Jürg Trachsel

Predicting natural avalanche activity and verifying avalanche forecasts have long been major challenges. However, the advent of new technologies, such as radar-based avalanche detection systems and prediction models, are beginning to fill these critical gaps. In this study, we describe the integration of these technologies into our operational workflow, assess their perceived value by forecasters, and provide a quantitative comparison between model predictions and radar detections in southern Valais. A recently developed natural avalanche model (NAM), which predicts natural avalanche activity, was used operationally by the Swiss Avalanche Warning Service in the 2023/24 winter season. The model was displayed next to avalanche observations reported by the observer network and avalanches detected by automated radar systems. This visualization was crucial in helping forecasters develop a better appreciation of the new model. The approach also provided immediate feedback when obvious deviations from predicted and actual conditions became apparent. In this work, after one winter of operational use, we quantitatively evaluated model predictions by comparing these with avalanche activity data from two radar avalanche detection systems in Southern Valais. The analysis confirmed that the natural avalanche model was related to regional avalanche activity, but also highlighted areas for improvement. In particular, after reaching a peak in predicted probability, the model often maintained a high probability while measured avalanche activity had ceased. Our findings suggest that incorporating a trend of predicted probability could improve the model’s accuracy. For further model development, we recommend integrating detection data from multiple sites and over multiple winters. In addition, we recommend the development of automated methods to classify detected avalanches as dry or wet and to link these events to explosives logs. This would greatly enhance the real-time utility of detection data for operational avalanche forecasting services and support ongoing analysis and model refinement.

Machine learning (ML) models are revolutionizing avalanche forecasting, providing increasingly reliable predictions. At present, however, such model output can hardly be integrated into the traditional operational forecast workflow. To close this gap, the Swiss Avalanche Warning Service has developed the Snow Avalanche Forecast Editor (SAFE), allowing a flexible integration of both human forecasts and model predictions. In SAFE, each hazard source (e.g., an avalanche problem) is assessed and described as a separate layer. This allows an entirely independent characterization of the severity of avalanche problems including their spatial extent, in line with the European Avalanche Warning Services standards. Once the assessment has been completed, all existing layers are automatically combined and published as regional avalanche forecasts. Forecast accuracy can be increased by minimizing noise. Decision theory advises to calculate an expected value from multiple independent assessments. For this reason, each of the two or three forecasters on duty assesses the regional avalanche danger in the forecast domain independently of each other. Another estimate comes from the danger-level model. To combine these, forecasters and models must assess the same hazard source using the same target variable. SAFE merges these independent assessments to expected values of the danger level including sub-levels, and the particularly affected elevations and aspects. This includes clustering into a limited number of danger regions, characterized by similar expected avalanche conditions. Following the discussion between forecasters, clusters can be refined. Lastly, the avalanche danger of each cluster is manually described. SAFE is conceived as open-source platform and a first version has been operational within the Swiss avalanche warning since winter 2023/24.

Saharan dust outbreaks have profound effects on ecosystems, climate, human health, and the cryosphere in Europe. However, the spatial deposition pattern of Saharan dust is poorly known due to a sparse network of ground measurements. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This somewhat improvised campaign triggered wide interest since 152 samples were collected from the snow in the Pyrenees, the French Alps, and the Swiss Alps in less than 4 weeks. Among the 152 samples, 113 in total could be analysed, corresponding to 70 different locations. The analysis of the samples showed a large variability in the dust properties and amount. We found a decrease in the deposited mass and particle sizes with distance from the source along the transport path. This spatial trend was also evident in the elemental composition of the dust as the iron mass fraction decreased from 11% in the Pyrenees to 2% in the Swiss Alps. At the local scale, we found a higher dust mass on south-facing slopes, in agreement with estimates from high-resolution remote sensing data. This unique dataset, which resulted from the collaboration of several research laboratories and citizens, is provided as an open dataset to benefit a large community and to enable further scientific investigations. Data presented in this study are available at 10.5281/zenodo.7969515 .

Hydrogen peroxide is a primary atmospheric oxidant significant in terminating gas-phase chemistry and sulfate formation in the condensed phase. Laboratory experiments have shown an unexpected oxidation acceleration by hydrogen peroxide in grain boundaries. While grain boundaries are frequent in natural snow and ice and are known to host impurities, it remains unclear how and to which extent hydrogen peroxide enters this reservoir. We present the first experimental evidence for the diffusive uptake of hydrogen peroxide into grain boundaries directly from the gas phase. We have machined a novel flow reactor system featuring a drilled ice flow tube that allows us to discern the effect of the ice grain boundary content on the uptake. Further, adsorption to the ice surface for temperatures from 235 to 258 K was quantified. Disentangling the contribution of these two uptake processes shows that the transfer of hydrogen peroxide from the atmosphere to snow at temperatures relevant to polar environments is considerably more pronounced than previously thought. Further, diffusive uptake to grain boundaries appears to be a novel mechanism for non-acidic trace gases to fill the highly reactive impurity reservoirs in snow's grain boundaries.

CAAML Version 6 for EAWS bulletins is a standardized data format designed to describe avalanche bulletins, providing a common language for conveying crucial information about snowpack conditions, avalanche activity, and hazards. Developed through collaborative efforts by international organizations and experts, CAAML Version 6 facilitates seamless data exchange, enhances data accuracy, and promotes effective decision-making in avalanche risk management. This paper offers a comprehensive overview of the format, discussing its fundamental principles, structure, and implementation guidelines. The support for both XML and JSON data formats, along with data validation guidelines and extensibility, ensures CAAML Version 6 remains relevant and adaptable to advances in avalanche science and information technology.

In public avalanche forecasts, avalanche danger is commonly summarized using one of five ordinal danger levels. This strong simplification of a complex phenomenon inevitably leads to a loss of information. To compensate for this information loss and to ease interpretation of the forecast, the Swiss avalanche warning service introduced sublevels, that indicate whether the forecast danger is in the lower (-), middle (=) or higher (+) range of the danger level. After a 6-year test period, during which it showed that forecasters can reliably assign sublevels to a danger level, the sublevels were published for the first time in the public avalanche forecast in the winter season of 2022/2023. To evaluate the general understanding and the usefulness of the sublevels, and to understand how they influence people’s backcountry behavior, we performed a user survey towards the end of the season. The survey with 3403 participants showed that participants perceived the sublevels as generally useful (85%) and that they understood them in the intended manner (94%). Sublevels also had a positive influence on the planning of backcountry tours. Faced with a forecast sublevel (+), almost half of the participants claimed they would change their plans to a less exposed tour than they had before when the same danger level was given but without sublevel information. This self-stated influence of the sublevels on the choice of a backcountry tour was especially important for participants with little or no avalanche training, showing that sublevels seem most useful for less experienced forecast users, who may find it difficult to extract similar information from the forecast text description.

When riding out of bounds or touring in the backcountry, many recreationists and professionals plan their trip with the aim of finding a tour at a personally acceptable level of risk. Particularly during the planning phase, information from the public avalanche forecast is considered. In Switzerland, the avalanche forecast summarizes avalanche conditions with a danger level (DL) and the aspects and elevations (AE) where the DL applies. Further, it informs about the relevant avalanche problems, including a text description. Previous studies have shown that most of this information is related to avalanche risk. However, it is poorly understood which information users consider helpful for trip planning and whether these (often) self-stated claims relate to what is remembered at the beginning of a trip. We therefore conducted two independent surveys. The online survey, with 3400 participants, showed that all information provided in the forecast is perceived as valuable for planning. The DL was considered the most important, followed by the avalanche problem(s). In comparison, the AE were considered less important. This ranking of the users is not in line with recent findings regarding avalanche risk. For the second survey, we went outdoors, either in a popular area for out of bounds skiing or at trail heads of ski tours and asked the users directly. Compared to the responses from the online survey, a different picture emerged: While the DL was well-remembered (90 % correct), only around half of the participants (44 %) could correctly name the avalanche problems. In an application exercise, a clear minority (24 %) could say whether slopes of a particular aspect and elevation were assessed as critical in the forecast. This apparent discrepancy between the self-stated use of forecast information during trip planning and the retention of the information at the start of a trip comes partly as a surprise. Especially the avalanche problems, intended to emphasize and focus on the cause of instability resulting in impact-oriented travel advice, are remembered poorly. The findings are supported by other recent surveys in Europe and show that the information from the forecast is not effectively retained, even at the start of a trip. It highlights the need to rethink and improve the communication of avalanche danger, including the level of detail. While providing detailed information may be helpful for experts, it may be overwhelming for less experienced users. Our study aims to contribute to the ongoing discussion on how to best communicate avalanche danger to reduce risks for recreational skiers.

Stable water isotopes are used as a paleothermometer in ice cores for climate reconstructions over the past millennia. The underlying physical processes involved in the isotope-temperature relation, however, unfold at much shorter timescales. Here, we study the temporary archival of frontal passages in the seasonal Alpine snow cover. We combine five snow profiles sampled in winter 2017 at the Weissfluhjoch with a quantitative snow layer age reconstruction and atmospheric reanalysis data to characterize the circulation and clouds associated with the precipitation producing synoptic-scale cold and warm fronts. We find that the vertical cloud structure and the air parcels' net cooling during transport leave a distinct imprint in the δ¹⁸O and δD vertical profile in the snow. The near-surface humidity gradient at the moisture source is reflected in the second order isotope parameter deuterium excess. In the cold season, these environmental conditions during cloud formation and at the moisture source are preserved in the snow. In the melt season, significant post-depositional effects due to wet snow metamorphism, however, leads to an enrichment in heavy isotopes in the snow and a strong smoothing of the initial atmospheric imprint. These findings show that the isotope signal archived in the dry snow cover is strongly modulated by individual weather systems prior to deposition. Major shifts in the upper-level jet stream and cyclone tracks likely leading to changes in moisture source regions and conditions, could therefore be detectable in the isotope composition of Alpine ice.

Earth's snow cover is very dynamic on diurnal timescales. The changes to the snow structure during this metamorphism have wide-ranging impacts on processes such as avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapour, on the chemical reactivity of bromide in the snow. To this end, the heterogeneous reactive loss of ozone in the dark at a concentration of 5×10¹²–6×10¹² molec. cm⁻³ is investigated in artificial, shock-frozen snow samples doped with 6.2 µM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletion. We find that the heterogeneous reactivity of bromide is completely absent from the air–ice interface in snow after 12 d of temperature gradient metamorphism, and we suggest that the burial of non-volatile bromide salts occurs when the snow matrix is restructuring during metamorphism. Impacts on polar atmospheric chemistry are discussed.

Understanding the impact of melting on the preservation of atmospheric compounds in high‐Alpine snow and glacier ice is crucial for future reconstruction of past atmospheric conditions. However, detailed studies investigating melt‐related changes of such proxy information are rare. Here we present a series of five snow pit profiles of 6 major ions and 34 trace elements at Weissfluhjoch, Switzerland, collected between January and June 2017. Atmospheric composition was preserved during the cold season, while melting toward the summer resulted in preferential loss of certain species from the snowpack or enrichment at the base of the snowpack. Increasing mobilization of major ions with meltwater (NH₄⁺ < Cl⁻ ~ Na⁺ < NO₃⁻ ~ Ca²⁺ ~ SO₄²⁻) can be related to their stronger enrichment at ice crystal surfaces during snow metamorphism. Results for trace elements show that less abundant elements such as Ce, Eu, La, Mo, Nd, Pb, Pr, Sb, Sc, Sm, U, and W were best preserved and may still serve as tracers to reconstruct past natural and anthropogenic atmospheric emissions from melt‐affected snow pit and ice core records. The obtained elution behavior matches the findings from another high‐Alpine site (upper Grenzgletscher) for major ions and the large majority of investigated trace elements. Both studies indicate that water solubility and location at the microscopic scale are likely to determine the relocation behavior with meltwater and also suggest that the observed species‐dependent preservation from melting snow and ice is representative for the Alpine region, reflecting Central European atmospheric aerosol composition.

Microplastics (MPs) are ubiquitous, and considerable quantities prevail even in the Arctic; however, there are large knowledge gaps regarding pathways to the North. To assess whether atmospheric transport plays a role, we analyzed snow samples from ice floes in Fram Strait. For comparison, we investigated snow samples from remote (Swiss Alps) and populated (Bremen, Bavaria) European sites. MPs were identified by Fourier transform infrared imaging in 20 of 21 samples. The MP concentration of Arctic snow was significantly lower (0 to 14.4 × 10³ N liter⁻¹) than European snow (0.19 × 10³ to 154 × 10³ N liter⁻¹) but still substantial. Polymer composition varied strongly, but varnish, rubber, polyethylene, and polyamide dominated overall. Most particles were in the smallest size range indicating large numbers of particles below the detection limit of 11 μm. Our data highlight that atmospheric transport and deposition can be notable pathways for MPs meriting more research.

Earth's snowpack hosts chemical impurities that exchange with the overlying air, strongly impacting atmospheric chemistry. Being embedded in firn and glacier ice formed from surface snow, impurities provide the basis for reconstructing past atmospheric composition from ice core records. The location of these impurity compounds within the snow critically controls their reactivity and preservation. Ammonium (NH₄⁺) determines acid-base equilibria and buffer capacity within the snow and is a fundamental ice-core proxy, especially for biogenic, forest fire, and anthropogenic emissions. However, the redistribution during snow metamorphism affecting snow chemical reactivity and potential post-depositional relocation is not understood so far. Here, we study the rearrangement of NH₄⁺ and five other major ions (Ca²⁺, Cl^–, F^–, Na⁺, and SO₄^2-) during dry snow metamorphism using a series of elution experiments. Artificial and natural snow samples were stored for up to 3 months at a controlled temperature gradient of 40 K/m and isothermal conditions. The different types of snow increase complexity as natural and artificial snow have a different history that impacts their physical properties and the initial distribution of impurities. Further, we test our findings using natural snow samples taken from different depths of a natural snowpack at the Weissfluhjoch (Swiss Alps) to confirm the impact of our laboratory results to the cryosphere. With progressing temperature gradient metamorphism, snow structures in natural and artificial snow converged and ions with high solubility in ice (NH₄⁺, F^–, and Cl^–) were incorporated into the less accessible ice interior. In contrast, ions with lower solubility (Ca²⁺, SO₄^2-, and Na⁺) became better accessible for the eluent. Our results show that the redistribution during snow metamorphism is strongly dependent on the temperature gradient, exposure time and chemical composition. This study allowed for the first time to explicitly relate the general low relocation proneness of NH₄⁺ during post-depositional processes such as meltwater percolation to the preferred incorporation of this ion into the less accessible ice interior during snow metamorphism. Furthermore, our results imply that with ongoing aging of a snowpack, NH₄⁺, independent of its primary location, is less available for chemical reactions at the air-ice interface.