From volume 119, winter 2018-19

By Laura Maguire and Jesse Percival

COGNITIVE SYSTEMS ENGINEERING (CSE) demonstrates how expert practitioners in high risk/high consequence domains make sense of risk in dynamic, ambiguous and changing conditions. Expert performance is identified as going beyond qualifications to include the ability to activate, organize and flexibly apply knowledge (Woods et al, 2010) in time pressured, goal conflicted and uncertain conditions. To do so involves cognitive work.

Using methods from CSE, this study assessed the operational aspects of snow safety then analyzed the artifacts (tools such as worksheets, websites, whiteboards, InfoEx, etc.) that shape cognition and collaboration. Semi-structured interviews were used to detail how tools are used to make and update forecasts over time. Finally, we elicited examples of surprise, near misses and actual incidents to calibrate findings.

Three prominent, interconnected themes emerged from the research:

1. Much of the cognitive work is not described in the explicit protocols. The formal representations of what constitutes good practice in forecasting is a small fraction of the strategies experts use.
2. The cognitive effort required to manage avalanche risk is a near continuous activity. Forecasting appears to require ongoing calibration. Disruptions to this calibration process have adverse effects on performance.
3. Forecasting is a distributed cognitive task across individuals, teams and the broader industry. Successful forecasting requires distributed practitioners of local team members as well as the resources and insights produced by others within the industry.

MT. WASHINGTON FORECAST TEAM EXAMINING THE SNOWPACK AND MENTORING NEW MEMBER // JESSE PERCIVAL

PREPARATIONS FOR FORECASTING
Formally, the protocols for a forecaster on duty (FOD) suggests producing a control plan shortly after arriving onsite - but each forecaster interviewed detailed extensive preparations that were not captured by the formal description. A variety of work-related techniques were described. For example, time spent carpooling is used as an informal handoff from one FOD to another to discuss recent activity or control measures. This suggests that formulating the day’s forecast begins well in advance so that a forecaster arrives for duty with a hypothesis of how recent changes in conditions affect their avalanche terrain management.

Shared, off the books activity is a common (and likely necessary) practice not explicitly noted in work procedures and demonstrates a need for ongoing calibration – an example that supports all three findings. It is well documented that forecasting takes place under time pressure. By seeking out data that can help them anticipate conditions in advance, the FOD relieves some of this pressure to lessen the cognitive demands required once they officially clock in.

DISRUPTION, ADAPTATION & SURPRISE
A second example: An unexpected in-bounds release. On this day, the forecasting plan had anticipated instabilities due to temperature changes. After control work, it was expected that normal monitoring would identify if a closure was necessary. However, a personal emergency meant the team was operating one person short. Concurrently, a first aid emergency tied up members who would otherwise be monitoring avalanche terrain. This left the FOD ‘in the bump’ for longer than the usual rotation and his normal practice was interrupted. As expected, the temperature fluctuated and a skier-triggered release occurred in one of the avalanche zones.

This example is informative in two ways. Firstly, it is reflective of what “normal work” is – constantly adjusting to workload demands or unavailability of resources and adapting practices to respond to conditions while balancing inevitable tradeoffs. Secondly, this example provides evidence that practitioners construct mental models (Adams, 2005) and continually update them.

THE BIG PICTURE - MOUNT WASHINGTON // COLE RAMSHAW

MENTAL MODELS
The model is an internal representation of current hazards and an expectation of how this may change over time. Mental models are used to retrieve technical knowledge and to flexibly apply it to variable situations.

In constantly changing conditions, mental models become stale unless continually updated. Referring to the in-bounds avalanche example, the model became insufficient after only a few hours. In the previous example, the forecaster coming back from time off is aware their model is stale and seeks information to recalibrate. LaChapelle (1980) notes a “...prevalent and strong reluctance of working forecasters to experience an interruption in their winter routine…” (pg. 78). This finding emphasizes organizing work schedules to protect forecasters’ daily and seasonal monitoring routine from interruptions or building in mechanisms to support rapid recalibration or redundancy by cross-checking across other team members.

DISTRIBUTED COGNITIVE EFFORTS
Notable as well, is the role of a distributed network in constructing mental models. A diverse range of perspectives informed by different experiences, knowledge and mindsets is needed for accuracy. In the resort, the schedule for FOD’s is designed to provide an overlap day to accommodate the need for distributed cognition. This is an explicit recognition of both ensuring currency of the mental model and the importance of interactions between practitioners. Updating provides an opportunity to draw attention to details and to generate shared insights.

Spatial and temporal constraints also require distributed cognitive efforts. Large terrain and limited daylight hours create time pressures. The FOD relies on technicians to gather and relay data efficiently and accurately. Without the team, the FOD’s mental model can only partially represent actual conditions.

WITH UNCOMMON SNOWPACKS BECOMING INCREASINGLY COMMON, PRACTITIONERS IN A COASTAL SNOWPACK HAVE BEGUN DEPLOYING NEW STRATEGIES // JESSE PERCIVAL

CONCLUSIONS
Errors by normally high performing experts are insights into how the cognitive demands may become temporarily overwhelming. Studies like this illustrate what aspects of practice should be protected from the pressures of ‘faster, better, cheaper’ common in many workplaces and allows for better engineering of the tools, technologies and protocols used.

Further research can provide an empirical basis for: designing decision support tools; developing training; orchestration & distribution of tasks; funding critical resources; and developing new forms of coordination across networks. Identifying cognitive work in different forecasting settings (mechanized skiing, transportation, industrial) is likely to be useful for accident prevention. In addition, CSE studies comparing expert vs recreational cognition is likely to help public safety efforts.

The authors gratefully acknowledge the Avalanche Canada Foundation for their travel support through the ISSW Fund and the Cora Shea Memorial Fund. For the complete proceedings paper or more information about this and other projects in cognitive work of avalanche forecasting contact Laura (maguire.81@osu.edu) or Jesse (jperceival@mountwashington.ca)

REFERENCES:
Adams, L. (2005). A systems approach to human factors and expert decision-making within Canadian Avalanche Phenomena. MALT Thesis. Royal Roads University,
Victoria, BC, 284.

LaChapelle, E. R. (1980). The fundamental processes in conventional avalanche forecasting. Journal Glaciology, 26(94), 75–84.

Woods, D., Dekker, S., Cook, R., Johannesen, L., Sarter, N. (2010). Behind Human Error. London: CRC Press.

From volume 96, spring 2011

By Bruce Jamieson, Dept. of Civil Engineering, Dept. of Geoscience, University of Calgary, Calgary AB, Canada
Jürg Schweizer, WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Grant Statham, Parks Canada Agency, Banff AB, Canada
Pascal Haegeli, Avisualanche Consulting and Simon Fraser University, Vancouver BC, Canada

ABSTRACT

At the 2004 ISSW, Roger Atkins proposed that—early in the terrain selection process—backcountry travellers could identify which types of avalanches were likely, e.g. wind slab, persistent slab, wet avalanche. These avalanche types are analogous to a set of scenarios in traditional risk analysis. Variations on Atkins’ approach have been incorporated into some public bulletins. The types of avalanches that dominate the danger ratings are called Avalanche Types/Characters/Threats/Concerns/Situations/Problems by different groups. The latest Swiss brochure for recreation in avalanche terrain suggests different observations for the four different types of avalanche situations. To help determine which observations are best for which types of avalanches, a field study was conducted in the winters of 2008-09 and 2009-10 in the Coast Mountains, Columbia Mountains, and Rocky Mountains of western Canada. On each field day, an experienced field team rated the local avalanche danger, identified two dominant avalanche types and observed a standard set of over 20 quick field observations. The quick observations included avalanches, wind transported snow, snowfall, etc. For correlation analysis, we focussed on two distinct classes of avalanche types: 1) persistent slabs, and 2) wind slabs combined with storm slabs. While some observations correlated with the local danger when either class of avalanches dominated the danger rating, other observations correlated best when only one of these two classes dominated the local danger rating. These results may help bulletin writers recommend that recreationists focus on certain local observations for better informed decisions.

INTRODUCTION
For decades, risk analysts for natural hazards have identified distinct scenarios (or potential events) which threaten something of value e.g. property or infrastructure. For each scenario, the probability of the natural event affecting the thing of value and the expected consequences are estimated (Kaplan and Garrick, 1981). Mitigation, if required, typically focuses on the scenarios with the highest risk (combination of probability and consequences). If the probability and consequences for each scenario can be quantified, the risk for the can be graphed as in Figure 1. If either the probability or consequence can only be ranked (not quantified), the scenarios are usually presented in a risk matrix (e.g. Ahrens, 2008, p. 22-24). The scenarios with the highest risk (or unacceptable risk) can be targeted for mitigation. This established approach to risk analysis has been used for long-return period avalanches that can affect property (e.g. Wilhelm, 1998). The same concept is also used informally by guides, forecasters and experienced recreationists, who often focus on one or two types of avalanches (scenarios) when assessing the risk on the terrain being considered for the current day.

For many years some Swiss guides and avalanche educators have proposed asking: “What is the main danger today?” On most days, it can be decided whether it is either a New Snow, and Old Snow, or a Wet Snow situation.

Once the situation is recognized, the mitigation strategy can be adapted (Wassermann and Wicky, 2003). Stephan Harvey has further formalized this approach, called it pattern recognition and added one more situation: Wind Driven Snow, when an increased avalanche danger often prevails (Harvey, 2008).

In parallel with the Swiss development of Avalanche Situations, at the 2004 ISSW in Jackson Hole, Roger Atkins proposed that the probability and consequences be assessed separately for different types of avalanches, e.g. wind slab, persistent slab, wet avalanche, so the decision makers could focus on the one or two scenarios (Avalanche Types) that posed the greatest risk. Some of his avalanche characteristics incorporated terrain, e.g. wind slabs near ridge tops.

Atkins’ concept was used by the Avalanche Danger Scale Project, which was a Canada-US part of the multi-agency project called Avalanche Decision Framework for Amateur Recreationists 2 (ADFAR2). Starting in 2005, the committee of mostly forecasters took a fresh look—actually fresh look after fresh look—at the forecasting process. When they finally had a consensus, the Avalanche Type was a key component of their conceptual forecasting model (Statham et al., 2010). Definitions for the different types of avalanches have been developed. These definitions were the basis for incorporating Avalanche Problems into Canadian avalanche bulletins (Klassen, 2010).

Most recently, Avalanche Type been used as the central theme in a field book for decision-making in avalanche terrain published by the Canadian Avalanche Centre (Klassen et al., 2010). The field book contains templates for recording the relevant observations and facilitates decisions when preparing for and travelling in avalanche terrain.

The concept of Avalanche Type has been and will continue to be applied at various scales. At the slope scale, experienced forecasters and guides can visualize certain types of potential avalanches on the terrain. At the regional scale, some avalanche forecast centres have started to use one, two, or occasionally three Avalanche Types in their public bulletins. Although there is as yet no consistent terminology (Table 1), the concept has caught on and is now used in various applications.

When updating the popular Swiss avalanche awareness brochure “Caution – Avalanches!” the idea of Avalanche Situations was merged with the reduction method with the classical 3x3 framework (Harvey et al., 2009). For each of the four Avalanche Situations, a number of key observations are proposed to help recreationists focus on the most important observations for the day (Table 2).

Early experience with this scheme suggests that on some days it is difficult to distinguish between new snow and wind driven snow. Also, the debate continues about whether to explicitly recommend digging when old snow is the dominant avalanche situation. On the other hand, the emphasis is not on digging when either new snow, wind driven snow or wet snow is the primary avalanche situation.

The relevant observations for each Avalanche Type in Table 2 are based on experience and an understanding of the processes that form the different types of potential avalanches. Haegeli and Atkins (2010) also present key observations from a survey of experienced avalanche professionals. For this study, we set out to use field data (independent of theory or experience) to identify some key observations when different types of avalanches were dominating the danger rating.

METHODS AND DATA
Since the winter of 2007, the Applied Snow and Avalanche Research group at the University of Calgary (ASARC) has been rating the local avalanche danger and making a standard set of over 20 observations (e.g. Jamieson and Haegeli, 2008; Appendix A). Starting in the winter of 2009, we began daily rating the top two Avalanche Types so we could assess which observations were “best” for the various types of expected avalanches. This paper summarizes the results from the winters of 2008-09 and 2009-10.

On most field days in the winters of 2008-09 and 2009-10, ASARC’s field teams in the Coast Range, Columbia Mountains and Rocky Mountains rated the local avalanche danger, made over 20 standard observations (Appendix A), and identified the two most important Avalanche Types (Table 1). For this study we used only the Avalanche Type with the greatest importance—based on its contribution to the danger rating. If the two avalanche types had equal importance (50:50), we used the one recorded as Avalanche Type 1.

Many of the observations were made before and after the decision point, i.e. when the team reached treeline. For each observation, e.g. blowing snow, we used the before or after observation that was more conducive to higher avalanche danger. So, if we observed blowing snow in the morning but not in the afternoon, we used the morning observation.

For most of the observation variables, the specific observation values could be ordered from the least associated with avalanching to the most. For example, the observations for blowing snow were ordered: none, at ridge, below ridge.

Appendix A shows that we rated the local danger for one, two or three elevation zones: below treeline, treeline and alpine. We used the treeline rating, except in four cases in which we did not rate the local avalanche danger at treeline, in which case we used the below treeline rating.

In a few cases in which the precipitation was rain, we treated the precipitation rate as missing. This resulted in the dataset shown in Table 3. Each case is a record of one field team travelling on touring skis in a specific area on a given day.

We excluded Loose Avalanche and Wet Avalanche types from the analysis since there were too few cases. Also because of limited cases, we combined Storm Slab with Wind Slab, and combined Deep Persistent Slab with Persistent Slab.

PRELIMINARY RESULTS
Spearman rank correlations between the local danger rating and the ordered observations are shown in Table 4. Correlations for which p < 0.05 are marked in bold. Correlations for which p < 0.01 are marked in bold italic.

Observations that correlated when either class of Avalanche Type was important?
When either Wind Slab/Storm Slab Avalanches or Deep/Persistent slab avalanches dominated the danger rating, the observations that correlated with the local avalanche danger were: slab avalanches, whumpfs/shooting cracks, clumps of snow falling off trees (tree bombs), deep ski penetration, snow height (snowfall) from in last 24/48 h, and air warming to 0°C (negative) (Table 4). The negative correlation prompted a second look at the data: when the air temperature reached 0°C (usually spring time), the avalanche danger was mostly Low or Moderate.

Observations that correlated when storm snow or wind slabs were important?
In addition to the observations mentioned in the previous paragraph, the snowfall rate, increased hand shear depth and absence of a surface melt-freeze crust correlated with the local avalanche danger when storm snow or wind slabs dominated the danger rating (Table 4). The key variables include the following observations of current or recent snowfall: snowfall rate, accumulated snowfall in the last 24/48 hours, as well as deep ski penetration.

Observations that correlated when deep/persistent slab avalanches were important?
In addition to the observations mentioned for both classes of Avalanche Types, low hand shear resistance, pinwheeling, and snow surface cracking at skis correlated with the local avalanche danger when Deep/Persistent Slab Avalanches dominated the local danger rating.

DISCUSSION
The observations proposed by the Swiss avalanche awareness brochure Caution – Avalanches! (Harvey et al., 2009) and the Canadian Avalanche Centre field book (Klassen et al., 2010) are supported by the correlations in Table 4. For a New Snow Avalanche Situation, recent slab avalanches and new snow amount correlated with the local avalanche danger. For an Old Snow Avalanche Situation, whumpfs correlated with the local avalanche danger. Some correlations, such as the one between pinwheeling and the local danger when Deep/Persistent Slabs are important, are difficult to explain and may not be significant in a larger, more balanced dataset.

For Deep/Persistent Slabs, fewer observations correlated with local danger than for Storm Snow and Wind Slab Avalanches, which is consistent with the greater forecasting challenge for persistent slabs. See also the limited relevant observations in Table 2 for the Old Snow Avalanche Situation.

Research often yields unexpected results. When ASARC’s morning stability evaluation was expanded to include identification of the one or two most important Avalanche Types, one of us (Jamieson) expected the usual response to increased paperwork. Instead, the field staff liked the focus that Avalanche Type provided to the morning safety meeting and has retained it. The Avalanche Type is just one part of the rethinking of the forecasting (Statham et al., 2010) that has become popular with ASARC’s field staff.

SUMMARY
Several regional forecast centres have adopted the concept of Avalanche Character/Type/Threat/Concern/Situation/Problem for use in their public bulletins. This concept is consistent with the scenarios in traditional risk analysis. Harvey (2008) has proposed specific observations for certain classes of Avalanche Situations. For this study, we analysed a dataset of 159 cases (locationdays) in which over 20 observations were made and the local avalanche danger was rated. When the dominant Avalanche Type was either Storm Avalanches or Wind Slabs, the observations that correlated (and were consistent with knowledge of avalanche formation) included recent slab avalanches, snowfall rate, snow clumps falling from trees (usually indicative of wind or warming), deep ski penetration and snow height from the last 24/48 hours. When the dominant Avalanche Type was either Deep Persistent or Persistent Slab, the observations that correlated (and made sense) included recent slab avalanches, whumpfs/shooting cracks, deep ski penetration and increased snow height from the last 24/48 hours.

Further field studies are planned. There are other observations that correlated in this study and may benefit from analysis of a larger dataset. However, any recommended observations should be consistent with the current understanding of the processes that form the different types of avalanches.

ACKNOWLEDGEMENTS
For the careful field work we are grateful to Cam Campbell, Spencer Krkosky, Deanna Andersen, Lydia Marmont, Peter Marshall, Chris Geisler, Ali Haeri, Cameron Ross, Thomas Exner, Mark Kolasinski, Katherine Johnston, Cora Shea, Mike Smith, Dave Tracz and Jordan Stiefvater. Thanks also to Mike Smith for proofreading, to Cameron Ross for checking the data and Dave Gauthier for checking the analysis.

For logistical support for the field studies we thank Mike Wiegele Helicopter Skiing, BC Ministry of Transportation and Infrastructure, BC Ministry of Parks, Parks Canada, the Canadian Avalanche Centre, as well as the Avalanche Control Section of Glacier National Park.

For financial support for the field studies and the first author’s time, we thank the Natural Sciences and Engineering Research Council of Canada, HeliCat Canada, the Canadian Avalanche Association, Mike Wiegele Helicopter Skiing, Teck Mining Company, Canada West Ski Areas Association, the Association of Canadian Mountain Guides, Backcountry Lodges of British Columbia, and the Canadian Ski Guides Association.

REFERENCES
Ahrens, T. 2008. Risk Analysis. John Wiley & Sons, Chichester, England.

Atkins, R. 2004. An avalanche characterization checklist for backcountry travel decisions. Proceedings of the 2004 International Snow Science Workshop in Jackson Hole, Wyoming, USA, 462-468.

Haegeli, P., Atkins, R. 2010. Exploring the ‘It depends’ – How do mountain guides assess avalanche situations? In Osterhuber,

R. and Ferrari, M. (eds.), Proceedings of the 2010 International Snow Science Workshop in Squaw Valley, California, USA, 130-132.

Harvey, S. 2008. Mustererkennung in der Lawinenkunde. In: I. Kroath (Editor), Sicherheit im Bergland. Oesterreichisches Kuratorium für Alpine Sicherheit, Innsbruck, Austria, pp. 88-94.

Harvey, S., Schweizer, J., Rhyner, H., Nigg, P., Hasler, B. 2009. Caution - Avalanches! 6th edition. Avalanche Prevention in Snow Sports, Core team of instructors, Davos, Switzerland.

Jamieson, B., Haegeli, P. 2008. Can field observations be combined systematically with the regional danger rating to estimate the local avalanche danger? Proceedings of the 2008 International Snow Science Workshop in Whistler, BC, 228-237.

Kaplan, S., Garrick, B.J. 1981. On the quantitative definition of risk. Risk Analysis 1(1), 11-21.

Klassen. K. 2010. The Avalanche Hazard Assessment Web-tool – A structured approach to public avalanche forecasting. Presentation at the Spring Conference of the Canadian Avalanche Association, 6-7 May 2010.

Haegeli, P., Atkins, R., Klassen, K. 2010. Decision Making in Avalanche Terrain. Canadian Avalanche Centre, Revelstoke, BC, 62 pp.

Statham, G., Haegeli, P., Birkeland, K., Greene, E., Israelson, C., Tremper, B., Stethem, C., McMahon, B., White, B., Kelly, J. 2010. In Osterhuber, R. and Ferrari, M. (eds.), A conceptual model of avalanche hazard. Proceedings of the 2010 International Snow Science Workshop in Squaw Valley, California, USA, 686.

Wassermann, E., Wicky, E. 2003. Lawinen und Risikomanagement. Edition Filidor, Reichenbach, Switzerland, 60 pp.

Wilhelm, C. 1998. Quantitative risk analysis for evaluation of avalanche protection projects. In Hestnes, E., ed. Proceedings of the Anniversary Conference 25 Years of Snow Avalanche Research, Voss, 12-16 May 1998. Oslo, Norwegian Geotechnical Institute, Publication 203, 288-293

From Vol. 101, fall 2012

By Rod Gee

Glide slab explosives control results, 50 mile path. Skeena River corridor, west of Terrace, BC. By Rod Gee

My twenty-five year glide slab education began on an early morning in January 1989. A snowplow operator on Highway 16 west of Terrace reported witnessing a Size 3.5 airborne wet avalanche cross the railroad and highway corridors.

The deposit pushed sections of concrete guardrail into the Skeena River. Fortunately, no one was involved. I arrived at the site shortly after hearing the plow operator’s report. “Argh! It’s the glide slab I’ve been monitoring for the last week," I thought; "Why this morning? It’s not raining, and it’s not warm. Why did it run now? Were there indicators I’d missed?”

I came to the north coast of British Columbia to work in CN Rail’s Skeena avalanche program. I brought seven years of work experience in the Rockies, and ITP training in the Selkirk Mountains and the Coast Ranges. However, I had minimal knowledge of glide slab behaviour.

Glide slab prediction is a challenge, compared to the relative predictability of most maritime snowpack avalanche activity. They are classic poster children for the discussion surrounding why “Hazard Level 2” is perhaps a better descriptor than “Stability Good, with the occasional size 4.” Without start zone instrumentation monitoring glide rates, the CN Skeena program offsets uncertainty to some degree with frequent explosives control, and, where effective, runout zone earthworks.

These are some of the observations on formation and natural initiation I now use to evaluate glide slab stability:

• A low-friction ground surface is important for slab formation, but the degree of support from terrain features immediately below the slab is at least as important for slab failure.
• Rapid, early season snowpack accumulation associated with relatively warm air temperatures increases the likelihood of early- and mid-season glide slab formation.
• Lack of an effective ground freeze prior to snowpack accumulation results in increased mid-winter glide rates.
• Rainfall and meltwater percolation in an isothermal starting zone snowpack may accelerate glide rate by decreasing friction at the slab/ground interface. Free water may also decrease the strength of the supporting snow downslope of the glide slab as well as the slab itself. Rain falling into the glide crack above the slab, likely has a similar net effect. However, rain does not
  guarantee slab failure it is only part of the equation.
• Glide slab failure does not require an isothermal snowpack. Failure may occur before the snowpack becomes isothermal or during the overnight cooling phase of the diurnal cycle,
  and without free water being present at the snow/ground interface.

Explosives Initiation
The ideal condition for explosives control occurs when the slab itself maintains a degree of strength greater than that of the snowpack below the toe and along the flanks of the slab. In an ideal scenario, a combination of terrain and weather factors unbalances the downslope snowpack stress/strength relationship to a greater degree than within the slab itself. The toe and flanks
are now barely able to support the loading of the gliding slab. Explosives applied at this time cause slab initiation by triggering a failure of the snowpack at the toe of the slab.

Technicians Herb Bleuer and Mike Zylicz began experimenting with charge quantity and placement in the Skeena corridor in the early 1980s. They realized that conventional charge quantity was usually insufficient for glide slab initiation, and that charge placement was extremely critical.

They also realized that placing the explosives charge into the glide crack above the slab was ineffective because that was not where the stress/strength relationship was deteriorating. Effective
glide slab control is about “kicking the knees out” from under the slab, and not adding load to the slab itself. Their testing produced reasonable results using 100-150kg ANFO charges placed at the toe of the slab.

The best charge placement is a very specific point where the gliding slab is having the greatest effect on the non-gliding downslope snowpack. Current Skeena corridor glide slab control strategy includes the use of charges of 150 and 500kg on 200-500cm deep slabs. Large charges are used because they increase the likelihood of triggering, which reduces hazard at the runout zone transportation corridor and minimizes the likelihood of natural events disrupting rail operations.

That said, control is not always successful. A complex, ever-changing interplay of factors affects glide slab stability, and the puzzle is not completely understood.

Some factors I consider in evaluating explosives control effectiveness include:

• Control is more likely to be successful on glide slabs poorly supported by the terrain below the slab. For example, a poorly-supported glide slab can be initiated with explosives so it will then trigger a better supported glide slab lower in the starting zone that does not respond to explosives.
• Rain or melt-water at the ground/snow interface is not essential for initiation to occur, but it does increase the likelihood.
• Initiating sections of glide slabs is useful both by reducing the deposit volume of a single occurrence, but also because it exposes the ground surface to solar radiation, which then potentially aids in increasing glide rate by introducing more heat into the slab’s basal layers.
• The strength of the snowpack below and alongside the slab allows the slab to glide a significant distance downslope without failing. Increasing glide rate may indicate decreasing snowpack strength.
• A 300-600cm slab can easily glide 50-100m without initiating if the downslope snowpack and terrain accommodates the glide’s loading effect. Increasing glide rate and/or deteriorating strength of the snowpack supporting the slab are two critical initiation factors.
• Three reliable nearby indicator paths I use to assess an east aspect path prone to glide slab formation have a northwest aspect, but the starting zones are at the same elevation. This
  suggests ambient air temperature affects glide slab behaviour to a lesser, but still relevant, degree.

Prediction and control have improved since the 1980s, but we still include a healthy dose of “art” to the “science” of our craft. Explosives control in January 2012 put a size 4 deposit within 2m of the rail roadbed. Is our understanding of glide slab management improving, or were we just lucky on that mission?

Rod Gee is a CAA and AAA Professional member with 30 years industry experience. His association with Chris Stethem and Associates Ltd. from 1985 to 2011 provided participation in a broad variety of Canadian avalanche programs. Rod is owner of Northwest Avalanche Solutions Ltd., and is based in Terrace, B.C.

From vol. 111, winter 2015

By Colin Zacharias

Conducting an extended column test. Photo by Colin Zacharias

THE WEIGHT OF EVIDENCE
Every winter day we make snowpack observations and extrapolate from observation sites to nearby terrain. Most days, for most avalanche problems, this extrapolation process works and we make key decisions from comparatively few quality bits of information. But it is easy to lose confidence in our abilities when conditions become unfamiliar or our information becomes scarce.

Outside of current avalanching and other alarm signs, and especially during periods of high snowpack variability, experienced observers tend to steer away from drawing quick conclusions from a few snowpack observations. They recognize that one test is just one observation, and to counter possible extrapolation errors they ensure that over the critical timeframe key information is supported and verified.

On the other hand, inexperienced observers may apply too much importance to a persuasive snowpack test result or a single avalanche occurrence and be subject to a confirmation bias. Experienced forecasters, even with a decent amount of information, recognize that at times their best is still in the end just that.

Karl Klassen, Avalanche Canada Public Avalanche Warning Service Manager and mountains guide, recently reminded me with a nice touch of irony that while our data -> information -> knowledge -> wisdom hierarchy (Zeleny 1987) fits into a neat little package, it can also backfire. Depending on the quality and quantity of the data set, its relevancy, and our ability to interpret the info, data isn’t information and information isn’t knowledge, and if one thing is certain, wisdom is a different kettle of fish.

There are times when logistics make it difficult to add weight to the evidence. Poor weather or difficult travel conditions, for example, may prevent access to terrain or study sites. Yet even then assumptions are made and conclusions derived. As Dr. Bruce Jamieson notes in his mountain snowpack presentation for the ITP Level 2 Module 1, “inaccurate assumptions can have serious consequences” when it comes to spatial variability in the mountain snowpack.

Decisions made from a deficit or even partial deficiency of information required to understand the avalanche problem are considered uncertain in light of an applied risk management strategy (as defined by ISO 31000). In the avalanche world we are okay with uncertainty—so long as we know what we don’t know. We understand that as the measure of uncertainty increases so does that long arm of caution when planning to reduce the risk.

In today’s avalanche world in Southern BC and Alberta, professionals rely on a daily information exchange to help manage the complexity of snowpack/terrain variability, to provide a “heads up” early warning system or a nearest neighbor confirmation— “yes, they’re seeing what we’re seeing.” Each day we scan through thousands of bits of data and information on the InfoEx, then go into the field and gather more, aggregate the data into information packets, and analyze and communicate patterns that we refer to as hazard factors.

This article, along with the “How Useful Is the Evidence?” table below, was developed in the fall of 2011 as part of an Avalanche Operations Level 2 Module 3 training course handout to help learners apply the notion of strength and weight to field observations, to use a checklist style verification process, and to encourage quality craftsmanship and a thorough approach when analyzing and discussing snowpack factors. It may help the learner to recognize whether or not their evidence drawn from snowpack tests is helpful to their decisions.

Fig. 1: From CAA Level 2 Module 3 handout

CRAFTSMANSHIP AND CONSISTENCY
“Jeez…. the weather and snowpack vary enough; can’t we all just do the same damn observation the same damn way?”

Regional and operational consistency with technique, application and interpretation ensures the quality of data gathered, recorded and communicated. On professional level avalanche training courses, instructors inform that practice, technique, and a meticulous day-to-day consistency with observations, recording and communication should never be undervalued, nor should the scope of the task be underestimated:

• Ensure that there is an objective for each snowpack test. The early morning safety meeting agenda usually includes assessing the day’s avalanche problem and identifying gaps in knowledge. Know what you’re looking for prior to looking.
  
• Select relevant sites for field test sites using experience and the seasonal observation of how the snow is layered over the terrain. Once sites have proven their worth, they are repeatedly used season to season.
  
• Conduct tests skillfully using standardized, practiced techniques. Observers use established guidelines when conducting, recording, and communicating weather, snowpack and avalanche observations; these come from Observation Guidelines and Recording Standards for Weather, Snowpack and Avalanches (OGRS) and Snow, Weather, and Avalanches: Observation Guidelines for Avalanche Programs in the United States (SWAG).
  
• Ensure consistency within an operation by having employees conduct observations side by side. Discuss technique and compare interpretation during preseason staff training.
  

THE RIGHT TOOL FOR THE RIGHT JOB
The CAA’s OGRS and the AAA’s SWAG provide guidelines for how to conduct and record weather, snowpack, and avalanche observations. Other than a few comments about the observed limitation of certain tests, these guidelines deliberately offer little information on how to apply or interpret the observations as they relate to an avalanche problem or forecast. This knowledge and proficiency is gained through other means, including research articles, professional avalanche training, and on the job training and mentorship.

Of course there isn’t any single test that will reveal exactly what you need to know about snow. Yet every decade or so it seems that guides and forecasters have a new favourite “go to” decision making aid they default to when investigating the current avalanche problem. First it was the Rutschblock test (RB), then the compression test (CT)—or the other way around depending on your region—and now it’s the extended column test (ECT). In a helpful 2010 article “Which Obs for Which Avalanche Type?” Bruce Jamieson and others conducted a field study that did an excellent job of directing attention to those observations that best identify each avalanche concern. The combination of determining the avalanche problem prior to departure (Atkins 2004) and having a good idea about which field observations and tests will best identify the problem is a good start when choosing the right tool for the right problem.

The AIARE Avalanches and Observations Reference included below (published in the AIARE Field Book and instructor materials) was inspired by the aforementioned article and is a useful field reference to help learners target those concerns described in the daily avalanche advisory.

Fig. 2: From AIARE instructor materials and field book, 2012

MANAGING FALSE STABLE AND FALSE UNSTABLE RESULTS
Doug Chabot, forecaster at the Gallatin National Forest Avalanche Center, brings up a good point in a recent blog post: “Snowpit tests are used to show instability, not stability. Never stability. Snow pits (and snowpack tests) do not give the green light to ski; they just give us the red light to not ski. An unstable test result is always critical information. A stable test result does not mean the snow is stable a hundred feet away.”

Chabot’s advice points to the quandary many backcountry recreationists face when analyzing snowpack factors: a test result illustrating unstable snow urges cautious risk reduction, but what does a “no result” mean? Yet estimating where the snow is strong and where the snow is weak is an important skill—particularly for guides committing clients to terrain. Determining stability or the “likelihood that avalanches will not occur” involves a detailed process of gathering evidence, drawing a big picture perspective and not leaping to conclusions from a single observation or test result.

• Knowing the sites that information is coming from, having a systematic or “toolbox approach” to clue gathering (see Fig. 3), and observing the terrain and trends over time are all crucial links in the chain of gathering information and applying it to a hazard analysis. And knowing to what degree those links are missing and then defining the information deficit (whether the uncertainty is weak layer location and distribution, character and sensitivity, or slab characteristic and estimation of destructive potential) is all part of guide and forecaster daily discussion. In addition to the strength, weight and verification checklist provided in Fig. 1, the following points may help when interpreting the day’s investigations.
• A seasonal perspective of where the terrain has historically formed stronger and weaker snow is important. Basal facet development tends to repeat itself in seasonal trends. While near-surface persistent weak layers tend to have a broader distribution, sun or wind effect can result in feature scale variability in weak layer character. For example, DF (decomposed and fragmented snow grain) layers can be unstable locally but may not be problematic on a drainage scale. Expect a higher incident of false stable test results when observing locally unstable layers like DFs, graupel or sun crust/DF interfaces.
  
• One of the best tools for determining the nature of snowpack variability is to simply observe and memorize how the current snow surface or near surface condition changes over the terrain. Knowing the extent of surface hoar, facet, crust, or graupel formation and the distribution of storm snow and wind redistribution of snow helps to form a baseline when later estimating snowpack strength. Imagine yourself a heli ski guide with the opportunity to travel over 10s or 100s of kilometres of terrain on any given day. Using your eyes, your skis, and a few quick penetration and hand tests provides insight into what to expect when the snow surface becomes a buried weak layer. “Quick tests,” while not subject to the same formal research as standard tests, still provide helpful information to an approximate depth of 45cm (Schweizer and Jamieson 2010).
  
• A checklist sum of snowpack structural properties (a.k.a. “yellow flags” or the Snowprofile Checklist (Jamieson and Schweizer 2005)) provide valuable clues about which layer interface is most likely to result in a localized failure/fracture. However, as the checklist sum has a tendency to overestimate instability (false unstable=false alarm), further tests are conducted to determine propensity for propagation (Winkler and Schweitzer 2008). The combination of CTs (with fracture character) and the profile checklist sums provide an excellent tool to determine which layer is worth testing prior to a propagation saw test (PST) or ECT propagation propensity test.
  
• The large column snowpack tests that employ taps or jumps to apply a load to the slab (e.g., the ECT and RB) may still indicate a “no result” when a significant weak layer is buried approximately 1m or deeper—and/or when stiffer snowpack layer characteristics (e.g., a crust) reduce the likelihood that surface taps are affecting the deeper weak layer. The cautionary note is that skier triggering of a layer of this depth may still occur from shallower or weaker area (see case history below). In this scenario, one would not use the ECT or RB as the sole observation tool. It may be more prudent to identify the deeper weak layer with a CT or deep tap test (DT) and if a sudden fracture is observed choose to conduct a PST (or choose a shallower location for an ECT) to observe propensity for crack propagation in the layer. The combination of the small column test (which may err on false unstable but identifies fracture character) combined with a large column test (testing for propagation propensity) both reduces the likelihood of a missed observation and provides more information with a verified result. This “toolbox approach” may help interpret a potential “no result” or a false stable result.

The 2010 Schweizer and Jamieson article “Snowpack Tests for Assessing Snow-Slope Instability” provides an updated, excellent perspective directed at a general audience on snowpack test use and limitations. The following summary points have been paraphrased from the article:

• A good test method should predict stable and unstable scenarios equally well.
  
• Column tests are particularly helpful for assessing persistent slab conditions.
  
• Small column tests (CT and DT test) are useful for identifying weak layers and likelihood of initiation but have a tendency to overestimate instability (false unstable) conditions. Observing fracture character improves, to a degree, the interpretation of the test results. These tests are a better indicator of layer character than instability.
  
• Large column tests are better at predicting propensity for fracture propagation than small column tests, particularly when used in combination with other large column tests. Comparative studies suggest that the RB, ECT, and PST have comparable accuracy.
  
• With large column tests, repeated test results in the same location are useful but the tests repeated on similar, nearby slopes add value.
  
• Each test has a margin of error. Even with very experienced observers an error rate of 5-10% is to be expected. Site selection and interpretation require experience.
  

A TOOLBOX APPROACH TO INVESTIGATING LAYERS OF CONCERN

The Toolbox Approach in Fig. 3 may help students avoid the relatively high number of false predictions that occur due to a combination of several factors, such as extrapolation from single tests and high snowpack variability. The diagram supports a dialogue encouraging students to take a step-by-step approach and observe clues from a combination of tests and observation methods. For example, the combination of both the “yellow flags” checklist sums and fracture character in compression tests provide clues, not confirmation about whether or not a “propagation likely” scenario exists, which is then verified with a large column test that is suitable for testing within limitations posed by the particular snowpack structural properties. Understanding test limitations, matching the test to observed structural properties and verifying observations with complementary tests may improve the ability to interpret the test results and reduce false stable or false unstable predictions. I created this diagram and instructional method five years ago and have included it on the L2M3 and American professional level courses.

FIG. 3 The toolbox approach, ver. 6, Zacharias, 2015 

A CAUTIONARY TALE
Backcountry winter travelers are always encouraged to make weather and snowpack observations in the field, and when possible identify on a drainage and slope scale what the public avalanche advisory describes for the region or range. For the most part, this is an effective risk management strategy. However, there have been a number of close calls, incidents and avalanche accidents with backcountry users increase their risk by not managing exposure when gathering information or misinterpreting the observations they collect. In December 2007, a fatal avalanche accident occurred on Tent Ridge in Kananaskis Country when two backcountry skiers were killed conducting a snow profile in the start zone of an avalanche path. Older examples of riders conducting tests on or very near the slope and being subsequently killed include Wawa Bowl, AB, and Mt. Neptune, BC in 1984, Thunder River, BC in 1987, and White Creek, BC in 1993. More recent incidents include Ningunsaw Pass, BC in 1999 and in Twin Lakes, CO in 2014, where a group of seven dug a profile and conducted eight CTs on a slope before choosing to ski it (see CAIC Incident Report for more information).

There are also several examples of “close calls” where test results gathered and extrapolated to chosen terrain illustrated one problem but not the primary concern. A recent example occurred in December 2013 in Hope Creek, BC involving two backcountry skiers. This is an unfortunate example where a combination of well-intentioned observations formulated a confirmation bias and decision making trap. The rider’s observations prior to descending the slope included three existing ski tracks on the slope, 15cm recent snow, light winds, -3°C and no recent avalanches. The group conducted several tests with the following results: CTM16 (SC), ECTP 23, and “numerous ski cuts in the start zone,” all revealing a significant surface hoar layer (size 7-10mm) 40cm deep but nothing deeper. A DT also revealed no results on deeper layers. The group decided that the surface hoar layer was manageable and to ski the slope one at a time. Rider 1 skied the slope with no problems and stopped 400m below, adjacent to the path trim line. Unfortunately, Rider 2 triggered the slope after landing an air low down in the start zone. The resulting D3 avalanche fractured 100m wide on basal facets 80-120cm deep and well below the surface hoar layer. The fast moving avalanche debris caught Rider 1 on the path’s edge before he could scramble to safety. Both involved were carried approximately 700m downslope. Both were buried and badly injured but were able to self extricate, call for help, and were successfully rescued
(Editor’s Note: read a first-hand account of this avalanche by Billy Neilson in The Avalanche Journal Volume 106).

Those involved generously provided the CAA occurrence report with snowpack observations and insight into what gave them confidence to venture onto this particular slope. This event is a helpful wake-up call as we can all place ourselves in their decision making shoes. In hindsight, it is revealing to examine the Kicking Horse Mountain Resort local forecaster’s public video statement issued on Vimeo on December 13, 2013 for the nearby backcountry terrain. The forecaster warned there is a “basal weakness at the bottom of the snowpack that is still reactive,” and “skier triggered size 3 avalanches have occurred,” and “avalanches had triggered larger slopes sympathetically,” and that “now is the time to be very mindful of slope history.” He went on to emphasize “without that degree of confidence that an avalanche has happened [on your slope of interest], you are really rolling the dice hopping onto big terrain.” This incident—though occurring over one week after the video statement—illustrates that when it comes to managing deeper persistent slabs, the careful observations and good well-learned techniques of the backcountry travelers were not sufficient to protect them from the lingering hazard. It also reveals the big-picture perspective of the forecaster, who clearly warned of the more serious basal concern.

Experience with this type of problem, experience monitoring unstable snow in a shallower snow climate, experience matching specific tests to specific problems, and experience managing false stable results and prioritizing the key concerns are all factors that may have given the experienced forecaster a different perspective than the backcountry riders. In this case, the knowledge of how the snowpack lay over the terrain held more weight than even a series of test results, all of which drew attention to a secondary problem that, while significant, was less so than what lurked below.
The bottom line is snowpack tests used to predict instability, while valuable when employed appropriately, are not foolproof. As Schweizer and Jamieson state obviously and importantly in the aforementioned 2010 article, “decisions about traveling in terrain should not be based solely on stability (snowpack) test results.”

REFERENCES
American Avalanche Association and USDA Forest Service National Avalanche Center. 2010. Snow, Weather and Avalanches: Observation Guidelines for Avalanche Programs in the United States. 2010. Pasoga Springs, CO: AAA. http://www.avalanche.org/research/guidelines/pdf/Introduction.pdf

Atkins, Roger. 2004. “An Avalanche Characterization Checklist for Backcountry Travel Decisions." Proceedings of the 2004 International Snow Science Workshop. Jackson Hole, WY. http://arc.lib.montana.edu/snow-science/objects/issw-2004-462-468.pdf.

Avalanche Canada Incident Report Database. Golden, Hope Creek Draining, Privateer Mountain. December 29, 2013. http://old.avalanche.ca/cac/library/incident-reportdatabase/view.

Campbell, Cam. 2008. “Testing for Initiation and Propagation Propensity.” Canadian Avalanche Association Level 2 Module 3 Lecture.

Canadian Avalanche Association. 2014. Observation Guidelines and Recording Standards for Weather, Snowpack and Avalanches. Revelstoke: CAA. www.avalancheassociation.ca/resource/resmgr/Standards_Docs/OGRS2014web.pdf

Chabot, Doug. “Another viewpoint on a Backcountry Magazine article.” Gallatin National Forest Avalanche Center Blog, November 6, 2015. http://www.mtavalanche.com/blog/another-viewpoint-backcountry-magazine-article

Colorado Avalanche Information Center. Colorado, Star Mountain. February 15, 2015. https://avalanche.state.co.us/caic/acc/acc_report.php?acc_id=526&accfm=inv

Gauthier, Dave, Cameron Ross, and Bruce Jamieson. 2008. “How To: The Propagation Saw Test.” University of Calgary Applied Snow and Avalanche Research. October 2008. http://www.ucalgary.ca/asarc/files/asarc/PstHowTo_Ross_Oct08.pdf.

Jamieson, Bruce. 2009. “Mountain Snowpack and Spatial Variability.” Canadian Avalanche Association Level 2 Module 1 Lecture.

Jamieson, Bruce. 2003. “Risk Management for the Spatial Variable Snowpack.” Avalanche News 66 (Fall 2003): 30-31.

Jamieson, Bruce and Jürg Schweizer. 2005. “Using a Checklist to Assess Manual Snow Profiles.”
Avalanche News 72 (Spring 2005): 57-61.

Jamieson, Bruce and Torsten Geldsetzer. 1996. Avalanche Accidents in Canada Volume 4: 1984-1996. Revelstoke: Canadian Avalanche Association.

Jamieson, Bruce, Jürg Schweizer, Grant Statham and Pascal Haegeli. 2010. “Which Obs for Which Avalanche Type?” Proceedings of the 2010 International Snow Science Workshop. Squaw Valley, CA. http://arc.lib.montana.edu/snowscience/objects/ISSW_O-029.pdf

Klassen, Karl. 2002. American Institute for Avalanche Research and Education Level 2 Student Manual. 2002 Version.

Ross, Cameron, and Bruce Jamieson. 2008. “Comparing Fracture Propagation Tests and Relating Test Results to Snowpack Characteristics.” Proceedings of the 2008 International Snow Science Workshop. Whistler, BC. http://arc.lib.montana.edu/snow-science/objects/P__8177.pdf.

Schweizer, Jürg and J. Bruce Jamieson. 2010. “Snowpack Tests for Assessing Snow-Slope
Instability.” Annals of Glaciology 51(54): 187-194.

Simenhois, Ron and Karl Birkeland. 2007. “An update on the Extended Column Test: New Recording Standards and Additional Data Analyses.” The Avalanche Review 26(2).

Zeleny, Milan. 1987. “‘Management Support Systems: Towards Integrated Knowledge Management.” Human Systems Management 7: 59–70.

“Skiers Died Testing for Avalanche.” The Calgary Herald, December 11, 2007. Accessed December 10, 2015. http://www.canada.com/story.html?id=75d72a3c-c743-4c65-a0c2-a18728813217.

From volume 104, fall 2013

By Troy Leahey

The start zone. Photo by Jim Bay.

This case study details a skier-triggered avalanche that occurred in the backcountry accessed from Revelstoke Mountain Resort (RMR) on February 22, 2013. The party included five young men, all new to Revelstoke. Three members of the party were involved in the avalanche. Two of these were partially buried; the deceased (an RMR staff member) was fully buried despite wearing an airbag. It was a size 2 slab avalanche with an approximately 40cm fracture line, which failed on an early February surface hoar layer.

Analyzing accidents has long been an important part of the CAA ITP program and in other risk  reduction industries. It is easy to be the armchair quarterback after an incident and identify the mistakes people made, but I believe it is also important to identify what was done well in the rescue effort to use as a good learning tool.

My involvement in this accident was on a number of different levels. As a member of Revelstoke Search and Rescue, I assisted Buck Corrigan and Ryan Buhler with the body recovery the day after the accident. I watched and helped interpret a Contour headcam video worn by one of the rescuers during the rescue effort for local members of the RCMP and a representative of the BC Coroners Service. This was a sobering but interesting piece of footage; although the actions of those involved on the scene would be apparent to most readers, the footage required some explanation and interpretation for non-skiing investigators. I interviewed some surviving members of the group for clarification on the location of those involved and their actions for the Coroners Service.

I also led a debrief at RMR for friends and co-workers of the deceased, including the other young men involved in the accident. This debrief was the most challenging public speaking exercise I have ever undertaken. Our company president asked if I could speak about the accident, as staff members and friends in the community had unanswered questions, and answers can help lead to understanding and closure. I wanted to be quite frank about the obvious mistakes made, as they were an opportunity for learning. I also wanted to commend the survivors on their effort and help them recover some confidence and dignity. I focused on the following points in the debrief.

This photo shows the position of the skiers when the avalanche occurred and where they ended up. Their uptrack is in red, the avalanche is outlined in black, and the blue dot is where the victim ended up. Photo by Troy Leahey.

MISTAKES:
• The most obvious mistake was the aggressive terrain choice—the danger rating at alpine and treeline was high. The five males were young, aggressive skiers with limited backcountry experience. This is the demographic we may expect to see on the avalanche fatality list. The deceased had skied in the terrain the day before and felt confident in his decision to lead the rest of the group to that zone. He had spent many days in this area in what had been a mostly stable season to that point. It was also the first major surface hoar cycle we had experienced in the season, and this type of avalanche failure may not have been familiar to a young German in Canada for his first winter. The CAC’s avalanche forecast was bang on—as it usually is—but youth, overconfidence and a desire to ski steep powder caused this glaring information to be ignored.

• Poor group management. The first three skiers on the uptrack were all involved in the avalanche; they were obviously not well spaced out enough and were all engulfed by the slab. Luckily the last two in the group were slower and not affected by the slab failure, and were able to execute a fairly quick rescue. Complacency on uptracks is a common problem for less experienced backcountry travellers. The group of five had been split into the first group of three up front and the slower pair at the back, which leads to a lack of communication and no consensus in the go or no-go decision. The most educated member of the group had been a student of mine on a CAA Avalanche Operations Level 1 course the previous year in Whistler. I spent a lot of time speaking with him about their decisions that day. He admitted to having reservations about the decisions being made, but did not speak up and deferred to the deceased as the leader, since he was most familiar with the terrain.

• Improper use of an avalanche balloon pack. Wear the crotch strap if you are wearing an airbag. The deceased was near the surface with his airbag inflated and clearly visible from 100m away. He had not attached the crotch strap of his airbag. As the overburden of the slab he triggered from mid-slope overran his position in the toe of the debris, the airbag was lifted away from his back and above his head. This caused two serious problems. As the balloons and pack were pushed forward and downhill it lifted the pack, causing the chest strap to catch on his chin and impede his airway. Secondly, the buoyant airbag also pulled the victim’s arms above his head, restricting movement and the ability to use hands to clear his own airway. The Contour video showed quite clearly the victim’s lifeless arms well above his head. The space between the balloon pack and the victim’s back was approximately 40-50cm.

The avalanche path where the victim was caught is on the right. Photo by Jim Bay.

WHAT THE RESCUERS DID WELL:

• The two not involved took a safe route to the toe of the debris and did not expose themselves to any additional hazard. They quickly and efficiently went into rescue mode when they saw the airbag on the surface, and began the excavation by first removing the pack and digging to the head to clear the airway.

• The two partial burials ended up mid-path and were able to self-rescue and do a transceiver search of the slide path down to the victim.

• Group members performed good first aid on the victim. Once they uncovered his head, they immediately cleared an ice chunk from his mouth and pulled him out to a prone position where they started CPR. Considering the environment, they performed excellent CPR with quality air movement as exhibited by the face of the victim in the video.

• The survivor with the most training took control of the rescue effort. He dispatched one of the members of the party to start moving back to the ski area boundary to report the accident as there was no cellular reception on the accident scene. This individual really led the first aid efforts as well.

• After at least a half hour of CPR, they made the decision to try to move the body with an improvised toboggan. They did not get very far as the conditions were very deep, but were able to move the body to a safe location out of the avalanche path. They then made the very difficult decision to leave the body and return to the ski area, as the weather conditions were deteriorating quickly. They left the body in a seated position under a tree with the inflated airbag and flagging tape arranged to mark its position, making our recovery very easy the next morning.

This was an unfortunate accident involving a group of nice young people from around the world enjoying the mountains in Revelstoke. There is nothing ground breaking about this accident other than the question of whether the airbag crotch strap could have made a difference. So why did I write this for The Avalanche Journal on a 30° July day when I’d rather be fishing? On a personal level, it brings back a bunch of vivid images and unpleasant emotions that make me sad. However, on the big-picture level this is an opportunity for others to learn and avoid mistakes in the future. A case study is really a story; this story may be repeated in Whistler, Banff or beyond. Hopefully the mistakes made and the triumphs that occurred in this accident will resonate and help others make better decisions in the mountains. That makes me happy.

Have a fun, safe winter.