Karl W. Birkeland

Snow Avalanche Climatology of the Western United States Mountain Ranges

Abstract The snow avalanche climate of the western United States has long been suspected to consist of three main climate zones that relate with different avalanche characteristics: coastal, intermountain, and continental. The coastal zone of the Pacific mountain ranges is characterized by abundant snowfall, higher snow densities, and higher temperatures. The continental zone of the Colorado Rockies is characterized by lower temperatures, lower snowfall, lower snow densities, higher snow temperature gradients, and a more persistently unstable snowpack resulting from depth hoar. The intermountain zone of Utah, Montana, and Idaho is intermediate between the other two zones. A quantitative analysis of snow avalanche climate of the region was conducted based on Westwide Avalanche Network data from 1969 to 1995. A binary avalanche climate classification, based on well–known thresholds and ranges of snowpack and climatic variables, illustrates the broadscale climatology of the three major zones, some spatially ...

The spatial variability of snow resistance on potential avalanche slopes

Since snow avalanches are believed to release from zones of localized weakness, knowledge of snow-strength patterns is important for determining slope stability and for applying effective avalanche-control measures. In this study, the spatial variability of snow resistance (an index of snow strength) and depth were measured and compared with terrain features on two inclined slopes. A refined instrument allowed the strength of an entire snow slab to be characterized in a short time. The spatial pattern of trees appeared to affect the pattern of snow depth at one site, where a significant linear relationship was found between snow depth and average snow resistance. These results suggest that localized snow-depth variations may be important in snow-strength genesis. Although a linear relationship existed at that site, additional factors may be critically relevant. A second site with more complex terrain features and less localized wind drifting did not show a linear relationship between depth and average resistance. Instead, complex patterns of resistance demonstrated that many factors contribute to snow resistance. In particular, the snow overlying rocks was found to have significantly weaker resistance than that in adjacent areas not over rocks

Spatial patterns of snow stability throughout a small mountain range

This research investigates snow stability on the eastern side of a small mountain range in southwest Montana, U.S.A., on one mid-season day and one late-season day during the 1996/97 winter. Although previous research has addressed snow stability at smaller spatial scales, this is the first field-based study to investigate snow stability (as measured by stability tests) over a mountain range in order to better understand its spatial distribution and the implications for predicting dry-slab avalanches. Using helicopter access, six two-person sampling teams collected data from over 70 sites on each of the two sampling days. Variables for terrain, snowpack, snow strength and snow stability were generated from the field data, and analyzed using descriptive statistics, correlation analysis and multiple regression. Results from the first sampling day show stability is only weakly linked to terrain, snowpack and snow-strength variables due to consistently stormy weather conditions leading up to that day. The second field days results demonstrate a stronger relationship between stability and the other variables due to more variable weather conditions that ranged from periods of sunshine to storms. On both days stability decreased on high-elevation, northerly-facing slopes. The data-structure complexity provides insights into the difficulties faced by both scientists and conventional avalanche forecasters in predicting snow avalanches.

Exploring multi-scale spatial patterns in historical avalanche data, Jackson Hole Mountain Resort, Wyoming

Many ski areas, backcountry avalanche centers, highway departments, and helicopter ski operations record and archive daily weather and avalanche data. This paper presents a probabilistic method that allows avalanche forecasters to better utilize historical data by incorporating a Geographic Information System (GIS) with a modified meteorological nearest neighbors approach. This nearest neighbor approach utilizes evolving concepts related to visualizing geographic information stored in large databases. The resulting interactive database tool, Geographic Weather and Avalanche Explorer, allows the investigation of the relationships between specific weather parameters and the spatial pattern of avalanche activity. We present an example of this method using over 10,000 individual avalanche events from the past 23 years to analyze the effect of new snowfall, wind speed, and wind direction on the spatial patterns of avalanche activity. Patterns exist at the slide path scale, and for groups of adjacent slide paths, but not for either the entire region as a whole or when slide paths are grouped by aspect. Since wind instrumentation is typically located to measure an approximation of the free air winds, specific topography around a given path, and not simply aspect, is more important when relating wind direction to avalanche activity.

Avalanche extremes and atmospheric circulation patterns

Abstract Avalanche forecasters can better anticipate avalanche extremes if they understand the relationships between those extremes and atmospheric circulation patterns. We investigated the relationship between extreme avalanche days and atmospheric circulation patterns at four sites in the western United States: Bridger Bowl, Montana; Jackson Hole, Wyoming; Alta, Utah; and Taos, New Mexico. For each site, we calculated a daily avalanche hazard index based on the number and size of avalanches, and we defined abnormal avalanche events as the top 10% of days with recorded avalanche activity. We assessed the influence of different variables on avalanche extremes, and found that high snow water equivalent and high snowfall correspond most closely to days of high avalanche hazard. Composite-anomaly maps of 500 hPa heights during those avalanche extremes clearly illustrate that spatial patterns of anomalous troughing prevail, though the exact position of the troughing varies between sites. These patterns can be explained by the topography of the western United States, and the low-elevation pathways for moisture that exist to the west of each of the sites. The methods developed for this research can be applied to other sites with long-term climate and avalanche databases to further our understanding of the spatial distribution of atmospheric patterns associated with extreme avalanche days.

ATMOSPHERIC CIRCULATION PATTERNS ASSOCIATED WITH HEAVY SNOWFALL EVENTS, BRIDGER BOWL, MONTANA, U.S.A.

Predicting heavy mountain snowfall, which is critical for avalanche hazard forecasting, is difficult due to complex interactions between rugged topography and atmospheric circulation. In this study the relationship between atmospheric circulation patterns and extreme snowfall events is examined at Bridger Bowl, Montana, U.S.A. which has a 26-year winter record of daily snowfall. Five hundred millibar composite and anomaly maps were constructed for days of heavy snowfall (greater than 32.8 cm). These maps show that during and prior to heavy snowfall, Bridger Bowl is located beneath the back side of a upper-level trough, with predominant winds and storms coming from the northwest. This atmospheric circulation pattern differs from those for other high-elevation sites in the North American interior due to the surrounding regional topography. High mountain ranges to the southwest and west often block incoming moisture, while relatively lower topography to the northwest allows Pacific moisture to reach Bridger Bowl. The results of this study can be used to complement operational forecasting models for predicting heavy snowfall at Bridger Bowl, thereby facilitating snow avalanche forecasting in the region.

The stuffblock snow stability test: comparability with the rutschblock, usefulness in different snow climates, and repeatability between observers

Abstract The stuffblock is a new snow stability test developed by the Gallatin National Forest Avalanche Center and used operationally since 1993. The test involves stressing an isolated column of snow 0.30 m 2 by dropping a nylon sack filled with 4.5 kg onto the column from 0.10 m increments until weak layer failure occurs. Results over several winters correlate the stuffblock test with the more widely used rutschblock test, and validate the usefulness of the test for evaluating snow stability in several different climates. Further, the test provides results that are consistent between observers, a favorable attribute for regional avalanche forecasting operations which use numerous observers.

A statistical validation of the snowpack model in a Montana climate

Abstract Recently, a computer model has been developed by the Swiss Federal Institute for Snow and Avalanche Research that simulates the evolution of a natural snow cover. Using common meteorological parameters as input, SNOWPACK predicts characteristics such as snowpack temperature and density, in addition to snow microstructure and layering. An investigation was conducted to evaluate the effectiveness of SNOWPACK in a Montana climate. A weather station was constructed in the Bridger Mountains near Bozeman, Montana, to provide the meteorological parameters necessary to run SNOWPACK. Throughout the 1999–2000 winter, weekly snow profiles were performed in undisturbed snow to provide a benchmark for the model output. Density, grain size, and crystallography were recorded on 10-cm intervals over the full snow depth, and the temperature profile was monitored with a thermocouple array. Finally, the meteorological parameters were input into SNOWPACK, and a statistical comparison was performed comparing the predicted snowpack to the observational data. Snowpack temperatures are predicted reasonably accurately by SNOWPACK. The modeled and observed densities correlated well, but the model typically underestimates snowpack settlement. Comparison of grain size and shape was problematic due to different definitions utilized by the model and observer, but still demonstrated some agreement.

Changes in the shear strength and micro-penetration hardness of a buried surface-hoar layer

Abstract We investigated a buried surface-hoar layer using the SnowMicroPen (SMP), an instrument designed to measure detailed snowpack profiles.We collected data from two adjacent parts of a slope 6 days apart. In addition, one manual snowpack profile was sampled each day, as well as 50 quantified loaded column tests (QLCTs) which provided an index of shear strength. For the SMP data, a 900 m2 area was sampled on both days in a grid with points 3 mapart, with some sub-areas of more closely spaced measurements. We collected 86 SMP profiles on the first day and 129 on the second day. Our analyses involved manually locating layer boundaries and calculating statistics for the force signal through the surface-hoar layer. The shear strength index increased by 40% between the two sampling days, but the SMP data show no statistical difference in layer thickness, and the mean, minimum, median, and a variety of percentile measures of the SMP force signal through the layer also do not change. Interestingly, the maximum hardness, and the variance and coefficient of variation of the SMP signal, increased. Since the small SMP tip might only break one or a couple of bonds as it passes through the weak layer, we interpret these changes as being indicative of increasing bond strength. Though we cannot specifically tie the increasing maximum hardness of the SMP signal to our QLCT results, our work suggests that the maximum SMP signal within buried surface-hoar layers may be useful for tracking increases in the shear strength of those layers.

Spatial patterns of surface hoar properties and incoming radiation on an inclined forest opening

Avalanche hazard evaluation relies in part on representative snowpack stability obser- vations. Thus, understanding the spatial patterns of snowpack instabilities and their environmental determinants is crucial. This case study integrates intensive field observations with spatial modeling to identify associations between incoming radiation, surface hoar development and its subsequent shear strength across an inclined forest opening. We examined a buried surface hoar layer in southwest Montana, USA, over five sampling days, collecting 824 SnowMicroPen resistance profiles and performing 352 shear frame tests. Spatial models of incoming long- and shortwave radiation were generated for the surface hoar formation period using modeled hemispheric sky visibility, physically based parameters and the Bird Clear Sky Radiation Model in a Geographic Information System. Before burial, the surface hoar persisted despite moderate winds and relatively high air temperatures. The buried surface hoar layer thickness varied between 3 and 21 mm within a distance of 30 m. Modeled incoming radiation explained spatial variations in layer thickness and shear strength. In areas exposed to large amounts of radiation, the surface hoar layer was strong and thin, while areas with limited incoming radiation (due to high sky visibility and shading) possessed a thicker surface hoar layer that sheared more easily. This demonstrates the usefulness of microclimate modeling for slope-scale avalanche hazard evaluation. We also identify that over the 3 week sample period, strengthening occurred without thinning of the surface hoar layer.