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Wednesday, February 17, 2010

The Answers

It's the school exam and the kids have run away—New Order

Here are the answers.

The Answers
  1. Describe Ian Burton's rule of thumb for natural disasters. Richer is better.
  2. Does this rule of thumb apply to avalanches in Western North America? No, this rule of thumb does not apply to avalanche involvement in North America. Relatively speaking, people who seek powder snow are among the wealthiest, including many backcountry skiers and most helicopter skiers.
  3. What is the Earth's weakest surficial material? Snow is the Earth's weakest surficial material.
  4. What is the ratio of air/ice commonly found in avalanches? The ratio of air/ice commonly found in avalanches is about 90% air and 10% ice crystals.
  5. Alpine snow is typically found within how many degrees of its melting point? Within a 2 or 3 degrees Celsius.
  6. Significant avalanche research started in what country and in what year? Significant avalanche research started in Switzerland during the 1930's.
  7. Describe how equipment modifies human behaviour. Improved equipment modifies human behaviour by allowing people to engage in activities that would otherwise be far more dangerous. Avalanche transceivers are a good example, because many people will ski in avalanche terrain while wearing a transceiver, but will not ski in avalanche terrain without a transceiver. The presence of the transceiver modifies people's behaviour.
  8. What percentage of backcountry travelers trigger the avalanche themselves? 90% of avalanche victims trigger the avalanche that buries them.
  9. What does this suggest about the root cause of these fatalities? The root cause of these fatilities is failure in perception; people believed the snow was safe when it was not safe.
  10. Name three major components of risk? Chance, consequences, and exposure.
  11. What causes most destructive avalanche cycles? Direct loading of slopes during synoptic scale weather events causes most destructive avalanche cycles.
  12. List three snow climates found in North America and briefly describe each. Maritime. Large amounts of precipitation, relatively warm temperatures, and many direct-action avalanches. Transitional. Large amounts of precipitation, cool temperatures, and a mixture of direct-action and delayed-action avalanches. Continental. Small amounts of precipitation, cold temperatures, and a combination of direct and delayed-action avalanches.
  13. Minor changes in slope angle have a significant affect on the character and areal distribution of wind deposited snow. True or False. True. A small change in slope angle can provide a perfect location for drift formation.
  14. Can avalanches occur from loading when snow is not falling from the clouds? Yes, avalanches can occur when strong winds load slopes with snow that has already fallen.
  15. Heat transfer in alpine snow is very rapid. True or False. False. Heat transfer in alpine snow is very slow, which is one reason that weak layers can persist for long periods of time.
  16. List the two key types of radiation that affect snow surface temperature. Shortwave and longwave radiation, whether direct or indirect.
  17. Variations in snow crystal type are responsible for some avalanches? True or False. True, variations in crystal form are responsible for some avalanches. This is usually a concern with storm snow, but some variations, such as a layer of plates below a layer of stellars, can create persistent weaknesses.
  18. Provide the common definition for surface hoar. Surface hoar is the equivalent of frozen dew.
  19. Describe the process by which surface hoar forms. Longwave radiation loss causes extreme cooling at the snow surface. Humid air, including clouds and fog banks, provides a source of moisture for crystal growth on the supercooled snow surface. A small amount of air motion is required to replenish the moisture, but most observers would regard the air as calm.
  20. Provide the common definition for facets. Facets are ice crystals with sharp, angular edges and surfaces.
  21. Describe the process by which facets form. Facets form when a strong temperature gradient causes movement of water vapor from the base of the snowpack toward the surface of the snowpack. Specifically, water vapor moves from areas of higher concentration inside the snowpack to areas of lower concentration outside the snowpack.
  22. What is the relationship between trees and snowpack metamorphism? Trees intercept snowfall, reduce incoming radiation, and inhibit loss of longwave radiation. In addition, trees drop bombs of snow which help break up the snowpack. Since trees prevent longwave radiation loss, surface hoar is less likely to form beneath tree cover.
  23. Describe snow grain types often found near rocks. Facets are often found near rocks.
  24. Why do these grain types form near rocks? Rocks absorb radiation from the sun. As a result, a temperature gradient forms near rocks and the surrounding snow. This is sometimes referred to as a sideways temperature gradient.
  25. List three types of ground cover anchors. Rocks, trees, and shrubs.
  26. What serves as the upper and lower boundaries for winter snowpack? The ground serves as the lower boundary and the air serves as the upper boundary.
  27. Which boundary is usually cooler? The air at the upper boundary.
  28. Once deposited on the ground, how many minutes must pass before snow crystals begin to change form? Zero. Crystals begin to change form immediately.
  29. Why do these initial changes cause direct-action, loose-snow avalanches? In some cases, networks of grains are held together by static friction. Initial changes to crystal form cause loss of branches, which results in loss of contact points. Unable to cling to each other, the crystals begin to slide downhill.
  30. Why do crystals change form? Crystals change form because temperature and supersaturation in clouds is different from conditions on the ground.
  31. What snowpack-related force rearranges grains in the snowpack? Overburden pressure.
  32. Growth rate and crystal form are more dependent on pore size than temperature gradient? True or False. False. The temperature gradient is the primary factor in growth rate and form. Pore size is a secondary factor.
  33. Faceted forms and highly angular snowflakes develop because of similarities between vapor saturation conditions in the atmosphere and snowpack. True or False. True. Relatively high supersaturation and relatively warm temperatures produce large, angular crystals.
  34. Why does depth hoar only form near the ground? Be very specific. Depth hoar forms near the ground because of relatively warm temperatures, high supersaturation, and long growth time. ( Depth hoar crystals are the oldest in the snowpack, and therefore have the longest growth period, at the highest temperatures, and highest supersaturation values. )
  35. How does a crust influence crystal formation? Crusts influence crystal formation by providing a vapour barrier that allows high supersaturation values required for development of faceted crystals.
  36. What leads to dry/wet faceting? Dry snow falling on wet snow causes dry/wet faceting. Latent heat in the wet snow, in combination with cold temperatures in the dry snow, creates a temperature gradient that drives the faceting process.
  37. If avalanches released easily on depth hoar, what conclusion could be drawn about travel in continental climates? Travel in continental climates would be much more dangerous that it actually is.
  38. Who coined the term "persistent forms"? Canadian researcher Bruce Jamieson.
  39. What are the characteristics of the persistent forms? Anisotropy: weaker in shear than compression, low number of bonds per unit volume, and low hand hardness.
  40. Discuss human perception with respect to persistent forms. The persistent forms are buried beneath the surface of the snow where they may remain "invisible" or "forgotten". Therefore, the persistent forms are related to many avalanche accidents where people believe that unstable snow is actually stable.
  41. Name the two most general classifications of avalanches. Loose snow avalanches and slab avalanches.
  42. What is the normal range of slope angles for slab avalanche release? 25 to 50 degrees.
  43. Triggering is possible during travel over flat terrain. True or False. True.
  44. What is the minimum thickness required to bury a skier? About 12 inches or 30 centimetres.
  45. Skier triggering of slabs thicker than ________ is rare. 1 metre.
  46. Define the two basic situations in operational avalanche forecasting. The two basic situations are absolute instability and low instability. However, the typical state of the winter snowpack is somewhere in the middle - this is referred to as "conditional instability".
  47. Define the basic rule of route selection. Avoid steep slopes when the snow is unstable. Do not enter them, and do not cross below them.
  48. Recent tracks indicate stability and safety because the slope has already been tested. True or False. False.
  49. Around what element is modern avalanche forecasting framed? From what perspective are forecasts issued? Modern avalanche forecasting is framed around "instability" and forecasts are issued from the perspective of the "trigger".
  50. List all seven elements of applied avalanche forecasting. Definition, goal, information types and relation to perception, reasoning processes, human factors and perception, scales in space and time, decision-making. 
  51. Avalanche forecasting is a ________ problem. Dynamic.
  52. All seven elements are ________. Interconnected.
  53. Most avalanche accidents occur as a result of human errors. True or False. True.
  54. Provide the definition of forecasting. Forecasting is the prediction of current and future events.
  55. Define the root cause of most avalanche accidents. Perceptual errors. People believed the snow was stable when it wasn't.
  56. How is avalanche forecasting linked to risk analysis? The link between avalanche forecasting and risk analysis is formed when decision-making follows the prediction issued by an avalanche forecast. Since these decisions involve a chance of losses, the process of avalanche forecasting and the resulting decision-making is the equivalent of a risk analysis.
  57. Is avalanche forecasting limited only to estimates of instability? Explain why or why not. Avalanche forecasting is not limited to estimates of instability. There is a connection between avalanche forecasting, decision-making, and the inherent risk of those decisions.
  58. Define the major physical uncertainty with respect to avalanche forecasting. The spatial and temporal variability of the snowpack.
  59. Avalanche forecasting is defined in terms of ________. Instability.
  60. Whereas traditionally, avalanche forecasting was defined in terms of ________. ( Omitted )
  61. In avalanche forecasting, what type of information is most highly prized? Information that reveals instability.
  62. To what does triggering level refer? Triggering level refers to the amount of energy required to release an avalanche.
  63. Provide three examples of types of forecasting relative to triggers. Forecasting for natural releases, forecasting for skier triggering, forecasting for explosive triggering.
  64. How do most slab avalanches release? Most slab avalanches release from overloading by precipitation or wind.
  65. Upon what does the energy required to release a slab avalanche depend? The energy required to release a slab depends largely on the size of imperfections and the parameters of the load applied at any given time. In this case, parameters of load applied means intensity, which is expressed roughly by the amount of force and the rate at which the force is applied ( the balance between shear stress intensity and shear fracture toughness in the weak layer ).
  66. What is the primary reason avalanche forecasting is probabilistic, with a risk-based character? At all times, but especially during times of conditional instability ( the prevailing state ), the size, state, quantity, and distribution of weaknesses and imperfections ( such as weak zones and weak interfaces ), and the energy required to trigger a slab release on any such weakness, are unknown. Therefore avalanche forecasting can be reduced to encounter probability and trigger probability, i.e. "what is the chance of encountering a critical imperfection and how much energy will it take to trigger an avalanche". These probabilities give avalanche forecasting its risk-based character.
  67. Define the goal of avalanche forecasting and discuss the primary sources of uncertainty. The goal of avalanche forecasting is the reduction of uncertainty about snowpack instability. The primary sources of uncetainty are variations in human perception, incremental changes to the snowpack, and the spatial and temporal variability of the snowpack.
  68. State the goal of avalanche forecasting from the human perspective. From the human perspective, avalanche forecasting seeks to align perception and reality, i.e. human perception of instability across the spatial and temporal scales should match reality as closely as possible.
  69. How is this goal accomplished? Aligning human perception with reality is accomplished by performing objective analysis on data relevant to the case at hand ( using the scientific method ).
  70. Define relevant information in the context of avalanche forecasting. Relevant information is that which contributes to the goal of aligning perception with reality, and it must contribute something to the analysis.
  71. There is a strong link between quantity of information and accuracy of decisions. True or False. False. Quantity of information is not related to accuracy. For example, a weather stations produces a large quantity of information, but much of that information is not relevant to forecasting problems at any spatial or temporal scale.
  72. There is a strong link between confidence in a decision and the resulting accuracy. True or False. False. Research shows that the link between confidence and accuracy is tenuous at best.
  73. Briefly discuss the role of redundant information in statistical predictions. Redundant information degrades the accuracy of predictions.
  74. List and describe each data classification used in operational avalanche forecasting. Operational avalanche forecasting uses data about the terrain, weather, and snowpack. Terrain = information about the interaction between terrain and synoptic scale weather events, but may include local variables such as orographic precipitation. Snowpack = information about the past and current snowpack that may be relevant to the next forecast. Weather = information about synoptic or meso scale weather patterns such as quantitative precipitation forecasts, local expectations about orographic/convective precipitation, and ambient air temperature.
  75. Discuss ensemble forecasts. An ensemble forecast is any forecast constructed from 2 or more people. These forecasts are usually more accurate than forecasts issued by a single person, and often serve as a hedge against the chaotic nature of the weather.
  76. Discuss the scale of failure in human perception with respect to avalanches. Failures in human perception with respect to avalanches run from the level of individual to the level of government and society. It is possible for a single individual to experience a serious perception failure and trigger an avalanche while skiing. On the other end of the scale, it is possible for an entire society to experience a serious perception failure and fail to allocate sufficient resources to avalanche forecasting, hazard mapping, and zoning.
  77. Define perception. Perception is a view of reality based on information processing by the senses.
  78. Discuss the two general components of human influences. Basic personality traits and behaviour ( risk propensity ) and individual perception and its effects on decision-making.
  79. What relationships does the Risk-Decision Matrix display? The Risk-Decision matrix displays the relationship between risk propensity, perception, and decision-making.
  80. Define Operational Risk Band [ ORB ]. The operational risk band is a framework defined by the upper and lower limits of risk. To avoid errors that result in either accidents or excessive conservatism, the results of all decisions should fall inside the operational risk band. This is an important component of formalized decision-making.
  81. What is the upper boundary of the ORB? The upper limit of the ORB is a Type I error, usually resulting in an accident.
  82. What is the lower boundary of the ORB? The lower limit of the ORB is a Type II error, usually resulting in lost opportunity or lost credibility.
  83. Provide a list of Type I errors. Reluctance to claim the snowpack is unstable unless hard proof is at hand.
  84. Provide a list of Type II errors. Failure to open an important transportation corridor.
  85. Define target risk. Target risk is the maximum risk an individual is willing to accept for a given reward. Target risk optimizes the difference between potential gains and potential losses. Behaviour modification is the typical method by which people seek to achieve target risk. For example, people might be willing to take a serious risk for a serious reward but usually are unwilling to take a serious risk for a small reward. Achieving target risk means that options are weighed based on the difference between risk and the reward across the series of options, with the option having the largest difference chosen most frequently. ( Relative to the individual and their risk propensity, which is of course, a complex subject by itself ). In the bigger picture, it is extremely important to understand how one's perception of risk and reward, influence decision-making. The ORB is a framework used to formalize decision-making with customizable upper and lower limits on risk. The upper and lower limits are set by an organization. ( Or an individual although most individuals probably do not consciously consider the ORB in their decision making process. )
  86. What are the consequences of Type I errors. Deaths, accidents, injuries.
  87. What are the consequences of Type II errors. Serious financial losses, lost opportunities, bruised egos.
  88. What is the relationship between uncertainty and perception? Variations in perception increase uncertainty. High levels of uncertainty degrade perception.
  89. Who coined the term risk homeostasis? Gerald Wilde.
  90. Explain risk homeostasis and provide an example. When safety devices are used, people modify their behaviour to maintain the same level of risk as before. When avalanche beacons are used, people choose to ski riskier terrain than they would ski without an avalanche beacon. Therefore the overall level of risk remains the same. The long and the short of this effect is that using a safety device will affect your decision-making and this awareness is a critical element of objective decision-making.
  91. List two or three items that improve perception. Targeted education and experience improve perception.
  92. List two or three items that degrade perception. Biases and lack of targeted education degrade perception.
  93. When might biases have a small effect on perception of instability? Biases have a small effect on perception of instability when instability is widespread and the triggering energy is low.
  94. When might biases have a large effect on perception of instability? Biases have a large effect on perception of instability when instability is not quite isolated and the triggering level is a bit higher than usual.
  95. Discuss absolute instability relative to perception. During times of absolute instability, most people, especially experienced people, agree that the snowpack is unstable. Therefore variations in perception are small.
  96. Discuss conditional instability relative to perception. During times of conditional instability ( the prevailing state ), people may or may not agree about the quantity or location of instability, nor about the required triggering energy. Therefore variations in perception are large.
  97. Write a brief explanation of the implications of perception of instability and the public danger scale. Perception of instability relative to the public danger scale clearly shows that many fatalities are linked to the Considerable danger level, which proves that perception during conditional instability is poorest ( or has the largest variations, depending on your perspective ).
  98. Draw the continuum of instability and describe perception at three points. Diagram Omitted.
  99. Why is the link between data sampling and perception so important? Data sampling is one of the most crucial inputs into any forecast. In fact, it is fair to say that data sampling forms the basis of forecasting, especially for backcountry travel. Therefore, if the data sampling is subject to bias, the forecast is not objective. For example, if a slopeside test reveals nothing about instability, it can be easy to conclude that instability is not present. However the choice of test location plays a critical role in the test results. This is a perfect example of how biased data sampling could lead to a disaster.
  100. What does White ( 1974 ) argue about perception of hazard? White argues that perception of hazard does not improve with the level of general education, i.e., high school graduates vs. college graduates.
  101. What is shown by statistics that compare fatalities to the public danger scale? Most accidents occur during Moderate or Considerable danger.
  102. Why is perception better for instability in new snow? Storm snow instabilities are found near the surface; this type of instability is much easier to find or detect through skiing. Storm snow instabilities are also subject to far less perceptual error than deep instabilities because biases strongly affect deep instabilities, especially when instability persists for a long time. ( i.e. Recency or Frequency. )
  103. Is randomness desired in the sampling process for avalanche forecasting? No.
  104. Why are slopeside instability tests sometimes compared to playing the lottery? The temporal and spatial variability of the snowpack, in addition to the danger of accessing real avalanche starting zones, often mean that the results of slopeside tests are, for all intents and purposes, random or chaotic ( like the lottery ). In addition, data sampling is subject to bias ( leading to serious perceptual errors ) that can add an element of Russian Roulette. In this case, not only might you "not win" any money, you also might suffer serious injury or loss of life.
  105. Describe the two main types of reasoning used in avalanche forecasting. 1. ) Inductive reasoning is intuitive and integrative; much more difficult to characterize than deductive reasoning. ( The inductive reasoning process differs from person-to-person. ) Inductive reasoning relies on a conclusion to establish a truth. 2.) Deductive reasoning relies on models, procedures, and data to arrive at a result. Deductive reasoning relies on a truth to reach a conclusion.
  106. Provide an example of each type of reasoning. 1.) Inductive. Looking a steep slope that has shed its snow after a storm and understanding why the slope is safe to ski. 2.) Deductive. Examining weather station data.
  107. Information for avalanche forecasting consists of two types. Explain each and include examples. 1.) Singular Information. Information relevant to the current situation and near future. 2.) Distributional Information. Information from the past or from similar situations in the past.
  108. Should one always have an opinion about instability before attempting risky activities in avalanche terrain? Yes.
  109. If avalanche forecasting is Bayesian, what information type constitutes the prior? Distributional data, or information about similar situations in the past. The previous forecast.
  110. If avalanche forecasting is Bayesian, what information type constitutes the likelihood? Singular data, or data about the current situation. The current forecast.
  111. If avalanche forecasting is Bayesian, what information type constitutes the posterior? The new forecast.
  112. Define informational entropy. Informational entropy refers to the level of uncertainty associated with any data. Relative to avalanche forecasting, both cracking in the snow cover and natural avalanche releases provide extremely reliable, i.e. low uncertainty, information about instability. On the other hand, a report of wind speed and direction is indirectly linked to instability. Understanding and linking concepts is required to convert high entropy data into low entropy data.
  113. Why are data such as wind speed and direct data harder to interpret than cracking of the snow cover? Cracking of snow cover is an obvious sign of instability; cracks mean that propagating shear fractures are occurring. Wind speed and direction is linked indirectly to instability, because there are many different interpretation of wind speed and direction values.
  114. Define highly correlated. Highly correlated means there is an indirect relationship between two elements in a system. This loosely coupled relationship means that a change to one element in the system may or may not result in a change to the other element in the system and/or the change may be difficult to predict or ascertain.
  115. What is necessary for dealing with highly correlated data? Generally speaking, resolving highly correlated data requires a thorough conceptual understanding of the systems and data involved in order to create a link between the systems, or to refine the data into a format relevant to the case at hand ( e.g., a report of wind speed and direction must be linked with a visual observation of wind-loaded snow ). This linkage can only formed if the observer understands the concepts of, and relationships between, distributional data ( wind speed and direction ) and singular data ( the case at hand, i.e. the visual observation of wind-loaded snow ). Even if wind-loaded snow is observed, it may be far away and still irrelevant to the case at hand.
  116. Does the class of information ( I, II, III ) always give the most priority to Class I information? Yes. Priority is given to Class I observations because this type of data reveals positive information ( highly prized ) about instability. Class II data only reveals the potential for instability and Class III data only reveals elements which might ( or might not ) contribute to instability.
  117. Describe the theory of weighting data. In general, any datum which reveals instability is considered more important than any datum that contains little or no information about instability, regardless of its class.
  118. Define spatial scale relative to avalanche forecasting. Avalanche forecasting operates at three primary spatial scales that refer to the geographic area of the forecast: synoptic scale, meso scale, and micro scale.
  119. Define temporal scale relative to avalanche forecasting. Avalanche forecasting operates along the temporal scale, including the distant past, recent past, the present, and the near future. Avalanche forecasting typically does not operate past the near future because of the chaotic nature of the data require ( i.e. the accuracy of long range weather forecasts is far from assured ).
  120. Define scale-matching. Scale matching involves resolving the scale of information to the scale of the forecast. For example, one should not rely solely on a synoptic scale forecast for decision-making at the micro scale. The synoptic forecast is important but cannot take precedence over information relevant to the current situation. If one observes natural avalanches or cracking in the snow cover, one can assume high instability regardless of the information contained in the synoptic scale forecast. Fundamentally, scale matching is necessary because information found at one scale cannot be simply applied to another scale. Seeing cracks in the snow cover at one location in the mountains does not mean the snow is unstable for 100 miles in every direction. Quantity, rate, and duration of snowfall is another good example. Most quantitative precipitation forecasts are issued at the synoptic or meso scale. At the micro scale ( very local ) one may find far less or far more snow than indicated by a synoptic scale forecast.
  121. Provide an example of what might happen if scale-matching is not performed. Despite local signs of instability, a backcountry traveler might rely on a synoptic scale forecast and decide to ski an unstable slope. This could result in an avalanche. This is a good example of the link between the dynamic, evolutionary nature of avalanche forecasting and the use of singular and distributional information. The synoptic scale forecast constitutes distributional information; local signs of instability constitute singular information relevant to the case at hand.
  122. Explain the three primary spatial scales. 1.) Synoptic. This is the largest scale: 1000 square kilometers. 2.) Meso. This is the middle scale: 100 square kilometers. 2.) Micro. This is the smallest scale: 1 square kilometer.
  123. Difficulty of forecasting is inversely proportional to scale. True or False. True.
  124. If true, explain. If false, explain. As the scale decreases, difficulty of forecasting increases and the need for accurate information relevant to the case at hand increases as well.
  125. Does failure to perform scale-matching result in many needless accidents? Yes.
  126. Define nowcast. A nowcast is a forecast of instability for the present moment.
  127. Which is more difficult: forecasting stability for next Wednesday or next Thursday? It is more difficult to forecast instability for next Thursday than for next Wednesday.
  128. Why does chaos influence avalanche forecasting? Weather is strongly linked to avalanche formation. The ability to successfully forecast avalanches is strongly influence by the essentially chaotic nature of weather.
  129. Discuss "search for supportive evidence" and how to neutralize this bias. The search for supportive evidence is expressed as a willingness to gather facts that support the desired conclusion while disregarding facts that support an alternate, or undesired, conclusion. To prevent this bias, always search for information that reveals instability.
  130. Discuss "inconsistency" and how to neutralize this bias. Inconsistency is expressed by applying different sets of decision-making criteria to similar situations. One might use the presence of existing ski tracks to justify the decision to descend a steep slope. In this case, the decision is based solely upon the existence of ski tracks, when without the presence of ski tracks one might use an entirely different set of criteria to evaluate instability.
  131. Discuss "conservatism" and how to neutralize this bias. Conservatism is expressed by failure to change one's mind when new information or evidence becomes available. This can affect evaluation of instability in either direction, and of course, this is linked directly to decision-making. Keep an open mind and use a formalized decision-making process to neutralize this bias.
  132. Discuss "recency" and how to neutralize this bias. Recency is expressed by allowing events from the most recent past to dominate decision-making at the expense of events in the less-recent past. Consider the current situation ( singular ) and past situations ( distributional ) when making-decisions. This bias is very important when instability persists for a long time.
  133. Discuss "frequency" and how to neutralize this bias. Frequency is expressed by allowing very frequent events to dominate decision making at the expense of less-frequent events. Consider the current situation ( singular ) and past situations ( distributional ) when making-decisions.
  134. Discuss "availability" and how to neutralize this bias. Availability is expressed when decision-making is dominated by specific events easily recalled from memory at the expense of information relevant to the case at hand.
  135. Discuss "illusory correlations" and how to neutralize this bias. Illusory correlations is expressed a link is "seen" between data when no such link exists. Deductive reasoning is strongly affected by this bias.
  136. Discuss "selective perception" and how to neutralize this bias. Selective perception is expressed by viewing a problem in the context of one's own background and experience. Allow everyone to have input, especially people with different backgrounds.
  137. Discuss "expert halo" and how to neutralize this bias. Expert halo is expressed by allowing one person's expertise ( real or perceived ) to dominate decision-making. Everyone in the group ( skiers, forecasters ) should contribute to the decision.
  138. Discuss "underestimating uncertainty" and how to neutralize this bias. Underestimating uncertainty ( denial ) is a method of coping with anxiety, especially when the outcome is time-pressured or may have a serious outcome. Consider distributional and singular information inside a formalized decision-making process to neutralize this bias.
  139. Discuss "excessive optimism" and how to neutralize this bias. Excessive optimism is expressed by denial. Seek the opinion of a disinterested third party to neutralize this bias.
  140. Discuss "anchoring" and how to neutralize this bias. Anchoring is expressed when initial information is given more weight in the forecasting process than new information. During a ski tour, signs of instability might not be present. However if signs of instability appear, it is possible to try and extrapolate to the best case scenario, i.e., instability is isolated in this location only. While this might be true, it is important to remember that "might" is the operational word.
  141. Discuss "rules of thumb" and how to neutralize this bias. A rule of thumb is expressed by a rule that greatly oversimplifies the problem. Consistency ( staticity ) in a situation is required for a rule of thumb to work properly and avalanche forecasting considers a variety of very specific, and dynamic, situations. Using a rule of thumb almost guarantees that one will overlook important information and this will have a negative effect on the decision-making process.
  142. Discuss "guide-client relationship" and how to neutralize this bias. Clients sometimes pressure guides to travel over terrain that is too dangerous. An inexperienced client should not be allowed to override the instability assessment of an experienced guide.
  143. Discuss "social proof" and how to neutralize this bias. Social proof is expressed by seeing other people doing something without consequences and believing that one can do the same thing without consequences. Formalize the decision-making process.
  144. Explain asymmetry of use relative to classes of information. Asymmetry of use refers to the process of discarding irrelevant information regardless of its class of origin. This concept is also related to the concepts of Bayesian revision: a report of an avalanche is an indicator of instability regardless of information available from other classes.
  145. Why does sampling performed on "average areas" lead to dangerous conclusions? Sampling performed on "average areas" lead to dangerous conclusions because data sampling forms much of the basis for perception of instability. Avalanches do not form under average conditions in average areas. Therefore sampling conducted in average areas misses instability required for avalanche formation and leads to "false stable" perception.
  146. Explain Class I Factors. Class I factors deals with the direct relationship between loads and weak layers. Examples of Class I data are avalanches, cracking in the snow cover, fracture propagation, and instability tests with positive results. These data reveal current instability.
  147. Explain Class II Factors. Class II factors deal with the structure, strength, and energy of the snowpack. Examples of Class II data are the snowpack structure ( stratigraphy ), crystal forms, layering, depth, density, temperature, hardness, and the results of instability tests that do not necessarily reveal information about instability. These data reveal current and future instability.
  148. Explain Class III Factors. Class III factors deal with meteorological phenomena that create the snowpack. Examples of Class III data are wind speed/direction, precipitation rate, precipitation intensity, snow/water equivalence, radiation balance, and humidity. These data may reveal current and future instability.
  149. Abundance of information is needed to ________ ________ ________. compensate for uncertainty.
  150. List at least four factors that contribute to uncertainty. 1. ) Incremental changes to the snowcover. 2. )Variations across space and time. 3. ) Human perception. 4. )Many observations are not conducted in avalanche starting zones. 5. ) No single factor provides the complete answer. 6. ) Incomplete knowledge about how individual factors relate to instability.
  151. What is needed with high uncertainty? Greater uncertainty requires larger amounts of relevant information or conservative decisions, or both.
  152. Why is screening Class III data especially important? Class III data is often collected from weather stations: too much information is available and most of the data is not relevant with respect to instability during periods when instability is not rapidly changing.
  153. Which observations have priority? Observations that reveal direct information about instability have first priority. Observations that reveal information about the snowpack have second priority. Observations about highly correlated data, such as weather, receive third priority. However, the analyst must work with the data available—which may not include Class I or Class II data for a specific area.
  154. List one very reliable indicator of unstable snow. Natural avalanches.
  155. Define indicator slope. An indicator slope is the first slope in a region where avalanches occur when unstable snow develops.
  156. Discuss the benefits and drawbacks of using indicator slopes to evaluate instability. Indicator slopes may provide an early warning that unstable snow is present. You can go visit an indicator slope with relative ease. It is not possible to identify indicator slopes and the information is not always reliable. It is important know the history and reliability of avalanche formation for a given slope before using the slope as an indicator.
  157. What is indicated by avalanche activity on indicator slopes? Avalanche activity on indicator slopes shows that unstable snow has developed.
  158. Provide a basic procedure for collecting data about avalanche occurrences. Move around and be observant. Avalanches, or signs of recent avalanching, are very easy to observe.
  159. Discuss the benefits and drawbacks of using devices to monitor avalanche activity. Using devices to record avalanche occurrences is useful because avalanches are reported immediately. Unlike humans, devices may be placed in harm's way without unnecessary worry. On the other hand, devices are often unreliable and have a high rate of false positives.
  160. Why keep records of avalanche activity? Records of avalanche activity are useful for identify slopes on which avalanches occur, determining frequency of avalanching, size of avalanching, and for maintaining a larger picture of instability throughout a season ( or several seasons ). Over the long term, avalanche records help land-use planners and avalanche professionals plan and implement protective structures. Backcountry recreationists may be able to travel more safely if they know whether or not a specific avalanche path has run, or if they have access to records that note the type of conditions in which the path does run, or the frequency of large events.
  161. Define fracture propagation. Fracture propagation is indicated by the sudden subsidence of the snowpack that occurs when a shear fracture propagates through a weak layer. The subsidence is often accompanied by an audible "whumpf" as air is displaced by the upper layer of snow. Cracks, indicating propagation of tension fractures, may form in the snow cover. It is possible for a thin, weak layer to fracture without subsidence, whumpfing, or cracking in the snow cover.
  162. What causes fracture propagation? Fracture propagation is caused by shear fractures that travel outward from the point of disturbance, or by widespread crushing of weak layers below the surface of the snow.
  163. Is fracture propagation the same as settling? No. Fracture propagation IS NOT the same as settlement.
  164. When might fracture propagation occur on a low-angle slope? Fracture propagation occurs on a low-angle slope when thick layers of the persistent forms are present below the snow surface. Surface hoar is a good example.
  165. Is subsidence of the snowpack always noticeable when a fracture propagates? No.
  166. Does fracture propagation help reduce uncertainty? Yes.
  167. Define crack propagation. Crack propagation occurs when initial shear fractures lead to subsidence of the snowpack. The subsidence of the snowpack leads to tensile cracks in the snow.
  168. Does crack propagation help reduce uncertainty? Yes.
  169. Define instability test. An instability test is a systematic method of applying force to the snow cover.
  170. What is the purpose of an instability test? Instability tests are used to determine whether or not the snowpack will fracture and whether or not the fracture will propagate. If the snowpack fractures, these tests are often used to determine the amount of force required to induce failure.
  171. An instability test provides what information? Be specific. Depth of fracture, ease of fracture, and an index of shear strength.
  172. What do the results of an instability test tell you about the snowpack in the surrounding area? Nothing.
  173. Instability tests serve as Class I information if instability is revealed. True or False. True.
  174. If true, explain. If false, explain. Class I information is any information that is directly related to avalanche formation. An instability test may yield such information if the test indicates clean shears that release with high energy, or if such a test reveals high propagation propensity
  175. Why might an instability test fail to reveal instability? Poor test location.
  176. What is the generally accepted minimum slope angle for an instability test? 30 degrees.
  177. Does the size of the test area affect the results? Explain. Yes, the size of the test area affects the results. Tests, such as Rutschblock or explosives, can test a large area of the snowpack. The results of these tests are considered much more reliable than tests that sample a very small area because uncertainty decreases as areal sample size increases.
  178. Explosives test the largest area of the snowpack. True or False. True.
  179. Which is better: a single, detailed test or many tests with less detail? Many test with less detail.
  180. Explain your answer to the previous question. A single, detailed test does not account for variations across space and time in the snow cover. Therefore a single test, no matter how detailed, cannot reduce uncertainty as much as many simple tests. Statistically speaking, a single test has the highest possible potential for error ( 100% ).
  181. Define test skiing. Test skiing involves skiing a slope, jumping, and kicking in order to apply force to the snowpack.
  182. Where does test skiing usually take place? Test skiing usually takes place on short, steep slopes where the consequences of an avalanche are very small.
  183. When is test skiing avoided? Test skiing is avoided when the consequences, such as a large avalanche, are high, or when an instability is suspected deep in the snowpack.
  184. Define ski stabilization. Ski stabilization is the intentional release of small avalanches and the breaking up of weak layers in the surrounding snow.
  185. What is another term for ski stabilization? Ski cutting.
  186. List general guidelines for test skiing? 1. ) Use a spotter who remains in a safe location. 2. ) Approach the slope from the top. 3. ) First attempt to start an avalanche at the transition zone. 4. ) Ski diagonally to a safe location. 5. ) Descend the rest of the slope without stopping. 6. ) Use a secure, roped belay for high consequence terrain or if you suspect deep instabilities.
  187. What does avalanche release by explosives indicate about instability? Avalanche release by explosives indicates fair to poor stability.
  188. How to you perform a Rutschblock test? 1. ) Select an appropriate test location. 2. ) Isolate a 2.0m × 1.5m block of snow. ( Two meters is the cross-slope dimension. ) 3. ) Depth must be sufficient to include the weak layers but not deeper than 1-2 meters. 4. ) Load the block until failure. 5. ) Note failure depth, layer/interface, and fracture characteristics.
  189. List and define the load levels for Rutschblock test. 1. Failure under the weight of the block without any additional load. 2. One person, wearing skis, steps onto the block. 3. The person performs a quick bend at the knees and returns to the standing position. 4. The person jumps. 5. The person jumps a second time. 6. A person, without skis, jumps onto the block. 7. No failure observed.
  190. What is the principle difficulty with a Rutschblock test? Selecting an appropriate site ( steepness, safety, representative of starting zones ) is the principle difficulty with a Rutschblock test.
  191. Is the Rutschblock test reliable for weak layers deeper than 1 meter? The Rutschblock test is not reliable for weak layers deeper than 1 meter and the test may not yield information on soft slabs at failure level 6.
  192. How do you perform a compression test? 1. ) Select an appropriate test location. 2. ) Isolate a 30cm × 30cm block of snow. 3. ) Depth must be sufficient to include the weak layers but not deeper than 1-1.2 meters. 4. ) Place a shovel on the top of the snow. 5. ) Tap, with finger tips, up to ten times while moving the wrist ( Stop if failure occurs ). 6. ) Tap, with finger tips, up to ten times while moving the elbow. ( Stop if failure occurs ). 7. ) Tap, with palm or closed fist, up to ten times while moving the shoulder ( Stop if failure occurs ).
  193. List and define the load levels for compression test. Very easy. Fails during cutting. Easy. Fails before 10 taps from wrist. Moderate. Fails before 10 taps from elbow. Hard. Fails before 10 taps from shoulder.No failure. Does not fail during testing.
  194. What is the principle difficulty with the compression test? The principle difficulty with the compression test is results that depend on the hardness of the entire column relative to the depth of the weak layer. The compression test finds many weaknesses that are of little importance. Last, the amount of force applied through tapping varies between individuals and in the same individual over multiple tests.
  195. Is the compression test reliable for weak layers deeper than 1 meter? No.
  196. Explain why or why not. When deeper than 1 or 1.2 meters, the isolated column of snow is subject to bending forces that cause the entire block to fail during testing. Such failures are not indicative of failure in a weak layer and do not reveal information about instability.
  197. How do you perform an extended column test? 1. ) Select an appropriate test location. 2. ) Isolate a 30cm × 90cm block of snow. ( 90cm is the cross-slope dimension. ) 3. ) Depth must be sufficient to include the weak layers but not deeper than 1-1.2 meters. 4. ) Place a shovel on the top of the snow at the left or right side of the block. 5. ) Tap, with finger tips, up to ten times while moving the wrist ( or until propagation occurs ). 6. ) Tap, with finger tips, up to ten times while moving the elbow. ( or until propagation occurs ). 7. ) Tap, with palm or closed fist, up to ten times while moving the shoulder ( or propagation failure occurs ). 8. ) Note number of steps required to induce failure, failure depth, layer/interface, fracture characteristics, and whether or not the failure propagates from one side of the block to the other.
  198. List and define the test results for the extended column test. ECTP. The failure propagates from one side of the block to the other. ECTN. The failure does not propagate from one side of the block to the other.
  199. Discuss false positives relative to the extended column test. The extended column test results in more false unstable results and fewer false stable results than the compression test.
  200. Is the extended column test reliable for weak layers deeper than 1 meter? No.
  201. Explain why or why not. Like the compression test, the column of snow isolated for this test is subject to bending forces that may result in premature breaking of the column. Such breaks do not reveal information about instability.
  202. When are results of instability tests regarded as Class I information? The results of instability tests are regarded as Class I information when the results reveal instability in the snowpack. All other test results are inconclusive.
  203. Discuss fracture character. Fracture character describes the surficial qualities ( smoothness ) of the shear plane and the amount of energy observed during the release of the test block. Energy may be expressed as the "ease" or "suddenness" with which the test block releases.
  204. The shear quality scale is a measure of what data quality? Propagation propensity.
  205. Explain each level of shear quality. Q1. Sudden. Fast block motion on a smooth, planar surface. Q2. Resistant. Slower block motion on a mostly smooth, planar surface. Q3. Break. Slow block motion ( if any ) on a rough, non-planar surface.
  206. Relative to the state of snowpack instability, what are three possible outcomes of a past avalanche? Past avalanches can: 1. ) Remove snow and weak layers, 2. ) Leave shallow snow that is subject to strong temperature gradients, allowing additional weaknesses to develop, 3. ) Small avalanches can overload snow further down the track and increase instability, and 4. )A smooth, polished bed surface can remain. Subsequent loading may result in higher velocity avalanches that run further and cause more damage.
  207. Why monitor snowpack depth? Observers monitor snowpack depth to determine if there is enough snow for avalanche formation.
  208. What is a basic requirement for avalanches? There must be enough snow to cover rough ground surface features such as rocks, brushes, tree trunks, and shrubs.
  209. Describe a typical scenario for avalanche formation early in the season. Early season avalanches have enough snow in the starting zone but not enough snow in the track. These avalanches don't run very far.
  210. How do you measure shallow snow? With a metal ruler.
  211. How do you measure deep snow? With a metal probe.
  212. What is threshold snow depth? Threshold snow depth is the minimum depth needed for avalanche formation on a given slope. Typically the ground surface features must be covered before avalanche formation is possible. Steepness of the track is another variable that has important influence.
  213. Slopes disturbed by human activity contain snow different from most backcountry slopes. True or False. True.
  214. Define surface penetrability? Surface penetrability is the depth to which a variety of instruments can penetrate the snowcover without assistance. Common measures include ski, boot, and ski pole.
  215. Why evaluate surface penetrability? To determine if the snow is unstable.
  216. What is indicated by deep ski penetration? Surface penetrability reveals the following information, 1. ) How much snow is available for wind transport, 2. ) How much snow has been transported by the wind, 3. )Snow depths across a wide area, 4. ) Whether or not the snow is suitable for soft slab formation, 5. ) How much snow is available for avalanches.
  217. What is indicated by lower-than-average ski penetration? Crusts at, or near, the snow surface.
  218. Relative to instability, discuss the positive and negative aspects of increases in temperature? 1. ) Positive: Moderate temperatures promote round form development in the snowpack, 2. ) Positive: Densification and bond formation occur more rapidly with moderate temperatures, 3. ) Positive: Persistence of instability is shorter, 4. ) Negative: Rate of creep may increase, causing an increase in shear stresses, 5. ) Negative: Water may infiltrate the snowpack, causing loss of cohesion, 6. ) Negative: Soft slabs form quickly and may release on weaknesses in new snow or at the interface between new/old snow.
  219. Relative to instability, discuss the positive and negative aspects of decreases in temperature? 1. ) Positive: Stiffness increases lead to better bridging and decrease force transfer from surface to weak layers, 2. )Positive: Inhibits soft slab formation, 3. ) Negative: Fractures propagate long distances in brittle snow, 4. )Negative: Recrystallization under a strong temperature gradient produces faceted crystals.
  220. What is the relationship between temperature and fracture toughness of the weak layer? Moderate temperatures increase fracture toughness in the weak layer by promoting sintering and rounding.
  221. What is the observation technique for measuring snow temperature? Insert a thermometer or thermistor probe into a shaded section of snow ( such as the inside of the snowpit ).
  222. How do you calibrate a thermometer? Submerge the thermometer into ice water ( 0° Celsius ) and check the reading. Account for any errors when measuring snow temperature.
  223. Provide four general examples of snow-temperature influence for the following ranges: <5° C, -1° to -5° C, -1° to 0° C, isothermal. Snow-temperature influence for the following ranges is as follows: 1. ) <5° C. Bond formation is slow and weaknesses persist for a long time, 2. ) -1° to -5° C. In the absence of a large temperature gradient, rounding and sintering is rapid, strength gains are rapid, 3. ) -1° to 0° C. The snow is in a delicate balance: rounding and sintering occur but the absolute strength may be low if liquid water is present, 4. ) Isothermal. The snowpack is slowly melting. Full-depth avalanches may occur.
  224. What is the major difficulty in evaluating wet-snow stability? 
  225. What measurement can accurately predict a full-depth avalanche? Acoustic readings.
  226. What are six important questions for evaluating snowpack structure? 1. ) Are weak layers and interfaces present? Are weak layers absolutely weak, as exhibited by low hand-hardness, or are these layers weak relative to other layers? 2. ) What is the strength of the weak layers and interfaces? 3. ) What is the depth of the weak layers and what is the weight of the load on the weak layers? 4. ) How strong are the slabs above the weak layers? 5. ) How are the slabs and weaknesses distributed across the terrain? 6. ) What is the shear-quality or fracture propagation potential?
  227. Define full snow profile. A full snow profile is a formal procedure used to study the entire depth of the seasonal snowpack. This includes stratigraphy, weaknesses, temperatures, and loads on layers. Snow profiles are useful for maintaining climate records as well.
  228. What is the purpose of a test profile? A test profile is used to identify weaknesses in the surface snow ( from surface to about 1.5 meters ).
  229. The primary advantage of a test profile, compared to a full study, is increased number of observations. True or False. True.
  230. Describe the type of information typically sought by a test profile? A test profile is used to find weak layers and perform quantitative analysis ( slopeside tests ) that follows standard procedures.
  231. A single detailed profile is more valuable than many quick profiles? True or False. True.
  232. List several criteria for choosing the site of a test profile? Consider performing a test profile when you find weak snow ( probing ) or a safe slope of at least 30° that has snow conditions relevant to the slope you wish to evaluate ( similar aspect and elevation ). The slope should be undisturbed and at least 5 meters from any tree branches.
  233. How do you weigh the information gained from a test profile? Information gained from a test profile is weighed according to its relevance. Information that reveals instability is most relevant ( Class I data ). All other information is either inconclusive or Class II.
  234. What Class I information can be learned from a test profile? Shear quality and fracture character.
  235. What Class II information can be learned from a test profile? Location of weak layers/interfaces, depth, grain type, hardness, and some numeric indicies such as the number of taps required to induce failure. It is important to remember that these numeric results are Class II data because they do not reveal instability.
  236. Provide the correct sequence of events for evaluating instability at a test profile. 1. ) Perform instability tests and record results. 2. ) Note fracture character and shear quality. 3. ) Examine crystal grain types in weak layers or around interfaces. 4. ) Estimate relative strength differences between weak layers and adjacent layers.
  237. Discuss the correct procedure for probing the snowpack with a ski pole or probe? Insert the pole at a right angle to the snow surface ( normal to the slope ). Push the pole into the snow and observe the resistance. Scrape the sides of the hole while removing the pole to check for weak snow or thin, weak layers.
  238. What is the most important observation with respect to the snowpack? The presence of weak layers and interfaces is the most important observation with respect to the snowpack. It is important to consider these failure planes in the context of the surrounding snow.
  239. What are the five key observations used to estimate shear strength of weak layers and interfaces? 1. )Hardness, 2. ) Size and shape of grain, 3. ) Bond of grains, 4. ) Free water content, 5. ) Density
  240. Describe each observation. 1. ) Hardness. The hardness of a layer usually indicates its shear strength ( and fracture toughness ). When testing hardness, the weak layer is often very soft and the surrounding slab may be quite hard, relatively speaking. 2. ) Size and shape of grain. Strong snow is composed of small, round grains, with many bonds per unit volume. Weak snow is usually composed of small, angular grains with fewer bonds per unit volume. ( This is the critical difference found in hardness tests. ) 3. )Bond of grains. The bonding between the grains, or between the grains in different layers, is more important than grain size. Bonding quality can be evaluated by observing the amount of effort required to disaggregate snow grains in the layer. 4. ) Free water content. While evaluating the strength of wet snow is a complex subject, wet snow is often quite weak. However fracture propagation potential decreases in wet snow. 5. ) Density. Strength usually increases with density but hardness is a better indicator of strength. Density is often used to calculate the load on a weak layer.
  241. Discuss surface condition relative to bonding of new snow. The condition of the existing snow surface has a lot of influence on bond formation between the existing surface and new snow. The two primary elements are roughness and physical characteristics such as temperature, crystal grain type, and hardness.
  242. Bonding over rough surfaces is usually ________. Good.
  243. Bonding over smooth surfaces is usually ________. Poor.
  244. What is a temperature mismatch? A temperature mismatch is a significant difference between the temperature of the existing snow and the temperature of new snow.
  245. List three qualities that promote bond formation. Warm, rough, soft.
  246. List three qualities that limit bond formation. Cold, smooth, hard.
  247. Provide three examples of snow types for which poor bond formation is expected. Poor bonding is expected when surface snow is composed of ice crusts, faceted grains, surface hoar, graupel, needles, plates, and machine/ski packed snow.
  248. Define snow water equivalent. Snow water equivalent is the amount of water contained in new precipitation. 10cm of new snow might have 1mm water equivalent or 5mm water equivalent. Obviously, 10cm of snow with 5mm water is much heavier than 10cm of new snow with 1mm of water.
  249. Provide the equation for determining snow water equivalence. Water Equivalent in millimeters is: snow depth ( mm ) × density of new snow ( kilograms per cubic meter ) / density of water ( 1000 kilograms per cubic meter ).
  250. Why is density of snow useful in forecasting avalanches? Density of snow is used to calculate the load on weak layers.
  251. What is the range of optimal densities for slab avalanche formation? 100-250 kilograms per cubic meter.
  252. Which is more important: rate of precipitation or water equivalance? Water equivalence.
  253. Explain the answer to the previous question. Rate of precipitation is often redundant; avalanches are expected with intense snowfall.
  254. Discuss the relationship between precipitation intensity, rate of precipitation, and shear stress. First a few definitions: Precipitation intensity is the rate of snowfall per hour. Rate of precipitation is the water equivalence per hour. Shear stress is the amount of force being applied to the weak layer at any given moment. There is of course a relationship between intense snowfall and avalanche formation. However the rate of precipitation provides important information about how quickly a specific load is applied to the existing snowpack.
  255. Why are rules of thumb with respect to rate and intensity of precipitation often of little use? These rules of thumb overlook important factors such as temperature, wind, and the existing snowpack stratigraphy.
  256. Relative to the manner in which snow fails, why is precipitation intensity important? Snow is rate sensitive with respect to fracture initiation and propagation. The rate at which the new load is applied to the existing snowpack must exceed the critical threshold required to induce mechanical failure in the weak layer or interface.
  257. Define settlement. Settlement is the percentage decrease in the height of new snow as densification proceeds.
  258. How is settlement related to strength increases? Settlement increases the hardness of snow.
  259. Why do high rates of settlement sometimes imply increased chance of avalanching? High rates of settlement indicate lots of new snow. Lots of new snow is usually associated with avalanche formation. In addition, high rates of settlement may indicate soft slab formation.
  260. Provide the equation for determining settlement. The equation for determining settlement of new snow is as follows: ( ( sum of new snow depths ) - ( storm snow depth ) / sum of new snow depths ) × 100
  261. What is the threshold speed for wind transport ( dry snow )? 7 meters per second.
  262. At what speed is snow most efficiently transported into avalanche starting zones? 10-25 meters per second.
  263. What happens to snow when wind speeds are greater than 25m/second? At very high speeds, wind transports snow away from avalanche starting zones and some snow is lost due to evaporation. In any case, the analyst should be careful to examine snow lower on the slopes.
  264. What wind variable determines the aspects that are most favorable for avalanching? Wind direction.
  265. Are direct observations of localized wind characteristics observable at the synoptic scale? No.
  266. Information about the direction and speed of are usually acquired by what equipment? Wind vanes and anenometers.
  267. How can you observe wind characteristics without relying on equipment? Watch for snow blowing from ridges and look for cornices.
  268. Good snow stability analysts watch for signs of drifting while driving. True or False. True.
  269. Ripples on the snow surface run ________ to the wind. Perpendicular.
  270. Sastrugi point in the ________ of the wind. Direction.
  271. Cornices face ________. Downwind.
  272. Scour holes appear on the ________ side of trees, rocks, and posts. Windward.
  273. Why is the relationship between blowing snow and avalanche formation hard to quantify? It is extremely difficult to measure/quantify/geo-correlate blowing snow.
  274. Air temperature influences which aspects of instability? The air temperature determines the temperature at which new snow is deposited. Cold temperatures slow bond formation and allow weaknesses to persist. Warm temperatures promote bond formation, densification, and other factors related to strength increases.
  275. Temperature trends during storms are important. True or False. True.
  276. Rising air temperatures during a storm have what effect? Rising air temperatures produce an upside down snowpack. This occurs when low density snow ( light ) is covered by higher density snow ( heavy ). An upside down snowpack is a classic recipe for instability.
  277. Avalanching sometimes starts immediately when air temperature reaches 0°. True or False. True, but sometimes there is a short delay.
  278. Prolonged warming often induces what type of avalanche? Deep, wet slabs.
  279. Why are these avalanches difficult to forecast? Release often depends on the complex interaction between snow, water, and the sliding layer. In this case, the snowpack essentially builds its own weak layer and the processes involved are hard to measure.
  280. List two or three instruments used to measure air temperature. Glass, metal, or thermistor thermometers.
  281. What is the relationship between high humidity and wind-transported snow? High humidity is thought to increase the cohesiveness of new snow.
  282. List another affect of high humidity related to wind-transported snow. Snow travels further before sublimating. High humidity is essential for surface hoar formation.
  283. What is the dominant influence on snow temperatures in the spring? Solar radiation.
  284. Is there a lapse between solar radiation input and free water production inside the snowpack? Yes, there is a lapse. This should be considered carefully when forecasting or when choosing terrain.
  285. Discuss radiation relative to dense cloud cover. Radiation is generally not an issue with thick cloud cover becaue the clouds prevent a lot of light from reaching the snow surface ( reflection ).
  286. Discuss radiation relative to thin cloud cover. Thin clouds create a greenhouse effect by allowing a lot of light to reach the snow surface while simultaneously re-radiating long wave radiation back into the snow cover.
  287. The snow in cirques and gullies receives more heat than open slopes. True or False. True.
  288. Please explain the answer to the previous question. Gullies and cirques are similar to parabolic surfaces that re-reflect a lot of the radiation back onto the snow surface. On the other hand, a convex form actually diffuses the radiation.
  289. Discuss the character of Class I, Class II, and Class III factors. 1. ) Class I. These are events that must be observed in the field. Data of this class are non-numeric and non-symbolic. These observations have the lowest number of interpretations and provide direct evidence of instability. 2. ) Class II. These are events, numeric, and symbolic data. Typically, these observations are made in the field by observing the interior of the snowpack. These observations provide information about the location of weak layers and interfaces in the snowpack that may or may not allow the observer to determine if the snowpack is suitable for avalanche formation. This is because the relationship between these factors and avalanche formation is not always direct. These observations can constitute Class I information IF direct information about instability is revealed. 3. ) Class III. There are numeric data. Typically these observations are made by machines. Since these data have many possible interpretations, it is difficult to know the relationship between avalanche formation and this data ( except during times of absolute instability ).
  290. In what order are these factors observed to produce a synoptic scale forecast? Class I, Class II, Class III
  291. In what order are these factors observed to produce a micro scale forecast? Class III, Class II, Class I
  292. Which forecast type is of the most interest to backcountry users? Micro-scale.
  293. Explain your answer to the previous question. A synoptic scale forecast applies to a very large area. This does not include information about a specific slope. A backcountry travelers needs to forecast instability for a specific slope at a specific time.
  294. Briefly describe conventional avalanche forecasting. Conventional avalanche forecasting requires data and a human forecaster. The human forecaster considers the data and relies on a combination of deductive and inductive logic to produce a forecast. This method of forecasting is very difficult to describe and the process used is unique to each individual.
  295. 80% of avalanche fatalities occur during what general activity? Backcountry recreation.
  296. Forecasting and hazard evaluation are only part of the picture. True or False. True.
  297. What is the major difference between "office-based" avalanche forecasting and backcountry avalanche forecasting? The scale for which the forecast is issued. Therefore, specific terrain considered very carefully during backcountry forecasting ( and specific terrain is not considered at all for synoptic or meso-scale forecasts ).
  298. What is a stability rating? A stability rating considers the probability of avalanche formation.
  299. What is a hazard rating? A hazard rating includes the consequences to people or facilities as a result of avalanches.
  300. Which is more useful during backcountry travel, a hazard rating or stability rating? A stability rating is more useful than a hazard rating for backcountry travelers concerned with individual slopes.
  301. Explain your answer to the previous question. Writing a hazard rating is complicated because it must consider exposure of people or facilities across time and space. With respect to avalanches, this must consider the maximum events ( with large return periods ).
  302. Low. Natural slab avalanches highly unlikely; human-triggered avalanches unlikely.
  303. Moderate. Natural slab avalanches unlikely; human-triggered avalanches possible.
  304. Considerable. Natural slab avalanches possible; human-triggered avalanches probable.
  305. High. Natural and human-triggered avalanches likely.
  306. Extreme. Natural and human-triggered avalanches certain.
  307. Very Good Stability. The snowpack is stable. No natural avalanches expected. Very heavy loads could trigger avalanches. Minimal results from instability tests.
  308. Good Stability. The snowpack is mostly stable. No natural avalanches expected. Heavy loads could trigger avalanches. Moderate to hard results from instability tests.
  309. Fair Stability. Snowpack stability varies considerably with terrain, often resulting in locally unstable areas. Isolated natural avalanches expected on specific terrain features. Avalanches may be triggered with light loads on specific terrain features or terrain features with specific snowpack characteristics. Generally easy to moderate results from instability tests.
  310. Poor Stability. The snowpack is mostly unstable. Natural avalanches are expected in areas with specific terrain features or terrain features with certain snowpack characteristics. Generally easy results from instability tests.
  311. Very Poor Stability. { Write the appropriate description. }

A = 277 points
B = 245 points
C = 214 points
D = 185 points
F = Less than 185 points

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