Anomalous snowfall: did it amplify the earthquake-triggered Langtang avalanche?

The disaster that unfolded in Langtang Valley in the moments after the M7.8 Nepal Earthquake on 25 April 2017 is difficult to contemplate. The earthquake-triggered collapse of glaciers high above the serene village of Langtang Valley contributed to a devastating avalanche that swept down from the mountains with a leading edge of straight-line winds that approached major tornado strength.  New research led by Koji Fujita from Nagoya University, published in the open-access journal Natural Hazards and Earth System Science (link), suggests that the avalanche may have actually been composed primarily of snow. The intersection of a rare (1 in 100 to 1 in 500 year) snowpack and a major earthquake (1 in 80 years) led to one of the biggest mass casualty events of the earthquake.


Perspective views of Langtang Village avalanche deposit. (a) orthoimage, and (b) pre- and post-event elevation difference. 

In the paper, we used a combination of data collected from helicopter and UAV surveys in the days and months after the earthquake to quadruple previous estimates of the total volume of the avalanche deposit (Figure 1 above). Koji, who has worked in the valley since the 1980s and is well known by the villagers, also interviewed locals who witnessed the blast to help constrain the sequence of events. Finally, we pieced together weather station data from the valley (ICIMOD/DHM) and regional precipitation fields to determine the return period for a winter snowpack of this magnitude.

The winter of 2014-2015 was particularly wet: the passage of Cyclone HudHud in October 2014 dropped upwards of 300 mm of precipitation in the Langtang region, and caused numerous avalanche fatalities on the famed Annapurna trekking circuit.  When I visited Langtang Valley after the earthquake, most of our stations appeared to be destroyed by earthquake-triggered avalanches.  However,after recovering the dataloggers and downloading the data, it became clear that some were toppled in the middle of winter by avalanches that also took out entire yak herds (according to the locals I spoke to).

The stations that remained standing during the winter told the story of near-continuous snowfall from early March to 25 April (Figure 2). If snowfall during the typhoon is included, snowpacks may have been up to 3.5 m at high elevations. This snowpack only needed a trigger to go off, and on 25 April at 11:57, it got two: one from the ground motion, and one from the glacier ice cliff collapses.


Our results have been shared with both local and government officials, but hotels have already started to appear in the rubble that lies over the avalanche.

Press release (English)


APECS webinar on work + life in the Himalayas

On the second anniversary of the Gorkha Earthquake, I gave a webinar on my time based in Kathmandu for the Association of Polar Early Career Scientists (APECS). It was primarily a research talk, but targeted towards early career researchers who may be contemplating a non-traditional position (i.e. not a post-doc or a tenure-track position). To keep the talk interesting I also got to talk about mountain biking, being in a Kathmandu cover band, and my personal experiences in dealing with the earthquake.

Its also my first webinar, and I have to admit that its a bit disconcerting to talk to 40 or so people without any feedback or visual clues as to how you’re doing. If you’re interested, the presentation and audio can be seen here:

UAV work in the Canadian Rockies

Believe it or not, its not as easy as UAV work in the Himalayas. My UAV partner-in-crime Philip Kraaijenbrink (PhD candidate at Utrecht University) recently joined the Coldwater Lab in Canmore, Alberta, for a few weeks. Here is his honest assessment:

Our goals with these repeat surveys during the melt season (April – ????) are to develop estimates of snow melt rates from a variety of slope aspects and angles, to look at thermal aspects of snow melt (enhanced melt rates and heat advection from vegetation, rocks), and to build datasets that can be used to validate distributed snow hydrology models.

We’ve only managed to sneak in one flight so far, but the new S.O.D.A. camera from senseFly seems to work very well with the eBee RTK.


A rare moment of relative calm, jacket thrown over the laptop to try and cut the glare from the snow.


From our first flights of 2017: a closeup of the digital elevation model with shading (left) and the same scene shown as an orthoimage (right). Sleds show up nicely, and you can even see our footprints in the snow heading to the upper right corner of the scene.


As of 1 December 2016, I will be joining the Coldwater Laboratory in Canmore, Alberta, as a Research Scientist!


New horizons! Canmore, from Ha Ling Peak. Our new office is somewhere down there.

The Coldwater lab is part of the Centre for Hydrology at the University of Saskatchewan. I am really excited about the opportunity to work with Dr. John Pomeroy and his crew of students, post-docs, technicians, and colleagues. Our work will focus on snow and ice hydrology, mountain hydrometeorology, forest hydrology and climate change. 

I am still involved with the International Centre for Integrated Mountain Development (ICIMOD, Kathmandu) as a Visiting Scientist, and look forward to continuing the collaborations and friendships I developed during my four years in Nepal.

My new position will keep me closer to family and brings me back to the mountains I cut my teeth on during my university years and my M.Sc. It’s great to be back home!





IGS 2015 Poster: On-glacier weather station observations

Here’s a poster I presented last year at the ICIMOD-International Glaciological Society symposium in Kathmandu. The time series plots were done in R ggplot, the study area map in QGIS, and everything was put together in Inkscape.

The goal was to clearly and simply present some initial results from our high-altitude on-glacier meteorological station. Standing beside the poster, it was easy to point readers to the interesting highlights (surface albedo, monsoon onset and withdrawal). As chair of the local organizing committee, it was great to just stand beside the poster and talk science for a few hours – but I think the poster design provides opportunities for discussions.  71A1604.png

Glacier Collapse, Tibetan Plateau

[Put this together with Simon Gascoin (CNRS – Toulouse) after a request from Brian Kahn, at Climate Central, @blkahn]

Recent posts by NASA and Nature describe a mysterious glacier collapse on the Tibetan Plateau:


Figure 1: Sentinel-2 imagery acquired 24 July 2016, after the event (NASA; S. Gascoin)

This event really has no precedent, and no apparent trigger. Possible mechanisms for the collapse could be earthquake, rockfall on the glacier, or excessive melt or precipitation leading to extremely high water pressures at the glacier bed. There are no reported earthquakes in the region around the timing of the event (17 July; A small mass movement on the southeast slopes above the glacier appear as a dark streak in the post-event imagery, but it doesn’t appear to be big enough to trigger the ice avalanche, and may have occurred because of the avalanche.

Is there a climate signal in this event? Right now the answer appears to be no. Excessive melt does not appear to be likely, as surface temperatures based on NCEP/NCAR reanalysis are only slightly above normal (+1 to +2C) in the region from June 2016 – July 2016 (Figure 2). Much higher temperature anomalies occurred in the Pamirs and Karakoram region (but no glacier collapses were reported there).  The Global Precipitation Mission satellites show decent precipitation in the region in the 24-48 hours prior to the event (Figure 2), but not at the site. Local measurements would help confirm if the event was triggered by precipitation.


Figure 2: Surface air temperature anomalies [C] for May-June-July 2016. Departures from 1981-2010 climatology (NCEP/NCAR)


Figure 3: Mean precipitation rate [mm/hour], 16-17 July 2016, from GPM (source:

The glacier is heavily crevassed, or broken up, above the detachment point (Figure 4), and it appeared to be in a similar shape before the event. Beyond this basic information there are no clues. But low-angle glaciers generally don’t just slide off mountains, so the field investigations and local data will be really important for determining the cause of this disaster.

The risk of natural hazards is amplified in the mountains and by the mountains. And climate change generally acts to enhance these risks even further. In the Himalayas, glacier changes are leading to the formation of lakes that can pose downstream flood risks (e.g. Dig Tsho, Nepal); the loss of glaciers can reduce the stability of mountain slopes and lead to landslides; and extreme precipitation events can cause severe, rapid, and widespread flooding (Pakistan 2010 and Uttarakhand 2013). And as we saw in Nepal in 2015, and now here on the Tibetan Plateau, glaciers can release deadly snow and ice avalanches.

If this event is climate related, its another ominous sign for the future.


Figure 4: Sentinel-2 imagery of the Aru Co slide, acquired 21 July 2016, and enhanced for better contrast in glacierized areas (S. Gascoin)




Glacier research and climate change in the Himalayas

[I still think the iceman is a good hook. Fun stuff here from Susan Hale-Thomas, who can actually hold her own in the field]


I envisioned him encapsulated within the ice — eyes open, satellite phone clutched in his gloved hand pressed to a sunburnt ear, his cracked lips straining to form his last word before the cold overtook him and he froze to death.

This tale of a dead mountaineer was shared with me by our Sherpa guide on a recent research trip that I joined. In my mind, his fate was ours, if anything were to go wrong.


A four-hour walk from the last village in the valley, our group — five glaciologists, one university student, and I — stopped to rest at the base of a steep hill at the uninhabited end of Langtang Valley. We had one last climb before reaching a high alpine meadow that would be our base camp for the next several days.

Looking back down the valley, heavy clouds were rolling in behind us. Earlier…

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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.