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Snow avalanche‐induced air‐blasts are capable of breaking trees, damaging buildings and causing fatalities. Predicting their destructive properties is an essential part of snow avalanche hazard mitigation. Here, we propose a depth‐averaged model that involves turbulent fluctuations to simulate the air‐blast dynamics. The turbulent energy of the air‐blast arises from that of dust‐mixed air transferred from the avalanche core, shearing work in the cloud and entrained air, and is exploited to improve the air entrainment and drag relationships. We further present a unique data set of air blast‐induced tree breakage, providing type, status, diameter and falling direction of the measured trees. Through case studies of two artificially released avalanches with measured powder heights and three natural avalanches with tree‐breakage information, we test the model and investigate the turbulence effect on air‐blast dynamics. The proposed model and tree‐breakage data set quantify the air‐blast destructiveness and can be applied for avalanche hazard assessment. Snow avalanche‐induced air‐blasts are common natural hazards in high‐altitude regions. They are fully turbulent mixtures of ice dust and gases capable of causing damage and human fatalities far beyond the avalanche deposits, representing a major threat to societies in avalanche‐prone environments. In this study, we propose a robust numerical model that accounts for the turbulent fluctuations to simulate the air‐blast dynamics. An unprecedented data set of air blast‐induced tree breakage in three natural snow avalanches is further presented. Using five case studies in Switzerland, of which two artificial avalanches and three natural avalanches with tree‐breakage data, we test the model and investigate the impact of turbulence on air‐blast dynamics. Results suggest great performances of the proposed model in calculating the air‐blast height, impact area and dynamic pressure. Turbulent fluctuations play an important role in the travel resistance and air entrainment of the air‐blast, and can magnify the maximum pressure several times larger than the mean value. The new air‐blast hazard model gives promising perspectives for estimations of snow avalanche hazards, and the tree‐breakage data set can serve as a calibration basis for future more accurate numerical avalanche models. An unprecedented tree breakage data set is presented to quantify the magnitude and reach of the air‐blast generated by three snow avalanchesThe forest destruction is simulated with a depth‐averaged avalanche model to calculate the pressures induced by snow avalanche air‐blastsTurbulence can magnify the air‐blast pressure several times larger than the mean value, acting at frequencies near the tree frequencies An unprecedented tree breakage data set is presented to quantify the magnitude and reach of the air‐blast generated by three snow avalanches The forest destruction is simulated with a depth‐averaged avalanche model to calculate the pressures induced by snow avalanche air‐blasts Turbulence can magnify the air‐blast pressure several times larger than the mean value, acting at frequencies near the tree frequencies

An exceptional July 2022 winter storm brought 550 mm of precipitation to the Southern Alps of New Zealand. A series of alpine mass movements occurred during the storm, including a widespread snow avalanche cycle, debris flows, and erosion from rain runoff. We detail the sequence of events in the Kitchener avalanche path. Here, two large snow avalanches were followed by a debris flow. Substantial erosion of deposition and the underlying alluvial fan were induced by runoff from over 300 mm of rain falling after the first avalanche. The Kitchener path saw the largest avalanche since 1986, testing the utility of a diversion berm constructed for a 1:100‐year event. Results from a unmanned aerial vehicle lidar survey and numerical modeling characterize the rain‐on‐snow hazard sequence. In particular, the rain‐on‐snow event occurred on a deep mid‐winter snowpack, offering insights into future hazards posed by increasingly frequent extreme alpine precipitation. Intense rain and snow in alpine regions can trigger snow avalanches, debris flows and other mass‐movements, posing risks to people and infrastructure. This study documents an extreme hazard sequence triggered by a record‐breaking winter rainstorm in the Southern Alps of New Zealand. A drone was used to map deposition from snow avalanches and a debris flow that ran along a diversion berm designed to protect Aoraki/Mount Cook Village from a 1:100‐year avalanche. The mapping was used to calibrate avalanche modeling software that could replicate key characteristics of the snow avalanches and provide insight into flow dynamics. The documentation and results from the modeling can be used to plan for future hazards triggered by intense rain falling on a winter snowpack, which is particularly important in the face of a warming climate. Record‐breaking winter storm bringing rain to high elevations triggered a series of alpine mass movements in New Zealand's Southern AlpsSnow avalanches were successfully diverted away from Aoraki/Mount Cook Village in the largest avalanche cycle observed in decadesEvent documentation and modeling help anticipate future hazards for such rain‐on‐snow induced mass movements on deep mid‐winter snowpacks Record‐breaking winter storm bringing rain to high elevations triggered a series of alpine mass movements in New Zealand's Southern Alps Snow avalanches were successfully diverted away from Aoraki/Mount Cook Village in the largest avalanche cycle observed in decades Event documentation and modeling help anticipate future hazards for such rain‐on‐snow induced mass movements on deep mid‐winter snowpacks