Dr. Christine Pielmeier

The snow compression test is a snow stability test where an isolated column of snow is progressively loaded by tapping on it to induce failure in a possible weak layer. The test result provides valuable information about the propensity of failure initiation within the snowpack. However, different persons might tap with different force and thus reduce the reproducibility of the test results. The aim of this work was to quantify the influence of different test persons and different snowpacks on snow compression test results. We therefore let 62 persons tap on a stress measurement plate during a workshop of the European Avalanche Warning Services. Moreover, in the field, we performed stress measurements during 116 snow compression tests with 13 persons at eight different locations in the Alps. Data on persons’ body features and snow properties were also collected. Our results show that the stresses that reach a weak snow layer due to tapping are influenced by both the snowpack as well as different persons. Still, the data's scattering is surprisingly small for lower loading steps and decreases with depth. Therefore, we can deduce that, especially when avalanche conditions are particularly dangerous, snow compression test results are quite reproducible.

Le rapport comprend une rétrospective de la situation nivologique et avalancheuse dans les Alpes suisses et le Jura suisse. L’évolution de la hauteur de neige et les principaux épisodes de précipitations ainsi que les périodes avalancheuses les plus importantes avec l’évolution de la structure et de la stabilité du manteau neigeux y sont abordés. De plus amples informations sur les différentes pé-riodes, les cartes de danger et de hauteur de neige peuvent être consultées sur l’AvaBlog (anciennement rapport hebdomadaire), les bulletins complets dans les archives sur Internet à l’adresse www.slf.ch.

Der Winter 2022/23 war ausserordentlich schneearm und warm. Während im Vorjahr der Winter bereits als «extrem schneearm im Süden» beschrieben wurde, war der Winter 2022/23 durch rekordtiefe Schneehöhen in der ganzen Schweiz charakterisiert. Vor allem zwischen Mitte Februar und Mitte März waren die Schneehöhen im Schweizer Alpenraum so tief wie noch nie seit Messbeginn. Die Schneearmut ergab sich aus der Kombination von unterdurchschnittlichen Niederschlagsmengen und zu warmen Temperaturen.

Recent advances in automated snowpack modelling notwithstanding, public avalanche forecasting relies heavily on human estimates of avalanche conditions. Like any human judgments, these estimates differ to some extent from one forecaster to the next. We assess inter-rater reliability (IRR) — the proportion of pairwise agreement among forecasters — both for estimates of factors determining avalanche danger and for the danger level (D) itself. Comparing forecast drafts prepared independently by forecasters for the same forecast task, both in Switzerland (SWI) and in Norway (NOR), we find that IRR is lower for the factors determining avalanche danger (SWI: 0.6 − 0.66, NOR: 0.46 − 0.75) than for the danger level (SWI: 0.87, NOR: 0.76). The EAWS Matrix is a tool for estimating D that is supposed to secure IRR. It is not a part of the daily workflow in Switzerland, and one might wonder whether introducing it there would help. We find that the IRR for D would on the contrary have been much lower were the primary D chosen in the Matrix (a mere 0.54)! Where IRR is low, individual forecasts must often be incorrect, since two different forecasts cannot both be right. We calculate on the basis of the observed IRR that when estimating the factors in avalanche danger the average forecaster is incorrect in 32% (NOR: frequency) and 13% (NOR: avalanche size) of cases. Forecasting D without the Matrix, a forecaster is incorrect 7% of the time (in SWI). With the Matrix, a forecaster is incorrect about D in 13% (NOR) and 27% of cases (SWI). We conclude that while the EAWS workflow does give structure to the forecasting process, using the Matrix can be counterproductive. It can inadvertently compound variability in parameter inputs. The IRR of Swiss D forecasts leaves some room for improvement, but introducing the Matrix into the Swiss workflow cannot be expected to increase it while the IRR of Swiss factor forecasts remains as low as it currently is. We recommend that avalanche warning services assess the IRR of forecasters and consider the effects of low input IRR on the IRR of their Matrix outputs. Moreover, they should consider the effect of unreliability on forecast correctness. Where IRR is low, one intervention to boost forecast correctness is training forecasters with a view to increasing IRR. Another is to aggregate several individual forecasts for the same task, as is standard practice in Switzerland.

The snow compression test is a well-known and widely used snow stability test where an isolated column of snow is progressively loaded by tapping on it to induce failure in a possible weak layer. The test result provides valuable information about the existence of possible weak layers and consequently the propensity of failure initiation within the snowpack. As the test is performed manually by tapping, different persons might tap with different force and thus reduce the reproducibility of the test results. The aim of this work was to quantify the influence of different test persons and different snowpacks on snow compression test results. Moreover, we compare our stress measurements to measurements performed previously by others and discuss the comparability of different measurements and different snowpack tests. As far as different persons are concerned, we let 62 persons tap on a stress measurement plate during a workshop of the European Avalanche Warning Services. In the field, we performed stress measurements during 116 snow compression tests with 13 persons at eight different locations in the Alps. Our results show that the stresses that reach a weak snow layer due to tapping are influenced by both the snowpack as well as different persons. Still, the data's scattering is surprisingly small for lower loading steps and decreases with depth. Therefore, we can deduce that, especially when avalanche conditions are particularly dangerous, snow compression test results are quite reproducible. Moreover, since the compression test and the extended column test share the same loading steps, the results are equally relevant for the extended column test, which is frequently used by snow and avalanche experts in the field.

In public avalanche forecasts, avalanche danger is summarized using a five-level ordinal danger scale. However, in Switzerland - but also in other countries - on about 75% of the forecasting days, only two of the five danger levels are actually used, indicating a lack of refinement in the forecast danger level. A refined classification requires the forecasters to assess the avalanche danger in greater detail than the established danger levels. This leads to the fundamental question, whether a reasonable accuracy and consistency of refined danger ratings can be achieved at all. We address this question relying on a data set from Switzerland, where forecasters of the national avalanche warning service have refined the forecast danger level using three sub-levels (minus, neutral, plus) during four forecasting seasons. These sub-levels, which describe where within a danger level the danger was estimated, were not provided to the public. With the goal to assess whether the forecast sub-levels were better than a random assignment of sub-levels, we compared these forecasts with local nowcast estimates of avalanche danger, for days when two observers reported such an estimate (N= 1146), as ground truth. The agreement between the forecast regional danger level and the local danger level estimate was 81%, with a distinct over-forecast bias in cases when forecast and nowcast disagreed. This tendency towards over-forecasting also showed in a spatial and temporal context. Furthermore, some anomalies in the use of the sub-levels were noted, particularly for sub-level plus in combination with danger level 2-Moderate. Despite these anomalies, the forecast sub-levels were clearly better than a randomly assigned sub-level, resulting in a lower misclassification cost. Furthermore, in case of over-forecasting, the forecast sub-level was in 70% of the cases the sub-level closest to the local estimate, and thus the difference between forecast and nowcast danger level was likely less than one "full" danger level. This indicates that forecasters can often forecast avalanche danger at greater detail than the established danger levels, provided that relevant and reliable data is available in sufficient spatial and temporal density, and that the warning regions, the smallest spatial units used in the forecast are sufficiently small. Therefore, we argue, such refinements of the danger level should be made whenever possible, last but not least for an improved internal assessment of avalanche danger.

Information on the structure of the snow cover is of great importance for operational avalanche forecasting. Manually observed snow profiles, including snow hardness, are therefore widely used to characterize snow stratigraphy. However, such manual measurements are subjective and observer dependent. While the ramsonde resistance profile provides a more objective alternative, it lacks the vertical resolution to identify thin layers and the hardness resolution to identify soft layers, which are essential components of a snow stability assessment. To overcome these limitations, digital cone penetrometers were developed to collect accurate and objective snow cover stratigraphy data. The SnowMicroPen provides highly resolved and accurate hardness profiles but its high price, size and weight, and fragility limit its usage to research purposes. Recently, a new lightweight penetrometer was released, the SP2, intended to fill the gap between the low-resolution ramsonde and the more expensive, accurate, high-resolution SnowMicroPen. We conducted an objective comparison of co-located vertical profiles measured by these three instruments in combination with manual stratigraphy and stability tests, in the French and Swiss Alps and in North America during winter 2015–2016. The SP2 profiles showed stratigraphic features similar to the SMP profiles. However, SP2 measurements were less repeatable with a profile variability generally larger than the spatial variability and influenced by the operator handling such as the penetration speed. The vertical accuracy was relatively low: the total depth was measured with a standard error of 7.5 cm and vertical shifts of the layer position were measured in the range [−10, 22] cm with a standard error of 7.4 cm. Hardness measured by the SP2 showed no significant bias and a standard error of 34 kPa compared to the SMP. The SP2 resolution, as the ramsonde resolution, was too low to detect the weak layer of the considered new snow problem but sufficient to detect the weak layer associated to the considered old snow problems. Nevertheless, on these problems, the accuracy of the SP2 to characterize the slab and weak layer properties was too low to effectively derive stability indices directly from the SP2 profiles.

Information on the structure of the snow cover is of great importance for operational avalanche forecasting. Manually observed snow profiles including snow hardness are therefore widely used to characterize snow stratigraphy. However, such measurements are subjective and observer dependent. While the ramsonde resistance profile provides a more objective alternative, it lacks the vertical resolution to identify thin layers which are often responsible for avalanche release. To overcome these limitations digital cone penetrometers were developed to provide accurate and objective snow cover stratigraphy data. Two well-known examples are the SnowMicroPen (SMP) and the recently developed SP2. In this study, we therefore investigate the accuracy and repeatability of various measurement methods to quantify snow stratigraphy by performing side-by-side SMP, SP2 and ramsonde measurements as well as profiles of hand hardness index and density on a level study site. Results show that the SMP provides the most repeatable and detailed measurements, while hand hardness profiles were generally very coarse but included relevant thin weak layers and crusts. SP2 profiles showed stratigraphic features similar to the SMP. However, SP2 measurements were less repeatable, resolution was coarser and shifts in the vertical resolution were observed. The strengths and limitations of the different methods are compared in view of future developments for operational avalanche forecasting.

Terrestrial radar interferometry is used in geotechnical applications for monitoring hazardous Earth or rock movements. In this study, we use it to continuously monitor snowpack displacements. As test site, the Dorfberg slope at Davos, Switzerland, was measured continuously during March 2014. The line of sight displacement was retrieved at a spatial resolution of millimeter to centimeter and a temporal resolution of up to 1min independent of visibility. The results reveal several temperature-driven diurnal acceleration and deceleration cycles. The initiation of a small full-depth glide avalanche was observed after 50cm total differential displacement. The maximum measured displacement of another differential glide area reached 43cm/h without resulting in a full-depth avalanche even after a total measured differential displacement of 4.5m. In regard of the difficulty to predict full-depth glide avalanches on the regional scale, the presented method has big potential for operational snow glide monitoring on critical slopes.

Information on avalanche activity or non-activity on local and regional scale is of great value for avalanche warning services, traffic authorities and experts responsible for safety in communities or ski resorts. In particular during bad weather condition, such information is available only very limited or not at all. The aim of the ESA IAP feasibility study “Improved Alpine Avalanche Forecast Service” was to investigate existing technology to overcome this gap. Of particular interest were radar-based techniques that have the potential to operate independently of daylight and weather conditions.
For testing the observation of avalanche activity on a local scale, a terrestrial radar was installed at the WSL Institute for Snow and Avalanche Research SLF, illuminating the Dorfberg close to Davos, Switzerland during winter 2013/2014. On that slope, frequent natural as well as artificially triggered avalanches can be expected. The system acquired datasets at minute temporal resolution, which allows the production of coherence maps to detect avalanche events and also features such as snow creep and free-riders tracks. The spatial coverage of the terrestrial system was 6 km² for this experiment. On the regional scale, data from radar satellites with very high spatial resolution (< 3 m) were analyzed. A TerraSAR-X stripmap mode satellite frame, for example, covers 1500 km² and has a temporal resolution of 11 days. A combination of terrestrial and space-borne radar sensors could be a powerful tool to map avalanche activity for different scales during any weather condition. We present first results of terrestrial and space-borne avalanche activity mapping at Davos during the winter 2013/2014 and discuss capabilities and limitations for local and regional avalanche warning services.

The "Improved Alpine Avalanche Forecast Service" (AAF) study was a one-­‐year feasibility study funded by the Integrated Application Program (IAP) of the European Space Agency (ESA). The project consortium consisted of four partners: the WSL Institute for Snow and Avalanche Research SLF (CH), the Norwegian Geotechnical Institute NGI (NO), GAMMA Remote Sensing AG (CH) and ENVEO IT GmbH (AT).
WSL/SLF was leading the project contributing with its experience in providing avalanche warning services in Switzerland. NGI contributed with experience in customer-tailored avalanche warning services in Norway and a background in applying satellite technology for snow-­related measurements. GAMMA Remote Sensing AG and ENVEO IT GmbH were technical consortium members with long-­term experience in optical and radar remote sensing of snow. The main goal of the AAF study was to assess the technical feasibility and commercial viability of improving European avalanche warning services by applying satellite technology. [...]