by Brian Lazar and Ethan Greene

Santa delivered a lot of snow to Colorado in the past two weeks, just in time for Christmas. Have we been naughty or nice? Well riding conditions have been fabulous, but there have been some impressive avalanches.

The last storm brought significant snowfall and avalanche activity, but since then the snowpack has been getting stronger and we’ve seen fewer avalanches and less cracking and collapsing.  Paradoxically, this does not mean things are necessarily safer for the backcountry traveler. The likelihood of triggering an avalanche is decreasing, but the size and consequences of avalanches that do release are steadily increasing.  This trend has prompted discussions amongst our forecasters about whether or not we are moving into a new risk paradigm, and perhaps, a new avalanche problem: Deep Persistent Slab (DPS) avalanches.

DPS avalanches have many characteristics in common with Persistent Slab (PS) avalanches. Both break on persistent weak layers. You can trigger both remotely and from low-angle slopes. Both of these types of avalanches can fail in surprising ways, breaking across and around terrain features that would contain a Storm or Wind Slab avalanche. PS and DPS avalanches have a lot in common, but there are some very important differences that affect how we avoid them and manage our own personal risk.

DPS avalanches are low probability and high consequence events. The likelihood of triggering a PS avalanche and the size of that avalanche can vary over a wide range. DPS avalanches are a specific creature, very large in size and hard to trigger.  We look for three things before we add it to our list of Avalanche Problems. Those three things are:

• Avalanches will be  stubborn to trigger,  Unlikely or Possible on the Likelihood scale
• Avalanches will be destructive,  D3 or larger
• Avalanches will break on deeply buried or basal weak layers

These criteria capture the low-probability/ high-consequence nature of DPS avalanches.  A low Likelihood means there will be very few or no natural avalanches, human-triggered avalanches will be unlikely, and large explosive and cornice triggers will only produce some results (ADFAR2).  A D3 (Very Large) avalanche could bury and destroy a car, damage a truck, destroy a wood frame house, or break a few trees. When the likelihood slider drops towards “Unlikely” and the size slider climbs to “Very Large or Historic”, we have a DPS avalanche problem (see image below).

DPS avalanches are especially scary because most people don’t have much experience dealing with them.  It is hard to gain experience dealing with these beasts because we don’t see DPS avalanche cycles that often. In a typical year we could see over twenty cycles of Storm, Wind, and Persistent Slab avalanches, but we may only see one DPS avalanche cycle in five years.  You could navigate through two Storm Slab avalanche cycles in a week of touring, but it could take you ten years to gain the same amount of experience with DPS avalanches. These avalanches are also very large and extremely dangerous. Most people that get caught in one get killed.  This makes it very difficult to learn from a close call. Your first encounter with a DPS avalanche could very well be your last.

Over the last 15 years, almost all avalanche accidents in Colorado where more than one person died were the result of a DPS avalanche. In two seasons with pronounced DPS avalanche cycles (2008-09 and 2012-13), DPS avalanches accounted for more than 60% of the avalanche fatalities.  In the figure below (covering two seasons: 2012-13 and 2013-14) you can see that avalanches involving persistent weak layers are particularly dangerous. DPS avalanches only accounted for 5% of the observed avalanches, but caused 42% of the fatalities.  Sure sounds like low-probability/high-consequence, doesn’t it?  You can read the whole study here.

In a year with DPS avalanches we can describe the forecast zones where they could happen and the aspect and elevation of the slopes that are most likely to produce one. This is the good news. The bad news is that if you have ten of those slopes, it is really hard to predict which one will produce a DPS avalanche. This is the low probability part. Remember the other half of the description is high consequence. Because DPS avalanches are so dangerous, the only safe way to manage your risk is by avoiding those suspect slopes. On a bad year, you might have to avoid those slopes for the rest of the season. This can be hard to do because people will test suspect slopes, and most will get away with it (they are low-probability events). And due to the nature of a DPS avalanche problem the danger is almost always MODERATE (Level 2) when this is our main avalanche problem, because these avalanches are hard to trigger. That combination -people testing slopes without immediate consequences and a MODERATE (Level 2) rating – doesn’t scream “dangerous” the way an avalanche warning does.

So where are we this year?  In some places we can produce D3 avalanches, as demonstrated by the mid-December avalanche cycle.  Between December 14 and 21, multiple D3 avalanches released in the Aspen, Gunnison, North San Juan, and Front Range zones. This includes both natural and human-triggered slides.  Around half of these avalanches ran naturally during and shortly after the storm cycle. So while we met the size criteria, we weren’t at the point where we called these avalanches stubborn to trigger. Instead, we had Likely to Very Likely, and Large to Very Large PS avalanche problems. This resulted in avalanche warnings and HIGH (Level 4) danger.

The likelihood of triggering PS avalanches in these areas has since decreased, but some notable D3 avalanches released post storm.  A narrow escape near Crested Butte, a very large avalanche triggered by a snowcat near Loveland Pass, and explosive triggered slides north of Berthoud Pass, and very large avalanche with an unknown trigger near Cameron Pass have us talking about if a potential DPS problem is in our future.

It is getting harder to trigger an avalanche that breaks into the weak snow near the ground in most of the forecast zones. So the Likelihood of triggering a Persistent Slab avalanche in decreasing. We have seen Very Large (D3) avalanches in the Aspen, Gunnison, North San Juan, and Front Range zones.  Most of these zones have a deep enough snowpack to produce more Very Large (D3) avalanches.  The Sawatch and Vail/Summit zones picked up less snow during the mid-December storms. Most of the avalanches in these zones have been large enough to kill you (D2), but not large enough to destroy a vehicle or timber structure (D3).We have a basal weak layer, the avalanches are getting harder to trigger, and in some zones they getting quite large. Although we have not started to warn people about DPS avalanches, some of the PS avalanches are getting larger and harder to trigger. The weather over the next couple of weeks will determine if we are just going through a scary period, or if we’ll move into a DPS cycle that lasts the rest of the season. For now, remember that we’ve seen some tricky conditions over the last few weeks and there is no indication they are over. Please read the forecast before you go out and keep in mind that this kind of Moderate (Level 2) danger includes some pretty big avalanches.

Stay safe out there and enjoy the snow!  Happy New Year!

Click here to learn more about Avalanche Problems from the USFS National Avalanche Center.

By Nick Barlow

One of the most useful resources provided on the CAIC webpage is the weather stations page (Observations > Weather Stations). Here you will find a table of hourly and archived observations from a large network of weather stations throughout Colorado, sorted by forecast zone and elevation.

A screenshot of the CAIC Weather Stations Page

The several highlighted columns report different quantities of precipitation. For SNOTEL stations, up to seven different readings are given. Below is a description of these readings, the instruments that take them, and how the data can be useful for backcountry users.

Snow Water Equivalent (SWE)

SWE is the total amount of water contained in a fixed sample of snow. More simply, it is the resulting depth of water if the entire sample melted. In this context, “sample” could mean the entire seasonal snowpack (SWE), or just new snowfall over the past 24-hours from a single storm (SWE24). Seasonal SWE is particularly useful for long-term hydrological applications, such as forecasting water supply or seasonal runoff. For example, water managers use the data to determine how much water is stored in the mountain snowpack for the warmer months ahead. This is the primary function of the SNOTEL network, and the strategic placement of stations in important water basins throughout the United States. Yet SWE is also relevant for backcountry users.

The density of water varies only slightly with temperature. By contrast, snow density varies significantly from storm to storm. The SWE calculation is a way of standardizing snowfall for use in further applications. When we think about loading weak layers in the snowpack, calculating SWE can be of great value. The data can reveal the load added to the snowpack from an individual storm.  By comparing SWE to snow depth, we can also discern whether the storm snow was dense and heavy vs. light and fluffy.

At SNOTEL stations, SWE is measured using snow pillows: large 3-meter x 3-meter bladders (steel and rubber) installed on the ground and filled with a volume of antifreeze. As snow accumulates on top of the pillow throughout the winter, instruments measure the increasing hydrostatic pressure upon the liquid. With that, the mass of the overlying snow is calculated.  Knowing the density of water allows us to calculate SWE. A snow depth measurement allows us to calculate snow density.

Snow pillow and depth sensor

Measuring Snow Depth

Snow depth is perhaps the easiest quantity to measure, simply by using a ruler or avalanche probe. It is more complicated at remote weather stations with the automated measurement and logging of data.

At SNOTEL stations, an ultrasonic depth sensor mounted above the snow pillow measures the snow depth. The sensor sends a signal downward towards the ground and measures how long it takes the signal to bounce off the snow surface and return to the sensor. Knowing how fast the signal travels, a properly-calibrated sensor will give an accurate reading of snow depth.  On the weather station page, there is a field for changes in depth over a 24-hour period (Sno24), in addition to the total depth of the snowpack (SnoHt).

The ultrasonic sensor is also useful for backcountry users. Most simply, it is the only tool at a SNOTEL station that can tell you how much new powder you’ll find on any given day. However, you can glean more, and more important information from a SNOTEL site.

For one, the total depth of the snowpack can be particularly useful. A shallow snowpack can promote changes in snow structure, and create persistent weak layers. This is important information to gather before traveling into the backcountry. On a shorter time-scale, the amount the snow depth increases in a single storm is a good estimate of how much snow is available for wind transport. We can also estimate the depth of new Storm Slab or Wind Slab avalanches, and at what depth we might find the old/new snow interface in our snow pits.

Measuring Liquid Precipitation

SNOTEL stations are equipped with a precipitation gauge to measure liquid for the entire water-year. During the warmer months, rain simply falls into the gauge. The gauge then measures and logs the data automatically. Snow also falls into the same gauge during the winter months. However, sub-freezing temperatures would make any kind of liquid measurement essentially impossible. To combat this effect, SNOTEL precipitation gauges are “charged” with a volume of propylene glycol, melting the snow on contact as it falls into the gauge. The gauges also contain mineral oil, designed to sit on top of the collected liquid and prevent evaporation over time. On the weather station page, data is in 1-hour (Pcp1), 24-hour (Pcp24), and since-midnight (PcpAc) format.

Liquid precipitation gauge

For backcountry users, liquid precipitation data can also be useful. Ideally, data from this gauge would match the calculated SWE data from the snow pillow and ultrasonic sensor. This is not always the case. It’s important to recognize the differences and primary functions of each piece of equipment. Data from the liquid gauge is used for seasonal purposes. The gauge keeps measuring precipitation long after the snow melts away from the snow pillow.

However, the data can be used in conjunction with the SWE and snow depth in order to provide a more well-rounded answer to what is going at the station. An example would be for rain-on-snow events.

Snow pillows may not always capture added SWE from rainfall, as some of the liquid may channel away from the pillow. In this case, the liquid gauge is the only piece of equipment that could tell us if rain-on-snow has occurred. A simultaneous temperature reading from the SNOTEL could also reinforce our suspicions.  

Takeaway

Remember that automated SNOTEL stations exist in remote mountain locations. The stations use three different pieces of equipment to measure precipitation, and each piece has its own unique purpose for being there. Like any equipment, the gauges are prone to both random and systematic errors, and the data may not always be trustworthy.

A variety of issues can (and do) arise at SNOTEL stations. For this reason, they require continued maintenance and quality control of the data they output. This can be exceptionally difficult during the winter months, as access to many of the stations is difficult.

As backcountry users, we should analyze each piece of data individually before forming a conclusion about what has transpired. Compare the different forms of output (SWE, depth, melted liquid) and attempt to read between the lines.

Also, recognize the data is from a single point, and may not be representative of the entire area in which you’ll be traveling. Of all meteorological surface measurements, precipitation is by far the most spatially variable. You will likely find inconsistent snowfall results within different elevation bands and aspects as well. Study the data from other near-by stations; learn which stations typically receive more or less snowfall than others.

Most of all, be thankful the SNOTEL network exists. It is a wonderful tool to have at our disposal. These stations shed light into the dark and cold, providing us with vital information at just a mouse-click away.

Overview of precipitation quantities

Blase Reardon

On January 17th, 2014, a pair of riders triggered a large avalanche on a steep, near-treeline slope in the backcountry behind Snowmass Ski Resort. The slope had previously been nicknamed “Mr. Magoo’s” after a ski patroller who sometimes acted like the near-sighted cartoon character. The riders escaped unhurt, despite an ugly terrain trap below. An hour later, the resort’s snow safety director watched a solo skier turn down the same slope and trigger a second slide adjacent to the first. He met the solo skier as he returned to the resort and asked him whether he’d seen the first slide—or the larger natural avalanche just up the drainage at the same aspect and elevation. The solo skier replied, “It’s okay; I have skied Silverton and I skied the path a couple of years ago.”

The slope where the January 17th incidents occurred is steeper than 35 degrees and faces southeast. On that day, it was blanketed with a foot-thick slab formed by a recent storm and subsequent cross-loading; the slab sat on a thin, persistent weak layer. It was a slope that closely fit a pattern of recent avalanche activity and that was highlighted in the CAIC forecast as the kind of slope where people were most likely to trigger slides. With the danger rated as Considerable, skiing that slope on that day was a risky proposition, especially alone and with a fresh slide visible.

The solo skier didn’t answer the question posed to him – did he see the other slide and, implicitly, was he concerned about avalanche danger on the slope? Indeed, he seemed to answer a different question altogether, one centered on skiing rather than avalanche conditions. Perhaps standing at the top of Mr. Magoo’s he asked himself, “Can I ski a slope like this?” And his answer seems to have been “Yes, because I’ve skied slopes this steep before. I’ve even skied this slope before.”

According to Nobel-prize winner Daniel Kahneman, substitution like this is a nearly automatic cognitive response to complex, irregular environments. Our brains produce what Kahneman calls “off-the-shelf answers” to difficult problems by answering simpler, more familiar questions. It’s a sub-conscious process, and it provides solutions that leave us feeling very confident in our assessments and choices. Assessing the risk of triggering a slide on a steep slope covered with new snow is a complex task, fraught with uncertainty. Faced with that, our brains quickly default to questions with simpler answers, like “Can I ski this slope without falling?” or “Will the skiing be as good as it looks?”

Marketing provides numerous everyday examples of this pernicious tendency. When faced with a question like “Is this the best pair of skis for me to buy?” we often answer a question more like “Do I like this brand of skis?” or “Do I like the graphics?” In situations like these, substitution often provides adequate answers, because the alternatives aren’t that different and the consequences of not answering the initial question aren’t severe. And substitution has the advantages of saving us mental energy and time. Once we’ve substituted a simple, seemingly coherent answer to a complex question, we can confidently summon numerous arguments supporting our choice without recognizing the substitution.

That leads us back to Mr. Magoo, the cartoon character referenced in the slope’s nickname. Mr. Magoo stubbornly refuses to recognize his near-sightedness. He doesn’t have to, because situations always work out for him. Magoo mistakes an airport for a movie theater, takes a seat on a departing plane—”It’s like I can feel the plane taking off!”—wanders around on the wings, unknowingly leads the police to a bank robber, and when the plane lands, tells the flight attendant he really enjoyed the film. The tension in the Mr. Magoo cartoons derives from seeing how lucky the character can get yet be oblivious to the dangers he’s facing, thanks to his near-sightedness . They’re funny because we know his luck will never run out.

We can all be Mr. Magoos in the backcountry. When nothing bad happens, it’s easy to finish a day of skiing or riding in avalanche terrain feeling confident we made good choices. So it’s easy to take the wrong lessons from our experiences. We’re sure we really liked the movie, unaware of how close we came to falling off the wing. The three riders involved on the slides on January 17th might easily conclude that they judged conditions correctly. More correctly even than the forecast, which called slopes like Magoo’s dangerous. None of them were hurt. The answer of “Yes, I can ski this” seemed to work, so the solo skier might be more likely to rely on it the next time he’s faced with a slope where the stability is questionable.

The winter backcountry is no cartoon, however. Substituting an easy question for the relevant one can kill our friends, our loved ones, or us. Our luck can run out. Or we may not get lucky at all. It’s what Kahneman and others have termed a “wicked environment”—an environment in which a lack of regular, reliable feedback allows us to develop habits and patterns based on faulty correlations, or luck.

So, what’s the alternative, given our brain’s hardwired proclivity for substitution and the wicked nature of the backcountry? How do we keep from being Mr. Magoo?

The avalanche on Magoo’s

In previous section of this article, I noted that the winter backcountry is an instance of what Nobel-Prize winning researcher Daniel Kahneman and others describe as a “wicked environment” for developing expertise. In part, that’s because expertise in the backcountry is a collection of skills. We have to master the individual elements—technical skiing and riding skills, route-finding, and stability assessment among them—while simultaneously learning which items in the set to prioritize and apply in a given situation. It’s also because in the winter backcountry, we don’t get much immediate, consistent feedback on our decisions and actions. We rarely know how close we are to triggering a slope, so it’s easy to develop habits and patterns based on faulty correlations, or luck.

A real-world example of the rarity of immediate feedback in avalanche terrain surfaced a few years ago, in a video posted on YouTube that’s since been pulled. It showed a skier finishing a run on Puckerface, a steep slope near Jackson Hole Mountain Resort. The soundtrack includes lots of whooping. Then a title card appears, reading “Second Run. 10 minutes later.” A snowboarder starts down the same face, and makes a hard first turn. The entire slope fractures several feet deep, and slides. The snowboarder claws into the bed surface and stops. The camera shakes and jerks, accompanied by lots of cursing. The snowboarder walks away on the ridge. The video shows the slide a second time, in slow motion.

Let’s put ourselves in the boots of the first rider on Puckerface on January 2, 2012. We choose to ride the  slope for some reason—maybe a well-considered assessment of stability, maybe by substituting a question that’s easier to answer, like whether there’s enough sun on the face for good video. When it doesn’t slide, we conclude our rationale was correct. Given enough similar experiences, we could start to feel very confident in our skills. But the slide triggered by the second rider reveals a more accurate conclusion: we got lucky. And instead of developing skills, we might just be getting lucky, a lot.

Puckerface, just after the 2014 fatal avalanche. Photo courtesy Alex Do.

The image above also shows Puckerface on an early-winter day, this time nearly two years later, on Dec. 26, 2013. On this day, a rider wasn’t so fortunate; he was killed in the slide visible in the image. That’s the potential penalty for substitution, inadvertently relying on luck, or just plain making a mistake. Each day in avalanche terrain, each run or route we chose, is unique and novel; we have incomplete or ambiguous data, we get one chance, and the cost for choosing badly can be fatal.

An alternative to relying on luck is expert intuition—distinguishing familiar cues in a new situation and choosing an appropriate response. As Kahneman notes, “Expert intuition strikes us as magical, but it is not…[It] is nothing more and nothing less than recognition.” It’s Mr. Magoo with eyeglasses, a prescription that lets him recognize an airplane instead of confusing it for a movie theater. In his classic essay “The Ascending Spiral”, pioneering snow scientist Ed LaChapelle echoes that point; intuition “is not some sort of extra-sensory perception.” He describes it as a “lifetime accumulation” of observations about snow, avalanches and weather. That doesn’t just happen, because the backcountry is a wicked environment. We help develop it by adopting simple habits that, over time, make the backcountry environment more regular and expand the base of stored cues necessary for expert recognition.

Below are examples of practices  that can improve the quality of our observations, our communication, and the feedback for our decisions.

It’s all about the up: Most—at least two thirds—of our time in the backcountry is spent going up. It’s our best opportunity for observing and communicating. It’s also when most miscommunications and mistakes occur. Set a low-angle, meanderthal skin track that takes advantage of the terrain to investigate different aspects and slope angles, and that allows relaxed discussions of your observations without having to stop. Steep skin tracks make it hard to see much beyond your ski tips, and even if you do notice something important, it’s hard to communicate it when you’re anaerobic. If you’re breaking trail and can’t hear the group behind you talking, your track is too steep for easy observations and communication.

Give it a rest: Take breaks at decision points. Fiddling with your clothes or gear randomly just slows you down yet provides little information about snow conditions or route choices. Stopping to drink, eat and layer up when you’re faced with a decision is productive; it allows you to look around when you’re comfortable and talk about what you see. More often than not, you’ll pick up nuances in the terrain that you didn’t see while moving and out of breath—as will your partners. And you’ll make better decisions when your brain isn’t starved for oxygen or nutrition. Pace your group so you’re moving steadily and don’t feel rushed when you stop at decision points.
You are not the Captain now: Encourage feedback within your group. You’re looking for ideas that can save your ass, not aiming for agreement. It helps to rely on questions rather than declarations. “Does that side of the slope look wind-loaded?” instead of “Most of the slope isn’t wind-loaded.” Listen for contrarian opinions rather than trying to silence a squeaky wheel. Acknowledge that anyone in the group has veto power.

Write it down: Keep a field notebook or submit observations to your local avalanche center after each backcountry trip. It’s a sure way to notice and remember details about snow and weather conditions.. Summarizing them for a field report forces you to make sense of what you observed, to sort what’s most important from what’s irrelevant. And it gives you something besides dim memories when you’re checking impressions of past events.
Debrief: When we talk about a day in the backcountry immediately afterwards, we often focus on the highlights—the great run, the funny fall, the beautiful light or snow. You provide otherwise unavailable feedback on your decisions by including an opportunity to talk about how you did things and whether those actions put you at risk. Guides often do this formally, in afternoon meetings in which they can identify when they were most at risk during the day. A friend’s more informal approach, is to ask, “Well, did we get it done, or did we get away with it?” Find a way to expand your end-of-day conversation to more than high fives. If something nags at you a day or a week later, talk with your partners so everyone understands and learns from the experience.

Find a mentor: Years ago, I spent a day traversing a high peak in the Wasatch with a mentor when the avalanche danger was high.  It was a lesson in micro-route-finding. Near the end of the day, when it seemed we’d mostly passed the hazards, I took a few extra turns on a small slope I now recognize as a terrain trap. I looked up to see my mentor giving me a look that said, “That. Was. Dumb.” That look still floats into my consciousness when I encounter similar slopes. Though the look clearly communicated stupidity of my move, it was much more forgiving feedback than triggering the slope. Or another like it, because without that mentorship I might have gone much longer without learning to take small slopes seriously. You learn from (and with) a mentor in an iterative process, the goal of which is your becoming equally skilled and knowledgeable, perhaps more so, than your mentor. This relationship is different than that with a guide, who may pass on some useful tips but who is a leader.

Others with extensive expertise in the backcountry can offer up other practices like these, which may work better for them or better period. The point is less the specific habits than making an effort to maximize the quality of our decisions and the feedback we get for them, so we have the best chances of seeing our Mr. Magoo-like close calls and learning from them, without the too-painful learning that comes if our luck runs out.  Time in the backcountry with that kind of reflection is what leads to the lifetime of accumulation and instant recognition that Kahneman and LaChapelle identify as expertise.