Backcountry Recipe Book

Terrain + Snowpack + Weather + Human = Uncertainty

NOTE: I was originally going to write a post about map reading, but I've been too busy with the non-digital part of my life, which includes boring tasks such as family chores, earning a living, and somehow finding time to play in the snow. In any event, I haven't been able to wrap my head around the topic of map reading just yet. This post discusses decisions and does not cover other important elements of the sport, such as trip planning and travel technique. { This post was revised on November 18th, 2010. }

Introduction
I've written some complicated posts about backcountry avalanche forecasting, snowpack instability, terrain, snowpack, and weather. Regardless of complexity, the essential question remains: how do you leverage all these observation techniques to produce a backcountry avalanche forecast that enables you to make sound decisions?

Learning which observations have priority and correctly interpreting observations is required for successful backcountry avalanche forecasting. Priority of observations ( relevance ) is usually determined by the size of the forecast area, but interpretation of relevant observations ( the relationship, or link, between the observation and snowpack instability ) is much more subjective and sometimes quite indirect.

Avalanche experts recommend integrating observations whenever possible instead of relying on disconnected observations. Yet the process of integrating observations is complex and somewhat mysterious. In this discussion, we're going to examine the linkages between types of observations, and develop a list of simple keywords that help frame these complicated problems. NOTE: The process of integrating observations does not apply to the golden rule: alternate plans are required if you observe absolute signs of instability such as whumpfing, cracking in the snow surface, or recent avalanches.

Let's discuss a recipe for decisions, and along the way, I'll restructure the typical decision-making process to explicitly revolve around the balance between awareness and uncertainty.

A Recipe For Decisions
I wrote an article about avalanche education for the December 2009 issue of The Avalanche Review, and in the article I discuss the importance of teaching students how to make decisions that blend uncertainty, safety, and fun. This structure for decisions is compatible with realistic human behaviour, the importance of which is discussed in The Avalanche Handbook.

Recently, there have been a number of online discussions about decision-making, some of which have included lively conversations about backcountry outings during which avalanches were triggered by members of the party. From these discussions it has become increasingly clear to me that the lack of a general, universal recipe for safe decisions is a primary source of confusion for recreational backcountry skiers. Rather than focusing on checklists or graphs, I am going to write about a simple approach to decision-making that integrates critical human elements into the mix.

From my post on TetonGravityResearch's Slide Zone Forum:

"Your question(s) underline a very common, and often unacknowleged, source of concern for anyone in the backcountry: Even after observing the terrain, snowpack, and weather, how do I manage the remaining uncertainty?"

Recreational backcountry skiers are taught, whether by other skiers or in a classroom setting, to use multiple observations before deciding whether or not to travel on a particular slope. Observations rarely provide clear and precise answers because the winter snowpack is conditionally unstable most of the time.
The standard recipe for decisions is as follows:

Terrain + Snowpack + Weather + Human = Decision

From my own experiences, including observations of recreational backcountry skiers, both online and in the field, I think it's fair to say that many skiers have difficulty using this recipe to connect their observations with their decisions. The difficulty in connecting observations to decisions revolves around what recreational backcountry skiers expect to gain from their observations. If I can believe what I've seen in avalanche safety training courses, and what I've seen in the field, the expectations of many recreational backcountry skiers are as follows:

Terrain + Snowpack + Weather + Human = Answers

Anyone with enough knowledge and experience knows that the observations rarely provide answers because the prevailing state of the winter snowpack is conditional instability. This basically means mostly stable with a chance of avalanches. Therefore, the recipe that ends with answers doesn't really exist, unless you are willing to accept answers that are very vague and seemingly unrelated to the situation at-hand. Most people won't find these "answers" very useful if they are expecting something definitive.

If we dig deep into both the scientific and human aspects of the problem, including a lengthy foray into stacks of published research, a far more intuitive recipe for decisions emerges:

Terrain + Snowpack + Weather + Human = Uncertainty

The key here is learning how to think about observations: observations are undertaken for the sole purpose of minimising uncertainty. Observations are not made for the purpose of finding definitive answers. The spatial and temporal variability of the winter snowpack ensure that some degree of uncertainty is always present. Therefore, in many situations, the best we can do is acquire information that minimises uncertainty before making the decision to travel on a particular slope. Observations rarely make the uncertainty go away entirely, and when they do, it is only when signs of absolute instability, such as cracking and whumpfing, are observed. In those situations, you can say the snow is absolutely unstable, but everything else is gray.

In many avalanche safety training courses, the element of uncertainty is often wrapped up in vague or complicated language about risk management or decision-making, yet such language is more suitable for insurance companies than backcountry skiers. The revised recipe presents a human-compatible method for making decisions based on uncertainty, and this method actually makes sense to most people.

Here's why:

As I said in my article for The Avalanche Review, during the process of purchasing an automobile, you don't acquire information to make a decision, you acquire information to reduce your uncertainty before making a decision. At least, this is how it works for most people. Rather than fighting against the inherently confusing uncertainty of observations, recreational backcountry skiers should be taught to use this uncertainty to their advantage.

Working With Uncertainty
It's safe to say that the amount of uncertainty present in any situation is highly related to the knowledge, skill, and experience of the observer, and it's also safe to say that these variables are influenced by the complexity of current conditions. According to research published by Laura Adams, the correct method for addressing this uncertainty is as follows:

Acknowledge + Identify + Reduce = Managing Uncertainty

The first step is to consciously acknowledge uncertainty. I find it helps to say it aloud: "What is my uncertainty?" The next step involves identifying the sources of uncertainty and deciding whether or not reviewing existing information or seeking additional information will reduce uncertainty.

Many times, it is not possible to reduce uncertainty by seeking out additional information, and this is exactly when many serious mistakes are made in the backcountry. A highly uncertain mind is very susceptible to unscientific speculation, dangerous biases, made up facts, and other forms of outright stupidity such as "explaining away the uncertainty" or "ignoring the uncertainty" altogether. With this in mind, it certainly seems reasonable to wonder if many grave but common errors, such as trying to "outsmart" the snowpack, are simply poorly managed reactions to high uncertainty.

Even with meticulous efforts to maintain awareness through careful and objective observations of the terrain, snowpack, weather, and human factors, recreational skiers should take an immediate step back when high uncertainty is present during decision-making. In general, without expert decision making skills, decisions made by recreational backcountry skiers should retain a conservative character when uncertainty is high.

Conclusion
The character of the correct decision can be easily uncovered by using observations to determine the level of uncertainty prior to decision-making. Failing to proactively manage uncertainty, including failing to recognise that uncertainty is always present, is a primary source of avalanche involvement and accidents in recreational backcountry ski outings.

Caveat
While important, awareness and uncertainty are just two parts of the multi-faceted discipline of backcountry avalanche forecasting. Backcountry avalanche forecasting has other elements and relying solely on awareness and uncertainty will eventually lead to mistakes.

A minimalist framework for backcountry avalanche forecasting is discussed here.

Weather Observations: Trend Analysis

( 1 + x ) × ( 1 + y )—Ms. Steffens

NOTE: Backcountry avalanche forecasting is composed of four interconnected elements: goal, people, awareness, and uncertainty. Four types of observations, human, terrain, snowpack, and weather are used in backcountry avalanche forecasting. { Edited on March 7th, 2010. }

Introduction
Backcountry avalanche forecasting relies on observations of the terrain, snowpack, and weather inside a single valley or backcountry ski run. Observations of terrain, snowpack, and weather are made to increase awareness and manage uncertainty.

Weather Observations: The Direction Of Instability
The primary difficulty with weather observations is the quantity of data, wide area of influence, and the uncertain relationship between observations and instability. Despite these complexities, weather observations focus on discerning the presence of, and effects of, three key factors that create and influence snowpack instability. These factors are listed below in order of importance relative to snowpack instability:

• Loading
• Warming
• Cooling

Warming, cooling, and loading are trends that can increase or decrease snowpack instability depending on the current structure of the snowpack and the magnitude, rate, and duration of the trend across space and time. Individual variables such as cloud cover, slope aspect, local terrain, weather patterns, and radiation balance contribute to these factors, but ultimately warming, cooling, and loading are the practical concerns.

Warming, cooling, and loading create new snowpack instabilities while simultaneously altering the current snowpack in ways that can increase or decrease instability. A primary source of confusion is the circular nature of trends related to these factors, especially the relationship between these trends and snow metamorphism. Temperature changes are a good example. A warming trend can create instability by melting the snow and decreasing its hardness. However, when subject to a gentler warming trend, the direction of instability will eventually reverse itself because warm temperatures promote settlement and strength gains throughout the snowpack in general. Trends for cooling and loading also create circular variations in the direction of instability.

The direction of instability depends on the magnitude, rate, and duration of the trend relative to the current state of the snowpack. In simple terms, it is important to understand:

• Magnitude. How much cooling, warming, or loading is expected?
• Rate. How fast will the cooling, warming, or loading occur?
• Duration. How long will the cooling, warming, or loading last?

You are probably aware that avalanche formation is much more likely at some times than others. Trends and their magnitude, rate, and duration are significant sources of uncertainty with respect to the formation of avalanches across space and time. These trends are responsible for the development of both long-term and short-term instability.

Table 1.1. Partial list of key weather observations mapped relative to instability and stability. Do you notice the potential for each factor to increase and decrease instability depending on the magnitude, rate, and duration? The circular nature of these trends, and their effects on both new snow and the existing snowpack, along with times when more than one trend is active ( cooling + loading ), are strong sources of confusion and uncertainty in backcountry avalanche forecasting. Make a list of your own and experiment.

Trend	Magnitude	Rate	Duration	Instability
Loading	Medium	Fast	2 Hours	+
Loading	Large	Slow	22 Hours	-
Warming	Large	Fast	18 Hours	+
Warming	Small	Slow	14 Days	-
Cooling	Large	Slow	12 Days	+
Cooling	Medium	Fast	4 Hours	-

Table 1.2. Contributors to warming, cooling, and loading.

Loading	Warming	Cooling
Precipitation	Air Temperature	Air Temperature
Wind	Sunlight	Shade
Skiers	Clouds	Clear Skies

The current state of the snowpack, and magnitude, rate, and duration of current trends, are extremely relevant to backcountry avalanche forecasting. Are you preparing to descend a steep slope covered in fresh snow even though temperatures have been rising quickly for the past two hours?

Snowpack Observations: The Search For Instability

An avalanche is defined most simply, as a block of snow cut out by fractures—McClung/Schaerer

NOTE: Backcountry avalanche forecasting is composed of four interconnected elements: goal, people, awareness, and uncertainty. Four types of observations, human, terrain, snowpack, and weather are used in backcountry avalanche forecasting.

In the prior article, I discussed terrain observations, and six universal qualities that indicate exposure. Now it's time to discuss snowpack observations. The relationship between terrain and snowpack is complex, but this article should provide useful context on how to think about the nature of their relationship. As with terrain observations, this article presents non-technical methods that are compatible with human behaviour.

NOTE: This discussion of snowpack observations is focused on slab avalanches. Most of this discussion departs from the pure shear fracture model of avalanche formation first proposed by McClung in the late 1970's. Recent avalanche research has revealed limitations in applying the pure shear fracture model to many types of avalanches.

Introduction
The main difficulty with snowpack observations is not spatial variability, nor the interpretation of results—although experience in these matters is valuable. The main difficulty with snowpack observations is learning the right way to think about these observations. Snowpack observations can provide direct information about instability, but only if you understand how slab avalanches form, and only if you know how to think about snowpack observations. Thankfully, recent research, along with several helpful analogies, provides some answers.

Thinking About The Snowpack
The seasonal snowpack is a multi-layer composite material formed by the weather. The state of the snowpack, including the condition of its surface and the structure of its interior, are also determined by the weather. Therefore, the seasonal snowpack is a multi-layer composite material, the quality of which is controlled by the weather. Different layers have different strengths, and the strength of an individual layer varies from place to place, and with the passage of time. The region where these layers touch each other is referred to as the interface between the layers, and as with the layers themselves, the strength of these interfaces varies from place to place, and with the passage of time. So, in total, the strength and structure of the snowpack is extremely complicated, right?

Believing that the snowpack is complex does not contribute to the goal of backcountry avalanche forecasting. Therefore, rather than believing that the strength of these layers and interfaces is complicated, it's much more helpful to focus on the very simple truth: extensive variations in the snowpack create a lot of uncertainty. If you never learn anything about the snowpack, and never dig a single hole in the snow, remember that the snowpack is a source of significant uncertainty.

Snowpack observations increase your awareness of these variations and their strengths, but residual uncertainty always remains. This residual uncertainty is part of the reason why snowpack observations are often perceived as vague, when in fact, the often vague nature of snowpack test results simply reflects the fact that the structure and strength of the layers and interfaces are a source of significant uncertainty. This uncertainty is perfectly normal, and snowpack observations can help greatly, especially when you decide to travel in big terrain.

Why then, with the apparent widespread variation of layer and interface strength, are skier-triggered avalanches so rare? Well, the seasonal snowpack is stable most of the time because it is a heavy, multi-layer laminate material. While snow is the weakest natural material, and while snow is typically found at temperatures close to its melting point, multi-layer composite materials are known to exhibit extraordinary strength even when the individual layers are constructed from relatively weak materials. Some of the other physical properties of snow, such as its ability to deform elastically and settle onto a mountain side, along with its ability to bond with neighbouring layers under a variety of conditions, also help explain why skier-triggered avalanches are rare.

But forget about the relative strength of the snowpack for a moment because the strength of the snowpack isn't related to avalanche formation. It's the weak spots that matter.

Flaws
Carbon fibre composites are used to construct aircraft components such as rudders and stabilisers. Cavities are a significant concern during the process of manufacturing carbon fibre composites because hollow cavities provide space for collapsing and cracking. When manufacturing carbon fibre laminates, great care is taken to ensure that cavities do not form in any part of the laminate because tiny flaws can turn into very large problems. For these reasons, carbon fibre laminates are usually manufactured in an absolutely dust-free environment, and highly-controlled procedures are used to prevent formation of cavities in any parts of the laminate. This might not seem relevant to avalanches, but the presence of cavities in the snowpack is just as important.

Avalanche formation is caused by a type of mechanical failure referred to as delamination. This means that the layers of the snowpack become detached from one another, and on a steep slope, gravity will pull the detached layer ( the slab ) downhill. It's helpful to think of this process as similar to paint flaking. Perhaps there is a small patch of dust that will cause a poor bond between the final coat and the primer. Later, as the paint dries, the outer layer pulls away from the inner layer ( delamination ) and cracks form at the margins ( detachment ). Eventually a paint chip falls onto the floor ( avalanche ).

Recent research by European and North American avalanche experts proves that buried surface hoar and facets indicate areas where the snowpack is effectively hollow. You can think of these regions as very large, thin cavities in the laminate structure of the snowpack. Weaknesses in new snow, such as low density sections of the new snow, operate on the exact same principle: low density snow, regardless of the form it takes, means that a portion of the snowpack is, essentially, hollow. As discussed above, the structural integrity of composite materials depends on the strength of the individual layers and the strength of the contact interfaces between the layers. Hollow regions indicate that, essentially, there is no interface between the layers, or any interface that does exist is very, very weak. Large hollow regions in any interface or in any part of any layer indicate the presence of a potentially serious flaw in the laminate structure of the snowpack.

Consider a layer of buried surface hoar, or a layer of facets, above a layer of hard, well-settled snow, and below a layer of soft, but well-settled new snow. It seems convenient to focus on the intrinsic weakness of the surface hoar crystals, and their well-known persistence in the snowpack, but I'm afraid that focusing on the crystals themselves is a bit of a red herring. Surface hoar and faceted crystals are dangerous not only because of their intrinsic weakness, but also because their presence indicates that some degree of mostly empty space is present in the snowpack. Such crystals are easy to crush, and the presence of empty space overlayed by a cohesive slab provides a means by which the crushing can spread on its own.

The inherent uncertainty in layer and interface structure and strength is one primary source of confusion when interpreting snowpack observations. But it's much easier to manage this uncertainty once you realise that significant uncertainty is normal and can be addressed by seeking additional information, making conservative choices, or simply by teaching yourself the difference between calculated risks and gambling. Gambling is a perfectly valid choice if you are prepared to accept significant losses, or if your friends and family are willing to pick up the tab.

Thinking About Snowpack Observations
After uncertainty, the second primary source of confusion is not knowing how to think about snowpack observations.

Since the seasonal snowpack is a material that is manufactured by the weather, quality control is a useful way to think about snowpack observations. Quality control is concerned with determining whether or not flaws are present in any material, including the extent of any such flaws and the potential outcomes and consequences.

Snowpack observations are simply a means by which you can perform quality control for snowpack by gathering information about the structure and strength of layers and interfaces. Since the structure and strength of layers and interfaces is highly related to avalanche formation, these observations can be very useful. In terms of snowpack observations for backcountry avalanche forecasting, slab avalanches are much more likely with some layer and interface configurations than with others. ( Learning about these configurations is one reason that you should take an avalanche class. )

Man-made composite materials, such as carbon fibre laminates used for aircraft construction are extremely strong because of the consistency of the layered construction, the strength of the individual layers, and the high-quality contact interfaces between each layer. Of course, manufacturing defects are much less likely in a highly-controlled manufacturing environment, but are still a source of concern. Manufacturing defects in the seasonal snowpack are a source of concern because such defects make avalanche formation possible. Weather is the source of the snowpack, and therefore, weather is the source of most manufacturing defects. The chaotic interaction between terrain and weather makes it very difficult to assess the state of the snowpack without close observations.

The difficulty in determining the location and extent of defects in the seasonal snowpack, including small changes from the continual influence of weather, is the biggest challenge in backcountry avalanche forecasting. So, the problems with snowpack quality control essentially boil down to a question of scale and consistency. It is definitely possible to thoroughly search a 4×4 metre square of carbon fibre laminate for the presence of flaws, and the process of quality control is made easier because of the consistency ensured by highly-controlled manufacturing conditions. Given the inconsistent and uncontrolled conditions during snowpack manufacturing, along with limitations in time and manpower, it is impossible to search an entire valley for flaws. That's why it's important to perform snowpack tests in areas where you are likely to find flaws.

To develop a useful mental model for evaluating snowpack observations, it is helpful to stop thinking about what an avalanche looks like on its way downhill, and think instead about why slab avalanches form.

Delamination Theory, Part I: Crushing & Collapsing
NOTE: Some of this material is derived from old and new research on the shear fracture model of avalanche formation proposed by McClung, and recent work involving anti-cracks. There is an element of theory to most models of avalanche formation.

Avalanche formation requires delamination, and crushing is one mechanism by which delamination occurs in layered composite materials. Let's examine some very simple snow profiles and determine whether or not delamination is possible.

Figure 1.1. Snow profiles for two different regions of the same slope. White pixels are air. Note the individual layers and interfaces in each image. The implication is fairly clear: the surface hoar crystals form a hollow cavity in the snowpack on the right, and the interface between the two layers is almost non-existent. Pretend for a moment that you are a "quality control engineer" out for a day of ski touring. Which product passes your quality control procedures and why? Which product does not pass your quality control procedures and why?

Figure 1.2. The snowpack laminate with simple crushing in progress. In this example, the layer on top is hard enough to provide a lot of energy for crushing as it falls, which means that the crushing is likely to spread on its own. Q: What happens if this crushing process spreads throughout the snowpack? A: delamination. Q: What happens if widespread delamination occurs on a steep slope? A: The delaminated portion of the snowpack detaches from its surroundings and moves downhill.

Figure 1.3. Old snow is dark gray, with layered storm snow above. The snowpack laminate with simple crushing in progress. In this example, the new snow layer on top is not hard enough to provide a lot of energy for crushing, but the layer immediately below the new snow is so hollow that the energy requirement is low. In this example, the crushing ends when it reaches the dense, old snow layer below. This is an example of a classic soft-slab avalanche in new snow. The most dangerous weakness is suspended in the middle of the new snow, but the avalanche appears to form on the interface of the old/new snow only because all the new, upper layers are swept out during the initial collapse. In reality, this avalanche started in the new snow, and the new snow could collapse no further than the dense old snow, which then served as the bed for the avalanche. New snow is often full of widespread weaknesses that require very little energy for avalanche formation. You would almost certainly hear whumpfing and cracking if you traveled on this snow.

The Avalanche Handbook helpfully points out that the very common nearly perpendicular orientation between the slab and the bed surface indicates a friction free relationship between the slab and the bed surface immediately prior to the avalanche. This is expected, because if significant friction existed between the slab and the bed surface after the collapse of the weak layer, then you would have a failed avalanche. Failed avalanches can occur and are usually indicated by a loud whumph. Most people correctly recognise this sound as an absolute indicator of high snowpack instability.

Delamination Theory, Part II: Shearing & Collapsing
Delamination can occur whenever there are hollow regions in the snowpack, and failures tend to spread when the snowpack layer above the hollow region is dense enough to generate energy as it falls onto the layer below. The potential for failure in the previous example was very obvious. However, recent avalanche research shows that you only need a hollow space approximately 1mm thick to provide 10× more energy than is actually required for the crushing process to sustain itself. In these cases, crushing may initiate from strong shear forces that crack the inter-crystalline bonds in the interface ( or at the base of the slab itself ) and shift the slab just enough to crush the ice crystals and start a self-sustaining collapse.

Figure 1.4. Snow profiles for two different regions of the same slope. White pixels are air. Note the individual snowpack layers and interfaces in each image. The flaw in this example could be much more difficult to find. In fact, it may be almost impossible to find this flaw with the naked eye. You may have to use a magnifying glass and examine the snowpack very carefully.

Figure 1.5. You can also initiate crushing in very fine, extremely thin layers ( such as facets or a crust ) if you apply enough energy to cause a shearing fracture in part of the weak interface or inside the weak layer itself. This initial shear fracture causes local collapse and crushing of the thin, weak snowpack layer. This collapse spreads through the combined action of a propagating shear fracture, with some collapsing as shown above. It's easy to visualise the results of collapsing, whether or not the collapse is initiated primarily by simple crushing or by the more complicated process of shearing. Either way, the result is the same: delamination, detachment, avalanche.

Detachment
Detachment occurs during and after delamination. Once delaminated, the layer of snow is no longer attached to the layer of snow below. Gravity is always in effect, so immediately following delamination, the layer of snow begins to pull on its margins and visible cracks form at the edge of the delaminated region. Now the layer of snow is completely detached from the snowpack and it begins to move downslope. In terms of human perception, this process is instantaneous, which is understandable since research has proved that disturbances can travel at speeds approaching 20 metres per second.

Quality Control
Interpreting snowpack observations is a primary source of confusion for many people because of high uncertainty related to the strengths and weaknesses of layers and interfaces, and because many people are not taught to approach the problem with the correct frame of mind.

In the backcountry, you serve as quality control. Snowpack observations, such as snow profiles, compression tests, and ski pole tests, are important and useful quality control procedures that help determine whether or not dangerous flaws exist in the snowpack.

In conclusion:

• The seasonal snowpack is a multi-layered composite material manufactured in poorly controlled conditions.
• The length of the manufacturing process is the entire winter.
• Flaws introduced during manufacturing make avalanches possible.
• Variations in the layers and interfaces originate from the chaotic interaction of terrain and weather.
• These variations are a primary and ongoing source of complexity uncertainty.
• This uncertainty is normal, and must be acknowleged and addressed prior to decisions.
• A highly uncertain mind is a breeding ground for speculation, half-truths, denial, and other undesired human factors.
• A highly uncertain mind makes excessively conservative decisions when avalanche danger is actually low.
• You can address uncertainty by seeking additional information, making conservative choices, or by gambling.
• Quality control procedures such as snowpack tests are designed to find and evaluate flaws in materials.

Terrain Observations: Choosing Terrain Appropriate For Conditions

I'm learning to fly, around the clouds ... what goes up, must come down—Tom Petty

NOTE: Backcountry avalanche forecasting is composed of four interconnected elements: goal, people, awareness, and uncertainty. Four types of observations, people, terrain, snowpack, and weather are used in backcountry avalanche forecasting.

CAPSULE: Recreational backcountry skiers are taught to analyse terrain for sources of exposure by using static variables that don't account for the dynamic nature of avalanche phenomena. This article discusses a more general model for analysing terrain that accounts for the dynamic nature of avalanche phenomena with respect to size, phase, and velocity. This model is non-technical and can be effectively applied by most people without any specialised training.

THANKS: To my father for his invaluable input.

Introduction
Why would you ski in one place instead of another place? How do you choose terrain appropriate for conditions?

Recreational backcountry skiers are taught to choose terrain using a simple list of shape parameters such as slope shape, angle, openness and size. This information is then combined with a simple list of terrain traps such as trees, rocks, cliffs, gullies, benches, and depressions. Collectively, we can refer to all these elements as slope shape parameters because ultimately all these elements do refer to the static shape of the terrain.

Unfortunately, the use of static parameters has some significant drawbacks. For example, using a simple list of slope shape parameters can limit perception, and that can lead to dangerous gaps in analysis. Doesn't something very specific come to mind when you hear the word gully or convexity or cliff? Perceptual traps are often associated with rules of thumb, and the relationship between rules of thumb and serious errors is well documented. In the real world, using static slope shape parameters teaches recreational backcountry skiers to find very specific hazards, but it also produces analysis that contains many blank spots. I refer to this phenomenon as pin the hazard on the donkey, or with the more technical term hazard diffusion.

Hazard diffusion occurs because a list of static slope shape parameters does not account for the existence of multiple spatial scales in the relationship between terrain and avalanches. To this point, consider the Strathcona-Tweedsmuir tragedy which occured in the Connaught Valley drainage of Glacier National Park, British Columbia in February 2003. For an avalanche of sufficient size and velocity, the Connaught Valley is a giant terrain trap. If you are willing to indulge in some semantics, then we can say that for a large, fast-moving avalanche, the term Connaught Gully would be a much more appropriate description.

The heart of the problem is that determining the degree of exposure for a given section of terrain depends largely in part on the size, phase, and velocity of an avalanche. Since avalanches occur at a variety of spatial scales, and since terrain exists at a variety of spatial scales, analysis of exposure must account for a variety of spatial scales. This type of analysis requires a more general set of parameters that integrate the spatial and temporal elements of avalanching with multiple scales of terrain. Such integration allows recreationists to very effectively analyse exposure across multiple spatial scales of terrain for a variety of important aspects of avalanche phenomena.

In The Beginning
You might be wondering how this model arose and whether or not it's backed up by any hard evidence? It's a good question with a very complicated answer, but I'll try to be as concise as possible. For the past couple of years I've been working on developing computer-based tools to analyse terrain for exposure to avalanches. It's rough business, especially since computers are mind-numbingly unaware. When a human looks at a digital elevation model, all the terrain features are staggeringly obvious. Unfortunately, a computer sees nothing but a list of elevation values. To get an idea of the problem, imagine if you had to perform route selection from a grid of elevation values. It's quite literally like trying to ski with your eyes closed.

To get around these problems, you can develop algorithms that the computer can use to perform analysis on the elevation values. For example, you can tell the computer about the relationships between the values, and then the computer can use those relationships to reconstruct data such as slope angles. This is all very simple stuff. But let's take things a step further and imagine that you want the computer to identify an avalanche starting zone, or a runout zone linked to multiple avalanche paths. Modern computers are incredibly powerful, but they cannot easily be programmed to solve certain types of problems. This is doubly true when you are faced with real world constraints such as time and money. After a few months of dead ends, I began to realise the depth of the problem and the futility of approaching it head on.

I found the first part of the solution in an old document that discussed Peter Schaerer's work on avalanche terrain along the Trans-Canada highway. Peter Schaerer discusses surface area as an important attribute of an avalanche starting zone, and at that very moment I became intensely curious. Could surface area be used as a statistical signal of avalanche terrain? Needless to say, I returned immediately to my computer and began to calculate surface area for different sections of terrain. The values were startling. It turns out that surface area is a very useful statistical measure of exposure inherent to any section of terrain. Eventually, I developed other geostatistics that made the original problem very tractable. For this reason, I feel comfortable saying that this model is backed up by hard data, and in fact this model is currently being used successfully in the real world.

In the avalanche community, there is a spectrum of complexity, from complex mathematical models to textual hazard communication tools. Regardless, everyone agrees that simplicity is an extremely effective strategic-tactical approach to education and communication. The value of simplicity far exceeds the scope of this article, but it's safe to say that simplicity is an effective technique because people cannot absorb material they do not understand. In the words of an esteemed technical writer who is a friend of mine, it's a lot of work, making things simple.

When Models Collide
I can't find anyone who really knows where the list of shape parameters arose, but it seems likely that it coalesced over time from the collective wisdom of mountain folks. During my time in the mountains, I have observed a very interesting phenomenon with respect to terrain selection. The list of shape parameters provided to most recreationists is extremely useful, but most don't seem to realise that it's just a partial list. To this point, the Avalanche Handbook specifically states that it's important to consider combinations of features in addition to individual features. Yet there is a lack of simple tools that people can use to accomplish this type of multi-scale, multi-feature analysis.

Finally, it's incredibly important to note that this model is not designed to help people outsmart terrain, which is a form of abuse frequently undertaken with travel technique. This model is designed help recreational backcountry skiers by providing simple, scale-invariant tools to determine the real degree of exposure inherent to a route or objective.

The Model
LOCALE. A model for analysing exposure.

Criteria	Description
Line-Of-Sight	Is line-of-sight limited? Do local terrain features obstruct your line-of-sight to terrain above or below? Is your uphill view blocked by rocks or trees? Can you see all the terrain below or only some of it? Pay attention and double-check your decisions when line-of-sight is limited for any reason. Limitations to line-of-sight can reduce your reaction time to zero.
Open	Is the terrain open enough to produce small, medium, or large avalanches? Are there open breaks in the forest that allow snow to travel unobstructed to your location? How much open terrain is present and where is the open terrain relative to your location? Large quantities of snow can accumulate in open areas near mountain tops before an avalanche and in valley bottoms after an avalanche.
Confined	Is the terrain confined relative to the size or speed of an avalanche of any size? Could a large, fast-moving avalanche overrun the valley floor? Are you in a gully where escape from a small but fast-moving avalanche could prove impossible? Small avalanches form deep deposits in confined terrain, such as hollows or depressions, where snow can accumulate. Estimate your reaction time before something goes wrong and double-check your decisions if reaction time is short. Reaction time is a very important part of your margin of safety.
Accumulation	Has snow accumulated above or below? Avalanches often start where snow accumulates, and then run downhill where they deposit snow on the valley floor.
ObstacLes	Are there obstacles above or below? This includes cliffs, crevasses, rocks, and trees. Obstacles above may block your line-of-sight, inducing hazard blindness, and can cause traumatic injuries during any phase of an avalanche. On the other hand, obstacles can block or redirect flowing snow and may offer protection at your current location.
StEep	Is the terrain steeper than 30 degrees? Avalanches start and rapidly accelerate on steep terrain. Steep terrain produces fast-moving avalanches that can release above you and travel toward your location. If you trigger an avalanche on steep terrain, you may be unable to escape from the flowing snow. Steep terrain can limit your line-of-sight, and indicate locations suitable for sluffs, cornice drops, serac fall, or rock fall—all of which can start avalanches above or around you.

During Trip Planning
You can use this model during trip planning as well.

Examples
Two examples are provided, along with relevant markup. According to The Avalanche Handbook, it is important to consider combinations of features rather than simply identifying separate gullies, benches, and cliffs. These parameters find specific traps and diffuse sources of exposure for terrain of varying size. At the bottom, several unmarked examples are included for large, medium, and small scale terrain. Feel free to evaluate the unmarked images by using the LOCALE parameters.

Image 1.1. Goat Island Mountain. At a large scale, these parameters are mostly concerned with large avalanches. This type of analysis would be suitable for general route-finding. It's worth noting that areas with line-of-sight limitations and obstacles often present significant route-finding challenges.

CONCLUSION: This analysis helps you develop a big picture understanding of exposure and traps for this area. Travel through terrain on the left side of this image takes place above and below accumulators on steep, open slopes with numerous obstacles and many limitations to line of sight. Travel through terrain on the right side of this image takes place above and below accumulators, on steep, confined slopes with numerous obstacles, and many line of sight limitations.

Image 1.2. Chinook Pass. At a small scale, these parameters are mostly concerned with small avalanches. Several possible backcountry ski runs are illustrated. You can envision other backcountry ski runs in the context of the hazards. Despite its relative simplicity, some of the backcountry ski runs in this area have numerous obstacles, line-of-sight limitations, and and significant accumulation potential. Intricate terrain with complex groundcover makes beacon searches difficult.

CONCLUSION:The ski runs in this area are steep, with numerous obstacles, but line-of-sight is generally good, except in a few areas. Still, small avalanches could have very bad consequences in many of the ski runs. Intricate terrain increases time for search and rescue.

Try It Out
Use the LOCALE parameters to evaluate the terrain in the following photographs. Feel free to use your own photographs as well.

Image 1.3. Baker Backcountry. Line-of-sight, Open, Confined, Accumulators, Obstacles, Steep.

Image 1.4. Baker Backcountry. Line-of-sight, Open, Confined, Accumulators, Obstacles, Steep.

Image 1.5. Baker Backcountry. Line-of-sight, Open, Confined, Accumulators, Obstacles, Steep.

Image 1.6. Snoqualmie Pass Backcountry. Line-of-sight, Open, Confined, Accumulators, Obstacles, Steep.

Image 1.7. Snoqualmie Pass Backcountry. Line-of-sight, Open, Confined, Accumulators, Obstacles, Steep.

Image 1.8. Snoqualmie Pass Backcountry. Line-of-sight, Open, Confined, Accumulators, Obstacles, Steep.

Precision: Forecasting For Large, Medium, And Small Areas

Wish I knew what you were looking for, might have known what you would find—The Church

NOTE: Backcountry avalanche forecasting is composed of four interconnected elements: goal, people, awareness, and uncertainty. The size of the forecast area determines the precision of the forecast. It is more difficult to develop a forecast for a small area but the precision of the forecast is usually much higher than forecasts for large areas. Forecast precision is linked to awareness and uncertainty—maintaining awareness and managing uncertainty are central tools for helping people successfully align their beliefs about instability with reality ( which is the goal of backcountry avalanche forecasting ).

Introduction
Backcountry avalanche forecasting is concerned with the specific slopes where high-stakes decisions require more precise information than in available in the avalanche bulletin. Forecast precision is important because of its relationship to awareness and uncertainty.

For most people, the bulletin is available at the scale of an entire mountain range, and does not contain information about specific valleys or slopes. Therefore, information about specific valleys and slopes must be obtained from direct observations made in the field. Understanding how to prioritise your observations based on the size of the forecast area can greatly increase your backcountry avalanche forecasting skill. At the scale of an individual slope,variables such as slope angle, slope shape, and the snowpack on the slope ( and your desire to ski the slope ) are the primary concerns.

You must acquire this information in the field because the chaotic interaction between weather and rough mountain terrain causes complex changes in the existing snowpack and complex deposition patterns for new snow. Managing the resulting uncertainty, while maintaining an accurate sense of awareness about instability for a specific place and time, is the heart of backcountry avalanche forecasting.

Information Types And Size Of Forecast Area
Avalanche forecasting uses three types of observations: weather, snowpack, and terrain. The size of the forecast area determines how observations are prioritised. For regional and local forecasting, which consider large geographic areas, weather observations are the primary source of information, followed by snowpack observations, and finally terrain observations.

Backcountry avalanche forecasting is concerned with specific valleys or slopes. Here, terrain observations are the primary source of information, followed by snowpack observations, and finally, weather observations. To develop an accurate backcountry avalanche forecast for a single valley or slope, you need information relevant to the valley or the slope on which you plan to travel.

Table 1.1. Different scales of terrain with observations used in forecasting. For regional and local forecasts, a few very general terrain observations are used. This includes aspect and elevation band. For valley and slope forecasts, very specific terrain observations are used, including aspect, elevation band, shape, angle, and slope configuration. The priority of observations is reversed as the size of the forecast area decreases.

Forecast Area	Range	Size	Observation Priority
Regional	1000 square kilometres	Large	Weather, snowpack, terrain.
Local	100 square kilometres	Medium	Weather, snowpack, terrain.
Valley	10 square kilometres	Small	Terrain, snowpack, weather.
Slope	2-3 square kilometres	Tiny	Terrain, snowpack, weather.

NOTE: Any observation that reveals direct information about snowpack instability, such as whumphing or cracking at the snow surface, automatically receives priority over any other observations. Revise your forecast immediately if you observe any absolute indicators of instability, or if you obtain such information from snowpack tests.

Scenario: Backcountry Avalanche Forecasting In The Cascades
A strong winter storm forms as a large mass of warm, moist air is forced over the Cascade Mountains. During the storm, office-based avalanche forecasters use meteorological data, along with knowledge of how air masses interact with mountain topography, to produce a forecast that is relevant for the Cascade Mountains in general. The bulletin may include information such as aspects where you might expect to find wind-loaded snow deposits, or other information about the snowpack that has been directly observed in some places. However, much of the snowpack data in the bulletin is derived from the weather observations before and after the storm.

After the storm, the bulletin rates the current avalanche danger as high above 4000 feet and considerable below. Excited by the prospect of fresh tracks, you and your friends discuss a trip to Snoqualmie Pass to ski the Phantom Trees backcountry ski run. The bulletin contains a set of generalisations that are accurate for the Cascade Mountains but may not apply directly to Alpental Valley, and will not contain any specific information on conditions near the Phantom Trees backcountry ski run. What is the appropriate course of action?

Table 1.2. Different forecasting data order for areas of decreasing size in the Cascade Mountains. Backcountry avalanche forecasting is only concerned with producing forecasts for valleys and slopes, not entire mountain ranges. However, information from wide-area forecasts may be very useful during the backcountry avalanche forecasting process.

Forecast Area	Size	Type Of Information	Source Of Information
The Cascades	Large	Weather, snowpack, terrain.	Public Avalanche Bulletin
Snoqualmie Pass Region	Medium	Weather, snowpack, terrain	Public Avalanche Bulletin
Alpental Valley	Small	Terrain, snowpack, weather.	Local Observations
Phantom Trees	Tiny	Terrain, snowpack, weather.	Local Observations

Figure 1.1. Regional. The Cascade Mountains in Washington State. Sometimes wide-area weather patterns create snowpack features, such as crusts, facets, or surface hoar, found across large areas of the Cascades. So what's the catch? A lot of information is missing. Little is known about the specific properties of the snowpack over most of the Cascades, and little is known about the specific properties of weather interaction with terrain during a given snow storm. While you can develop an accurate forecast of instability in general by observing the weather, you simply cannot create a precise forecast of snowpack instability for all the valleys and backcountry ski runs in an entire mountain range from weather data alone. Precise information on the existing snowpack and current snow deposition patterns is extremely important for backcountry avalanche forecasting. The bulletin does not contain precise information about the structure of the existing snowpack on specific slopes, nor about new snow deposition patterns on specific slopes. Existing snow structure and new snow deposition patterns are critical variables for avalanche formation.

Figure 1.2. Local. The mountains around Snoqualmie Pass. Even though this area is much smaller than the entire Cascade Mountains, the public avalanche bulletin still does not apply to these groups of mountains except in a general sense. In this area, certain aspects and elevation bands may conform to the pattern of instability discussed in the bulletin. As you travel through the area, your observations will help you develop the first version of your backcountry avalanche forecast for the day. Do you notice large amounts of new snow? Recent avalanches of any type? Is it raining? Is it snowing? Is the ambient air temperature warm or cool? What is the expected air temperature trend? Weather observations are the priority since you are still dealing with avalanches on a large scale, but snowpack observations may be useful as well. Terrain observations are of little use since you won't be skiing in most of this terrain. ( Always follow the golden rule: pay very close attention to any observation, such as cracking in the snow surface or recent avalanches, that reveals direct information about snowpack instability. )

Figure 1.3. Valley. Alpental Valley. A backcountry avalanche forecast is usually prepared for a single valley, however some elements may be relevant to other valleys nearby. The public avalanche bulletin does not contain information about instability in this valley because office-based forecasters do not have precise information on the interaction between the weather and the terrain during the storm. Without precise information, office-based forecasters only have a rough, general idea about how the interactions between the weather and the terrain have affected the snowpack here. Combining information from the bulletin with your own observations helps refine your backcountry avalanche forecast even further: once inside the valley you can begin to examine the terrain and snowpack to see the actual conditions created by the recent weather.

Figure 1.4. Slope. Phantom Trees backcountry ski run. A slope forecast applies to a specific backcountry ski run inside the valley. The public avalanche bulletin does not contain information about instability for this ski run because office-based forecasters do not know exactly which slopes have been loaded by wind, nor do they know the exact locations of weaknesses and whether or not these weaknesses have the right structure, strength, and energy to release avalanches. Therefore, you must combine information from the public avalanche bulletin with your own observations to determine whether or not the snowpack is unstable inside this specific backcountry ski run. For example, a quick visual observation of the east bowl below the summit of Mt. Snoqualmie will provide information on whether or not the slope has been loaded ( is a cornice present? ) and whether or not there have been recent avalanches. This observation might tell you whether or not a lot of snow has been blown off the upper section of Phantom Trees, and gives you an idea about what you might find on the upper half of the mountain. Could there be a transition zone between the lower and upper section of the run where the snowpack is thin and weak? Several observations are noted in this image—it should be obvious that the bulletin does not contain information with this level of precision. By this point, you should have some degree of awareness about instability. However, it is still important to measure your residual uncertainty and make decisions accordingly.

With respect to signs of instability, absolutes are rare but they do exist.Any observation that reveals direct information about instability, such as whumphing or cracking at the snow surface, automatically receives priority over any other observations. Revise your backcountry avalanche forecast immediately if you observe any absolute indicators of instability, or if you obtain such information from snowpack tests.

Building A Nowcast From Your Observations
When it's time to ski up or down, you need a nowcast, which is your belief about patterns of instability on the slope you plan to ascend or descend right now. As you combine observations, whether from the bulletin or your own, consider whether or not the observations point toward instability. The distribution of weaknesses and the energy required to release avalanches changes with the passage of time and location, so you may need several nowcasts. For route selection purposes, it's useful to have a nowcast prior to uphill travel.

Figure 1.5. Distribution of weaknesses could range from very rare to very frequent. What do your observations suggest?

Figure 1.6. Triggering energy required to release avalanches could range from high triggering energy to low triggering energy. What do your observations suggests?

On the day of this ski tour, from observations collected prior to travel, it is reasonable to conclude:

• Observations of the snow surface above treeline show significant snow drifts.
• Relatively low energy triggering energy is required for avalanche formation in wind-deposited snow.
• Stability is poor on steep slopes above tree line.
• Because of the consistent temperatures during the storm, there are fewer weaknesses below treeline and slightly higher triggering energy is required for avalanche formation.
• Stability is good on gentler slopes below tree line and fair on steeper slopes below treeline.
• This only applies to areas where the snowpack is sheltered from the wind.
• There is a transitional region where stability is fair to poor on moderate and steep slopes at treeline.
• Ski quality is best below treeline.

The mix of stability ratings illustrates a key concept from this discussion: even at the smallest scale, one size rarely fits all.

Conclusion
Your perception of instability is likely to be at its worst when snow quality is very good but instability is relatively difficult to find or trigger. Understanding forecasting procedure for geographic areas of various sizes helps you maintain awareness and manage uncertainty by teaching you how to effectively prioritise your observations.

Research by Bruce Jamieson ( which may be relevant only in British Columbia ) shows that the public avalanche bulletin for the Columbia Mountains tends to predict higher regional danger levels than you might actually find in the field. However, local danger can be much higher on specific terrain features. This is why it is very important to combine information from the public avalanche bulletin, which covers a large geographic area and does not account for specific terrain features, with information that matches the much smaller size of a backcountry avalanche forecast region.

At which location is your perception of instability poorest? Below treeline or above treeline? Where are you most likely to make a mistake?

Perception Of Instability

She loves me, she loves me not—Unknown

NOTE: Backcountry avalanche forecasting is composed of four interconnected elements: goal, people, awareness, and uncertainty. The elements of instability are linked to awareness and uncertainty—maintaining awareness and managing uncertainty are central tools for helping people successfully accomplish the goal of backcountry avalanche forecasting.

Introduction
The winter snowpack is stable most of the time, which is a state of existence referred to as conditional instability. This means it is possible to trigger avalanches under certain conditions, provided you discover a weakness and deliver enough energy to release an avalanche.

Figure 1.1. State of instability. Instability fluctuates between very stable and very unstable.
During conditional instability, weaknesses are not widespread, and the triggering energy is relatively high. Perception of instability is much poorer when the snowpack is mostly stable because it is very easy to become blind to instability. On the other hand, perception of instability is usually very good when instability is widespread and triggering energy is very low. Important questions are as follows:

• What do I believe about the number of weaknesses and their locations?
• What do I believe about the triggering energy required to release avalanches on these weaknesses?
• Am I dealing with long-term weaknesses, short-term weaknesses, or some of each?
• Am I at risk of making errors when weaknesses are rare?
• Am I at risk of making errors when it may take a lot of triggering energy to release an avalanche?

To answer these questions, you have to start at the beginning, way back when your perception began to take shape.

The Origins Of Perception
This is a complicated subject, but it is important to realise that all of us have our own personal beliefs about the world around us. These ideas can influence our beliefs about snowpack instability and its consequences. Prior to a tour, you might review the public avalanche bulletin, or you might ask questions about local conditions on an Internet message board. You could also acquire information during the nightly weather report. Your perception of instability begins to take shape from the moment your brain begins to process relevant information. Similarly, taking an avalanche class may have a lifelong affect on perception of instability as a someone transitions from lack of awareness to awareness.

Your perception of instability is shaped whether or not you choose to manage the process. It's pretty easy to unconsciously form a perception of instability by reading the bulletin, talking to friends, and then making observations during a backcountry outing. However, it's much more useful to be consciously aware of what and how certain factors shape your perception of instability, and how this could affect your choices.

It's critical to remember that information of any kind can be helpful or harmful with respect to your beliefs about the presence and distribution of instability in the snowpack. This includes snowpack tests and weather reports and the presence of other parties. It is up to you to manage how this information affects your perception. Ideally, this information should help align your beliefs about instability with reality.

If your perception of instability is faulty, you will unknowingly expose yourself to hazards against which you will have little protection. If you can't assess your perception of instability, or if you feel your perception may have been compromised, then it's time to make conservative decisions.

Assessing Your Beliefs
Ask yourself the following questions:

• How does the public avalanche bulletin affect my beliefs about instability?
• How does the information I obtain from the Internet affect my beliefs about instability?
• How does seeing tracks on the snow, or seeing other groups of skiers, affect my beliefs about instability?
• How do weather observations affect my beliefs about instability?
• How do the results of instability tests affect my beliefs about instability?
• How does terrain selection reflect my beliefs about instability?
• Am I aware of which elements shape my perception?
• Am I aware of how my perception of instability affects my choices?

If you're interested in an quick exercise, evaluate a few memorable days from the last few seasons. If you can remember, write down your perceptions of instability on those days and look for patterns. Are your beliefs fairly uniform regardless of the public avalanche bulletin? Are your beliefs all over the map? Is it possible to place too much weight on the public avalanche bulletin and not enough on your own observations?

Are Your Beliefs Accurate?
Assess your beliefs about weaknesses and triggering energy to shape your perception of instability. This begins with your beliefs in general, and includes how the public avalanche bulletin influences your beliefs, and the effects of data sampling in the field.

Types Of Instability

Don't you, forget about me—Simple Minds

NOTE: Backcountry avalanche forecasting is composed of four interconnected elements: goal, people, awareness, and uncertainty. The type of instability is linked to awareness and uncertainty—maintaining awareness and managing uncertainty are central tools for helping people successfully accomplish the goal of backcountry avalanche forecasting.

Introduction
It's important to outline the two key classes of instability: temporary instability in new snow and persistent instability in old snow. Safe winter backcountry travel often involves dealing with both types of instability to some degree. Persistent instabilities are harder to trigger but much more difficult to manage. Temporary instabilities are much easier to trigger and easier to manage. Since it doesn't take very much snow to bury, injure, or kill a person, both types of instability can be equally dangerous.

Table 1.1. The two types of instability.

Class	Description
Short-Term Instability	Generally found in new snow ( storm snow ). Instability expressed by loose snow avalanches and soft slab avalanches. Generally does not surprise professionals; definitely surprises recreationists. Instability at surface is easy to find. Large, new-snow slab avalanches may trigger secondary avalanches that involve long-term instability. Recency is critical factor; sensitivity to trigger is high. Hazard is obvious.
Long-Term Instability	Generally found in old snow. Instability expressed by wet or dry hard slab avalanches. Surprises professionals and recreationists alike. Instability far below surface is difficult to evaluate. Produces large primary avalanches. Sensitivity to trigger is unknown; recency is much less unimportant. Hazard is unclear.

Combinations Of Short-Term And Long-Term Instability
Absolutes are rare in chance-based activities such as backcountry avalanche forecasting. Even the type of instability is rarely a choice between one or the other. For the purposes of backcountry avalanche forecasting, instability is separated into weaknesses and triggers. The actual type and distribution of these weaknesses is usually a mix of long-term and short-term instabilities.

Figure 1.1. Combinations of long-term and short-term instability. The typical state of instability is often a blend of both, and largely defined by recent weather and the parameters of the snowpack.