World of Science | Review ISSW2018: Session Snow and Avalanche Dynamics

The first session of ISSW2018 deals with the topic of avalanche dynamics, which examines the flow behavior of avalanches in the broadest sense. Current research is multi-pronged - some scientists study large avalanches experimentally, others try to simulate and measure effects in the laboratory, and others develop and use computer models. Nowadays, computer models are becoming increasingly important and so it is not surprising who got the very first talk at the conference:

What do avalanche dynamics have to do with Disney's animation studios?

For some time now, a win-win situation has been inspiring snow science. During a stay in Los Angeles, the young professor and professional snowboarder Johan Gaume developed a snow model together with Disney that not only looks good but also works exceptionally well (O1.1). If you want to know what it looks like, you can visit the current movie "The Ice Queen 2". If you want to follow the scientific scope of the model, we recommend Johan's Twitter channel or the website of the SLAB (snow and avalanche simulation laboratory) at EPFL in Lausanne.

The fascinating thing about the model is that it simulates the properties of snow and all applications such as fracture mechanics and flow dynamics arise from this. Technically, the model is based on the "Material Points Method" (short explanatory video). Instead of being based on a rigid computational grid, "Material Points" (quasi individual snow grains or granules/snowballs) are defined, which carry properties such as mass, momentum and deformation. This enables simulation over several orders of magnitude - i.e. from the weak layer in the centimeter range to the flow of the avalanche in the hundred-meter range. Furthermore, it is precisely this simulation method that is suitable for modeling transitions from solid mechanics to flow dynamics: The stationary snowpack behaves like a deformable solid, but the avalanche behaves more like a granular fluid.

In addition to the aforementioned statistics through model validation based on many avalanches, probabilistics is another way of approaching the uncertainty of the model parameters. On the one hand, the "poor man's ensemble" can be carried out by applying different flow models; or the sensitivity of a model parameter to the result is considered as uncertainty in the results themselves. Accordingly, the article O1.4 defines the so-called "runout gradient", i.e. the change in a parameter that increases the simulated runout length by 100m. Roughly speaking, doubling the crack width or reducing the friction by 5% increases the runout length by 100m. Such a probabilistic concept thus makes it possible to compare the different errors of the input parameters and to transfer the uncertainty of the parameters to the simulation result.

For more information on avalanche modeling and back calculation of individual avalanches, we recommend the article O1.2 about the avalanche accident in Rigopiano (central Italy), in which an entire hotel was destroyed.

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15 kg of explosives, 100,000 m³ of snow and lots of data

Experimental avalanche dynamics is absolutely fantastic. It is one of the few experimental geophysical disciplines where it still makes a real impact - and when the media are involved, there are not only spectacular images but also a complete car in the avalanche. Of course, the car was not only equipped with cameras, but also with acceleration and rotation sensors to measure the interaction with the avalanche.

Apropos flowing measurements: Two papers describe 3D-printed balls, which are equipped with motion and positioning sensors to record conditions in the avalanche. In principle, avalanche research overlaps here with research on rockfalls, where similar sensors are located in the stones. Individual colored stones can be located quite easily using camera images, but in an avalanche it is more difficult and only the acceleration directions remain to calculate the position of the balls back (P1.2). In response, contribution P1.3 is developing a positioning system based on WLAN, which may be supplemented by radar tracking in the near future.

Large avalanche test sites equipped with many different sensors can be counted on the fingers of one hand. This makes the article P1.8, which reports on a new site in Niseko, Japan, all the more pleasing. In other words, right in the well-known powder ski resort in Hokkaido - measuring and powder skiing at the same time is also an absolute advantage for avalanche researchers. Although the test slopes only have a height difference of around 200m, avalanches that would otherwise be labeled as a "dynamically uninteresting little skier's slide" can be investigated. That's nonsense, of course, because avalanches like this are on the border between flow and dust avalanches. Incidentally, virtually nothing is known about this transition.

Of course, there are also contributions from the most prominent avalanche test site "Vallée de la Sionne" in Valais. The two contributions deal with pressure measurements on a 20m high steel pylon, which stands in the avalanche path and is directly surrounded by water. Article O1.5 deals with the pressure and bending moment due to different flow regimes on the steel pylon. The authors find that dust avalanches mainly cause impulsive, short-term and very high dynamic pressures in the range of up to 1000kPa. In contrast, slow wet snow avalanches cause continuous pressures of around 400kPa due to their high density. As a comparison for the avalanche danger zones, the boundary from the red to the yellow zone is around 10kPa, and the boundary to the unzoned areas is 1kPa. More descriptive: a water column of 1m height causes about 10kPa static pressure.

Another laboratory article repeats a quasi-scientifically correct experiment from 3 years ago, in which snow of different temperatures was shoveled into a concrete mixer to observe the formation of granular snowballs. It was found that at temperatures warmer than -2°C, the snow quickly glopped together from fine-grained snow to fist-sized balls^TM - trivial for Bavarian primary school children, complex result for academics. This contribution P1.16 also uses a rotating drum with a diameter of 2.5m. The improvement over the concrete mixer is speed control and the direct measurement of temperature, liquid water content and flow profile. The limit value of -2°C to -1°C, at which the grain size changes quite abruptly, was also determined.

Wet snow vs. warm snow

After the concrete mixer experiments, the snow temperature was focused on by various avalanche dynamics experts. In contrast to liquid water content, temperature is a classically measurable variable that can be simulated quite well with snowpack models and can also be roughly estimated from historical data. The article P1.14 reports on a possible parameterization of snow temperature in avalanche models. The article on the hotel accident in Rigopiano mentioned above also comes to the conclusion that warm snow in the lower part of the avalanche path was decisive for the long run-out length. Even if the term wet snow avalanche may not be optimal, I personally find the term warm snow avalanche equally weak.

Conclusion

It is always difficult to show the current state of research in a field from contributions to a conference. A lot is certainly happening in avalanche dynamics at the moment, and it will be exciting to see what avalanche science will look like in 10 years' time. Outstanding innovations at ISSW 2018 were definitely the Disney model, the flowing sensor nodes and the fact that several contributions now talk about warm instead of wet snow.