and over (and over) again.


One foot in front of the other on Yala Glacier, October 2014. Langtang-Lirung (7200 m) looms in the background.

On an average Langtang Valley fieldtrip, which covers about 18 days, our team typically covers 80-90 km on foot. Which may not seem like much, but most of that is over 4000 m in elevation, which means the oxygen content is lower and you tend to move sllloooooowwwlllly. We also ascend (and descend) over 7000 m in elevation, as knees and quads will loudly attest at the end of the trip.


Our October 2015 route in Langtang Valley, Nepal, as recorded by our SPOT tracker. Google Maps version available here:

One of the many perks in working for ICIMOD (the International Centre for Integrated Mountain Development, is that there is a budget for expedition support. So our trips actually wind up being quite comfortable foodwise, tentwise, and loadwise. There are tea breaks and cookies when you get back to camp, hot soups to start the evening meals, and endless portions of the Nepali classic dal bhat.

The weather and the field work itself is another story. I’ve been tentbound by typhoons, convincingly charged by yaks, sunburned and snowburned, and listened to avalanches and thunder crash around in the mountains while huddled in a flimsy nylon shell. The earthquake in April 2015 deposited house-sized boulders along the hiking trail that we have walked before, and continue to walk now. An unanticipated side effect of high-altitude fieldwork is sleep deprivation and sleep apnea, which manifests itself as dreams of drowning (AKA lack of oxygen). And then, on top of everything else, there is the constant gnawing stress of the conducting research in the field: did I bring all the tools, sensors, and hardware I need? Will the generator still work with dirty siphoned petrol? Did I pack pants? [self-edit: keep in for the Brits]


“I forgot the wrench.”

LED glasses for tent-bound entertainment.

The success of our work ultimately depends on the team that supports us. We have been incredibly fortunate to work with strong, dedicated, and amazingly resilient and helpful porters and guides. As I finish this post (6 months after starting the draft), the dry and dusty Kathmandu winter has given way to hot mornings and pop-up thunderstorms. And I look forward to putting my feet in front of each other over and over again in the mountains this spring.


Pasang Sherpa (left) and Ngawang Sherpa (right) near the end of a trip.

A video of our recent fieldwork in Langtang, shot by Susan Hale-Thomas (@susanhalethomas) and produced by Science Media (Netherlands), can be seen here:

Susan has also posted a behind-the-scenes look at the fieldwork here:



Current Science: Stable Glaciers?

A paper published last year in the Indian journal Current Science (pdf) has recently been raised in the Indian parliament. A number of scientists have been rightfully critical of this paper in different online forums. In this post, I’m going to take a quick look at the results of the paper, which are surprising to anyone familiar with the current state of Himalayan glaciology.

Why are the results surprising? Based on a sample of 2018 glaciers, the paper’s authors suggest that nearly 87% of the glaciers in the region have stable snouts, while 12% have retreating termini, and < 1% are advancing.

There are a number of issues with these figures, which lead the authors to the incorrect conclusion  that glaciers in the region are actually in steady state. In no particular order, these issues are:

  1. Glacier snout position is determined by a complex range of factors, including climate, dynamics, and lag times. Over short periods (i.e. less than 10 years, as in this paper) the behaviour of the terminus may not be indicative of the overall health of a glacier.
  2. Glacier retreat is a very different thing from glacier mass loss. Glaciers lose mass primarily due to downwasting (surface lowering), not terminus retreat. And study after study has confirmed that glaciers across the region (except for the Karakoram) are losing mass.
  3. The position of the terminus on debris-covered glaciers can be  difficult to interpret, and it will not respond to climate change in the same way as the terminus on clean (debris-free) glaciers. The authors do not distinguish between debris-covered and clean glaciers in their terminus assessments.
  4. Its not clear how the 2018 glaciers were sampled. There are over 54,000 glaciers in the HKH region, and while a 3% sample size is not too bad, biased sampling for debris-covered or large glaciers make extrapolations to the entire population problematic.

Finally, the “stable” glacier examples given in the paper actually show glaciers in retreat! Here is a Landsat pair (data available at from 2001 and 2014 for the Gangotri Glacier, in the Garwhal Himalaya (Figure 7 in the Current Science paper):

Not only is the  Gangotri (the main north-flowing glacier in the center of the image) in retreat, but you can also literally see the downwasting occur as the distance between the active ice surface and the large lateral moraines gets bigger. Smaller glaciers throughout the region also appear to be in retreat.


The authors also use the example of Siachen Glacier in the Karakoram Range (Figure 8 in the Current Science paper). This is the terminus of a massive glacier system (ca. 700 km²) and the Landsat pairs I pulled from 2000 and 2013 also appear to show retreat and deflation at the terminus:


Siachen Glacier, Karakoram Range, 2000 and 2013.

Bottom line: the Current Science paper is simply not credible. The conclusion that > 80% of glaciers in the region are stable is based on incorrect interpretations of satellite imagery, a possibly biased sampling method, and an unjustified reliance on short-term changes in terminus position as an indicator of glacier health.

In-Flight Service: UAV Research at the Top of the World

[My latest field write-up, also online in a slightly different form at ]

Against the unparalleled backdrop of Everest and Nuptse, the late November sun warms the glaciologist slightly as he prepares for an unmanned aerial vehicle (UAV) survey flight. From his coat pockets he pulls batteries that desperately need to stay warm for full power: batteries for the laptop, camera, and UAV that have been stored in his sleeping bag overnight, when temperatures plummeted below -20 C. He checks the wind. He sets up the flight on his laptop, sends the details to the UAV through a radio transmitter, and heads to the nearby launch location. At 5,350 m above sea level, the air has less than half as much oxygen as at sea level, and it can be difficult to launch the ultralight fixed-wing as the air pressure is so low. He breathes heavily — partly due to the oxygen depletion, and partly due to nerves. With the UAV in his hands, he starts the motor, heart racing as the propeller whine reaches an intense pitch. He steps forward to throw the aircraft and start the flight. He hopes.

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In collaboration with Dr Patrick Wagnon[1] and Dr Dibas Shrestha[2],  I recently joined a field expedition to Sagarmatha National Park ( to conduct UAV surveys of several glaciers in the region. Using the senseFly eBee (, we took a total of 730 photos over six successful high-altitude flights. We also collected 56 high-precision ground control points for post-processing. And in very exciting news, our research may have inadvertently set an unofficial eBee altitude record, with a maximum flight elevation of 5,896 m [confirmed!]. However, the flight conditions deteriorated after two great days, and the eBee was damaged after a downdraft pushed it into a large boulder during a launch. [If senseFly wants to work on a high-altitude version, I’ve got some suggestions (and would be happy to test!)]

The project is part of a larger research project that I am working on with Dr. Walter Immerzeel (Utrecht University) and his PhD student Philip Kraaijenbrink. Data collected during the research will be used to construct detailed mosaics and elevation models of the study sites. Comparisons of the UAV datasets with satellite imagery and terrestrial photography will be used to examine rates of glacier change, glacier flow velocities, and the role of ice cliffs and ponds in the melt rates of debris-covered glaciers. The research was funded by the UK Department for International Development (DFID), ICIMOD, and Utrecht University. Special thanks to the Nepal Army, the Civil Aviation Authority of Nepal, and NAST for the UAV flight permissions. The eBee was generously loaned by FutureWater (Netherlands), who have been assured that it will be sent back to the factory for repairs and testing.

[1] Visiting scientist at ICIMOD and researcher at L’Institut du Récherche pour le Développement (IRD, France)

[2] Research Scientist at the Nepal Academy of Science and Technology (NAST)

Reviving the Science in Langtang Valley

[News item published on the ICIMOD website. With much-appreciated inputs from Susan Hale-Thomas and Inka Koch]

A small team of ICIMOD researchers recently returned to earthquake-ravaged Langtang Valley to rebuild and maintain the network of hydrological and meteorological stations that was partly destroyed by the 25 April Gorkha tremors. As the lower portion of the trail was destroyed by landslides and rockfall, the new ‘high-route’ to Langtang took the team from Syabrubensi up to Sherpagaon, and then back on to the main trail at Rimche.

From Rimche to the main upper village of Kyanging Gompa, the Langtang Valley was essentially deserted. The roar of the Langtang Khola was interrupted only by our heavy breathing as we climbed past tea-houses and hotels damaged by the earthquake and rockfalls. At Ghodatabela, 4 km downvalley from Langtang Village, we saw first evidence of the magnitude of earthquake destruction on the opposite valley walls. Here, mature forest was stripped and toppled by the massive air blast that preceded the ice, snow, and debris avalanches (

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Continuing upvalley, the devastation became more apparent. Twisted sheets of tin roofing and lumber were scattered across the landscape. At the former site of Langtang Village, the 9 May 2015 rockfall masked all previous signs of human habitation with a thick debris-layer, though the earthquake-related avalanches had stripped houses to its bones and thus left little to cover. A few prayer flags fluttered in the valley breeze, and the waterfall-fed river that used to power a small hydroelectric plant still flowed into the debris. We raised some prayer flags of our own, and remembered those who lost their lives in the earthquake and its aftermath.

The team continued upvalley, and we spent 10 days to repair broken weather stations, replace broken sensors and solar panels, and conduct surveys of surface height change of the debris-covered Langtang and Lirung glaciers with an unmanned aerial vehicle (UAV). We scrambled along moraines to visit and maintain precipitation stations at 4,500m above Langshisha Kharka and Morimoto Basecamp, stood in the near-freezing waters of Langshisha Karka to measure water flows, and spent two nights at the base Yala Glacier (5,100 m), where the absence of recent snow cover indicated a very warm monsoon season. Having revived the weather stations will provide data to understand patters of temperature and precipitation changes and how this influences glacial melt in the valley. Though the valley and its inhabitants are still reeling from the earthquake, Langtang Valley remains as impressive and awe-inspiring as it ever was. ICIMOD will continue to support the people of Langtang through ongoing scientific research and outreach.

Resilience: Nepal’s Greatest Strength and Most Crippling Weakness

Great and insightful writing from Martin Punaks on the ongoing fuel/humanitarian crisis in Nepal.

tintin in nepal

Pic of Nepali people - low

The country I live in is slowly slipping into another humanitarian crisis. It will be the second humanitarian crisis this year. But whilst the earthquake was an act of nature, this new crisis is very much man-made.   The Terai – the plains area which runs along the Nepal-Indian border – has been shut-down for over two months, with schools and businesses forcibly closed and freedom of movement restricted as protestors bring normal life to a standstill. More than 45 people have been killed in violence between the Police and ethnic minority groups. Kathmandu is struggling to run with minimal petrol and gas, resulting in businesses closing, tourists cancelling, and the economy slowly collapsing. Perhaps saddest of all, the 2 million people affected by the earthquake in April – who were pledged $4.4 billion dollars by the international community to help them rebuild safe homes – are yet to receive a…

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The Music of Climate Change II – Sea Ice

At the top of the world, the Arctic Ocean is covered by a floating cap of ice that represents one of the most obvious indicators of global climate change. The sea ice is a semi-permanent feature that grows in the winter and shrinks in the summer.  But the minimum ice extents and volume that occur at the end of summer  have been getting lower and lower.  Warmer oceans and a warmer atmosphere are the basic reasons behind these reductions.  2015 has just produced the fourth-lowest sea ice extent on record, and satellites have been measuring sea ice extents since 1979.

The loss of Arctic sea ice is a big deal – ask anyone who lives next to an ocean. Water has an amazing capacity to absorb (and later re-release) large amounts of heat, and moderate the climate. Reduced sea ice cover also means that more solar radiation is absorbed, instead of being reflected back out by the ice and the snow. In the Arctic, these factors work together to amplify the CO2-induced warming.

The National Snow and Ice Data Center (NSIDC) has compiled daily sea ice extents from multiple satellites. I wrote a little R script that grabs all the daily data from their FTP server, extracts the annual minimum, and calculates decadal means. Then, I went hunting for some music* to accompany the results.


The results. Annual minimum Arctic sea ice extents, 1979 to 2015 (source: NSIDC). Decadal averages and corresponding best-selling album shown for musical context.

The minimum ice extent in 2015 was 4.31 km², a whopping 38% lower than the average minimum extent in the 1980’s (6.96 km²).  The top-selling album of the 1980’s (and of all time, with over 42 million copies sold) was Thriller by Michael Jackson. The timing on the video entry here is fortuitous and completely intentional:

Top-selling album of the 1990’s?  Shania Twain, Come on Over?! Well, get your out your pleather and rock the CanCon, because the minimum sea ice extent in 2015 was 32% lower than in the glorious 90’s (6.42 km²):

Finally, we get to the first decade of the 21st century. I will admit to being surprised by both top selling album of 2000s (Hybrid Theory by  Linkin Park), and the fact that ice extents in 2015 were 21% lower than the 2000 – 2009 mean (5.47 km²).  In the end (pun intended), the decline of Arctic sea ice is dramatic and compelling evidence of global climate change.

*Having to lay myself some ground rules here, I do not include compilations or reissues. Which is unfortunate because the Beatles 1 was technically the bestselling album of the 2000s, but Linkin Park wins instead.