Spatial consistency and bias in avalanche forecasts – a case study in the European Alps

In the European Alps, the public is provided with regional avalanche forecasts, issued by about 30 forecast centers throughout the winter, covering a spatially contiguous area. A key element in these forecasts is the communication of avalanche danger according to the five-level, ordinal European Avalanche Danger Scale (EADS). Consistency in the application of the avalanche danger levels by the individual forecast centers is essential to avoid misunderstandings or misinterpretations by users, particularly those utilizing bulletins issued by different forecast centers. As the quality of avalanche forecasts is difficult to verify, due to the categorical nature of the EADS, we investigated forecast goodness by focusing on spatial consistency and bias, exploring real forecast danger levels from four winter seasons (477 forecast days). We describe the operational constraints associated with the production and communication of the avalanche bulletins, and we propose a methodology to quantitatively explore spatial consistency and bias. We note that the forecast danger level agreed significantly less often when compared across national and forecast center boundaries (about 60&thinsp;%) than within forecast center boundaries (about 90&thinsp;%). Furthermore, several forecast centers showed significant systematic differences in terms of more frequently using lower (or higher) danger levels than their neighbors. Discrepancies seemed to be greatest when analyzing the proportion of forecasts with danger level 4 – high and 5 – very high. The size of the warning regions, the smallest geographically clearly specified areas underlying the forecast products, differed considerably between forecast centers. Region size also had a significant impact on all summary statistics and is a key parameter influencing the issued danger level, but it also limits the communication of spatial variations in the danger level. Operational constraints in the production and communication of avalanche forecasts and variation in the ways the EADS is interpreted locally may contribute to inconsistencies and may be potential sources for misinterpretation by forecast users. All these issues highlight the need to further harmonize the forecast production process and the way avalanche hazard is communicated to increase consistency and hence facilitate cross-border forecast interpretation by traveling users.</p

Computation of 3D curvatures on a wet snow sample

The map of 3D curvatures of a porous medium characterizes most of its capillary properties. A model for directly computing curvatures from a three-dimensional image of the solid matrix of a porous medium is presented. A precise distance map of the object is built using the “chamfer” distance of discrete geometry. The set of local maxima of the distance map is used for quick location of the normal to each point P of the object's surface. The normal being known, principal radii of curvature are computed in 2D and lead to 3D curvature. This model was validated on geometric shapes of known curvature, then applied on a natural snow sample. The snow image was obtained from a serial cut (performed in cold laboratory) observed under specularly reflected light. Views of both fresh and sublimated sections were taken for each of the 64 section planes: this allowed easier distinction between snow and filling medium and made possible automatic contouring of section plane images. Curvature maps computed from pore and grain phases respectively were found to be in excellent agreement for each tested object shape, including the snow sample

Measurements of pore-scale water flow through snow using fluorescent particle velocimetry

Fluorescent Particle Tracking Velocimetry (FPTV) measurements of the pore-scale water flow through the pore space of a wet-snow sample are presented to demonstrate the applicability of this measurement technique for snow. For the experiments, ice-cooled water seeded with micron sized fluorescent tracer particles is either sprinkled on top of a snow sample to investigate saturated and unsaturated gravity-driven flow or supplied from a reservoir below the snow sample to generate upward flow driven by capillary forces. The snow sample is illuminated with a laser light sheet and the fluorescent light of the particles transported with the water in the pore space is recorded with a high-speed camera equipped with an optical filter. Tracking algorithms are applied to the images to obtain flow paths and flow velocities. A flow loop found in a pore space for the case of saturated gravity flow together with the tortuosity of the particle trajectories indicate the three-dimensionality of the water flow in wet snow. The average vertical flow velocities in the pore spaces were 11.2 mm s1 for the downward saturated gravity flow and 9.6 mm s1 for the upward flow that is driven by capillary forces for the limited cases presented as examples of the measurement technique. In the case of unsaturated gravity-driven flow, the average and the maximum flow velocities were found to be 30 times smaller than for the saturated gravity flow. Velocity histograms show that the fraction of the total water flowing against the main flow direction was about 3–5%, and that the horizontal velocities average to zero for both the saturated gravity-driven and the capillary flow