Orographic lifting of air masses and other topographically modified flows induce cloud and precipitation formation at larger scales and preferential deposition of precipitation at smaller scales. In ...this study, we examine orographic effects on small‐scale snowfall patterns in Alpine terrain. A polarimetric X‐band radar was deployed in the area of Davos (Switzerland) to determine the spatial variability of precipitation. In order to relate measured precipitation fields to flow dynamics, we model flow fields with the atmospheric prediction model “Advanced Regional Prediction System.” Additionally, we compare radar reflectivity fields with snow accumulation at the surface as modeled by Alpine3D. We investigate the small‐scale precipitation dynamics for one heavy snowfall event in March 2011 at a high resolution of 75 m. The analysis of the vertical and horizontal distribution of radar reflectivity at horizontal polarization and differential reflectivity shows polarimetric signatures of orographic snowfall enhancement near the summit region. Increasing radar reflectivity at horizontal polarization over the windward slopes toward the crest and downwind decreasing reflectivity over the leeward slopes is observed. The temporal variation of the location of maximum concentration of snow particles is partly attributed to the effect of preferential deposition of snowfall: For situations with strong horizontal winds, the concentration maximum is shifted from the ridge crest toward the leeward slopes. Qualitatively, we discuss the relative role of cloud microphysics such as the seeder‐feeder mechanism versus atmospheric particle transport in generating the observed snow deposition at the ground.
Key Points
Orographic snowfall enhancement near the summit region
Preferred snow deposition on leeward slopes
Snow drift affects reflectivity patterns observed by radar
The thermal conductivity of snow determines the temperature gradient, and by this, it has a direct effect on the rate of snow metamorphism. It is therefore a key property of snow. However, thermal ...conductivities measured with the transient needle probe and the steady-state, heat flux plate differ. In addition, the anisotropy of thermal conductivity plays an important role in the accuracy of thermal conductivity measurements. In this study, we investigated three independent methods to measure snow thermal conductivity and its anisotropy: a needle probe with a long heating time, a guarded heat flux plate, and direct numerical simulation at the microstructural level of the pore and ice structure. The three methods were applied to identical snow samples. We analyzed the consistency and the difference between these methods. As already shown in former studies, we observed a distinct difference between the anisotropy of thermal conductivity in small rounded grains and in depth hoar. Indeed, the anisotropy between vertical and horizontal thermal conductivity components ranges between 0.5-2. This can cause a difference in thermal conductivity measurements carried out with needle probes of up to -25 % to +25 % if the thermal conductivity is calculated only from a horizontally inserted needle probe. Based on our measurements and the comparison of the three methods studied here, the direct numerical simulation is the most reliable method, as the tensorial components of the thermal conductivity can be calculated and the corresponding microstructure is precisely known.
The composition of the lower atmospheric boundary layer can be strongly influenced by snow photochemistry. Surface snow, where air‐snow interactions take place, is viewed as slowly changing ...quasi‐isothermal snow, implied by the observation of mainly rounded snow crystals. The role of snow for photochemistry is therefore expected to be purely geometric. However, large temperature gradients are often observed in these layers, which would imply high recrystallization and faceting. In controlled laboratory experiments we showed that temperature gradients on the order of 100 K m−1 do not lead necessarily to faceting if their sign changes with a daily cycle. The shape of snow crystals does not reflect necessarily the metamorphic process. With time‐lapse X‐ray tomography, recrystallization rates as high as 60% of the total ice mass were observed during 12 hours. The high recrystallization rates in apparently isothermal snow not only contradict the current understanding of snow metamorphism, they also might influence chemical air‐snow interactions.
Dry snow metamorphism under an external temperature gradient is the most common type of recrystallization of snow on the ground. The changes in snow microstructure modify the physical properties of ...snow, and therefore an understanding of this process is essential for many disciplines, from modeling the effects of snow on climate to assessing avalanche risk. We directly imaged the microstructural changes in snow during temperature gradient metamorphism (TGM) under a constant gradient of 50 K m−1, using in situ time-lapse X-ray micro-tomography. This novel and non-destructive technique directly reveals the amount of ice that sublimates and is deposited during metamorphism, in addition to the exact locations of these phase changes. We calculated the average time that an ice volume stayed in place before it sublimated and found a characteristic residence time of 2–3 days. This means that most of the ice changes its phase from solid to vapor and back many times in a seasonal snowpack where similar temperature conditions can be found. Consistent with such a short timescale, we observed a mass turnover of up to 60% of the total ice mass per day. The concept of hand-to-hand transport for the water vapor flux describes the observed changes very well. However, we did not find evidence for a macroscopic vapor diffusion enhancement. The picture of {temperature gradient metamorphism} produced by directly observing the changing microstructure sheds light on the micro-physical processes and could help to improve models that predict the physical properties of snow.
Finding relevant microstructural parameters beyond density is a longstanding problem which hinders the formulation of accurate parameterizations of physical properties of snow. Towards a remedy, we ...address the effective thermal conductivity tensor of snow via anisotropic, second-order bounds. The bound provides an explicit expression for the thermal conductivity and predicts the relevance of a microstructural anisotropy parameter Q, which is given by an integral over the two-point correlation function and unambiguously defined for arbitrary snow structures. For validation we compiled a comprehensive data set of 167 snow samples. The set comprises individual samples of various snow types and entire time series of metamorphism experiments under isothermal and temperature gradient conditions. All samples were digitally reconstructed by micro-computed tomography to perform microstructure-based simulations of heat transport. The incorporation of anisotropy via Q considerably reduces the root mean square error over the usual density-based parameterization. The systematic quantification of anisotropy via the two-point correlation function suggests a generalizable route to incorporate microstructure into snowpack models. We indicate the inter-relation of the conductivity to other properties and outline a potential impact of Q on dielectric constant, permeability and adsorption rate of diffusing species in the pore space.
The shortage of information on snow properties in high latitudes
places a major limitation on permafrost and more generally climate modelling.
A dedicated field program was therefore carried out to ...investigate snow
properties and their spatial variability at a polygonal tundra permafrost
site. Notably, snow samples were analysed for surface-normal thermal
conductivity (Keff−z) based on X-ray microtomography. Also, the
detailed snow model SNOWPACK was adapted to these Arctic conditions to enable
relevant simulations of the ground thermal regime. Finally, the sensitivity
of soil temperatures to snow spatial variability was analysed. Within a typical tundra snowpack composed of depth hoar overlain by wind
slabs, depth hoar samples were found more conductive (Keff-z=0.22±0.05 W m−1 K−1) than in most previously published
studies, which could be explained by their high density and microstructural
anisotropy. Spatial variations in the thermal properties of the snowpack were
well explained by the microtopography and ground surface conditions of the
polygonal tundra, which control depth hoar growth and snow accumulation. Our
adaptations to SNOWPACK, phenomenologically taking into account the effects
of wind compaction, basal vegetation, and water vapour flux, yielded realistic
density and Keff−z profiles that greatly improved simulations
of the ground thermal regime. Also, a density- and anisotropy-based
parameterization for Keff−z lead to further slight
improvements. Soil temperatures were found to be particularly sensitive to
snow conditions during the early winter and polar night, highlighting the
need for improved snow characterization and modelling over this period.
Isothermal snow metamorphism is based on the fundamental process of sintering. However, the relative weights of the physical processes responsible for sintering between ice grains are still debated. ...The most active are expected to be grain boundary diffusion or sublimation‐condensation. We performed four isothermal experiments, starting with fresh snow, at temperatures of −1.6, −8.3, −19.1, and −54 °C during nearly 1 year. Monthly, we imaged the snow samples by X‐ray microtomography. We monitored the changes in density, specific surface area, structure model index, and several structural parameters based on the distance transform of the ice matrix and pore space in the snow, as the trabecular number and thickness. At −54 °C, the metamorphism process was very slow, and during 1 year the specific surface area decreased by only 19%. For the other samples, the results can be interpreted as a two‐stage process with a first phase of rapid change in trabecular number and structure model index and a second phase where the trabecular number and structure model index were constant. An increase in density and trabecular thickness together with a decrease of the specific surface area following a power law were observed throughout the experiments. The increase in ice thickness (coarsening) related linearly to the densification. The continuous densification implies that volume processes like grain boundary diffusion have to occur. The linear relation between densification and coarsening suggests that the same mechanism governs both processes. The logarithmic decrease of the specific surface area is an indication that the coarsening is rate limiting.
Microtomography can measure the X-ray attenuation coefficient in a 3-D volume of snow with a spatial resolution of a few microns. In order to extract quantitative characteristics of the ...microstructure, such as the specific surface area (SSA), from these data, the greyscale image first needs to be segmented into a binary image of ice and air. Different numerical algorithms can then be used to compute the surface area of the binary image. In this paper, we report on the effect of commonly used segmentation and surface area computation techniques on the evaluation of density and specific surface area. The evaluation is based on a set of 38 X-ray tomographies of different snow samples without impregnation, scanned with an effective voxel size of 10 and 18 μm. We found that different surface area computation methods can induce relative variations up to 5 % in the density and SSA values. Regarding segmentation, similar results were obtained by sequential and energy-based approaches, provided the associated parameters were correctly chosen. The voxel size also appears to affect the values of density and SSA, but because images with the higher resolution also show the higher noise level, it was not possible to draw a definitive conclusion on this effect of resolution.
Laboratory-based, experimental data for the microstructural evolution of new snow are scarce, though applications would benefit from a quantitative characterization of the main influences. To this ...end, we have analyzed the metamorphism and concurrent densification of new snow under isothermal conditions by means of X-ray microtomography and compiled a comprehensive data set of 45 time series. In contrast to previous measurements on isothermal metamorphism on time scales of weeks to months, we analyzed the initial 24–48 h of snow evolution at a high temporal resolution of 3 hours. The data set comprised natural and laboratory-grown snow, and experimental conditions included systematic variations of overburden stress, temperature and crystal habit to address the main influences on specific surface area (SSA) decrease rate and densification rate in a snowpack. For all conditions, we found a linear relation between density and SSA, indicating that metamorphism has an immediate influence for the densification of new snow. The slope of the linear relation, however, depends on the other parameters which were analyzed individually to derive a best-fit parameterization for the SSA decrease rate and densification rate. In the investigated parameter range, we found that the initial value of the SSA constituted the main morphological influence on the SSA decrease rate. In turn, the SSA decrease rate constituted the main influence on the densification rate.
The first hydrometeor classification technique based on two-dimensional video disdrometer (2DVD) data is presented. The method provides an estimate of the dominant hydrometeor type falling over time ...intervals of 60 s during precipitation, using the statistical behavior of a set of particle descriptors as input, calculated for each particle image. The employed supervised algorithm is a support vector machine (SVM), trained over 60 s precipitation time steps labeled by visual inspection. In this way, eight dominant hydrometeor classes can be discriminated. The algorithm achieved high classification performances, with median overall accuracies (Cohen's K) of 90% (0.88), and with accuracies higher than 84% for each hydrometeor class.
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