Proksch M.,Institute for Snow and Avalanche Research SLF |
Proksch M.,University of Innsbruck |
Rutter N.,Northumbria University |
Fierz C.,Institute for Snow and Avalanche Research SLF |
Schneebeli M.,Institute for Snow and Avalanche Research SLF
Cryosphere | Year: 2016
Density is a fundamental property of porous media such as snow. A wide range of snow properties and physical processes are linked to density, but few studies have addressed the uncertainty in snow density measurements. No study has yet quantitatively considered the recent advances in snow measurement methods such as micro-computed tomography (μCT) in alpine snow. During the MicroSnow Davos 2014 workshop, different approaches to measure snow density were applied in a controlled laboratory environment and in the field. Overall, the agreement between μCT and gravimetric methods (density cutters) was 5 to 9 %, with a bias of-5 to 2 %, expressed as percentage of the mean μCT density. In the field, density cutters overestimate (1 to 6 %) densities below and underestimate (1 to 6 %) densities above a threshold between 296 to 350 kg m-3, dependent on cutter type. Using the mean density per layer of all measurement methods applied in the field (μCT, box, wedge, and cylinder cutters) and ignoring ice layers, the variation between the methods was 2 to 5% with a bias of-1 to 1 %. In general, our result suggests that snow densities measured by different methods agree within 9 %. However, the density profiles resolved by the measurement methods differed considerably. In particular, the millimeter-scale density variations revealed by the high-resolution μCT contrasted the thick layers with sharp boundaries introduced by the observer. In this respect, the unresolved variation, i.e., the density variation within a layer which is lost by lower resolution sampling or layer aggregation, is critical when snow density measurements are used in numerical simulations. © 2016 Author(s).
Klein T.,University of Basel |
Klein T.,Institute of Soil, Water and Environmental Sciences |
Vitasse Y.,University of Neuchatel |
Vitasse Y.,Swiss Federal Institute of forest |
And 2 more authors.
Tree Physiology | Year: 2016
In deciduous trees growing in temperate forests, bud break and growth in spring must rely on intrinsic carbon (C) reserves. Yet it is unclear whether growth and C storage occur simultaneously, and whether starch C in branches is suffcient for refoliation. To test in situ the relationships between growth, phenology and C utilization, we monitored stem growth, leaf phenology and stem and branch nonstructural carbohydrate (NSC) dynamics in three deciduous species: Carpinus betulus L., Fagus sylvatica L. and Quercus petraea (Matt.) Liebl. To quantify the role of NSC in C investment into growth, a C balance approach was applied. Across the three species, >95% of branchlet starch was consumed during bud break, confrming the importance of C reserves for refoliation in spring. The C balance calculation showed that 90% of the C investment in foliage (7.0-10.5 kg tree-1 and 5-17 times the C needed for annual stem growth) was explained by simultaneous branchlet starch degradation. Carbon reserves were recovered sooner than expected, after leaf expansion, in parallel with stem growth. Carpinus had earlier leaf phenology (by ∼25 days) but delayed cambial growth (by ∼15 days) than Fagus and Quercus, the result of a competitive strategy to flush early, while having lower NSC levels. © 2016 The Author. Published by Oxford University Press.
Lowe H.,Institute for Snow and Avalanche Research SLF |
Picard G.,University Grenoble Alpes |
Picard G.,French National Center for Scientific Research
Cryosphere | Year: 2015
The description of snow microstructure in microwave models is often simplified to facilitate electromagnetic calculations. Within dense media radiative transfer (DMRT), the microstructure is commonly described by sticky hard spheres (SHS). An objective mapping of real snow onto SHS is however missing which prevents measured input parameters from being used for DMRT. In contrast, the microwave emission model of layered snowpacks (MEMLS) employs a conceptually different approach, based on the two-point correlation function which is accessible by tomography. Here we show the equivalence of both electromagnetic approaches by reformulating their microstructural models in a common framework. Using analytical results for the two-point correlation function of hard spheres, we show that the scattering coefficient in both models only differs by a factor which is close to unity, weakly dependent on ice volume fraction and independent of other microstructural details. Additionally, our analysis provides an objective retrieval method for the SHS parameters (diameter and stickiness) from tomography images. For a comprehensive data set we demonstrate the variability of stickiness and compare the SHS diameter to the optical equivalent diameter. Our results confirm the necessity of a large grain-size scaling when relating both diameters in the non-sticky case, as previously suggested by several authors. © 2015 Author(s).
Leinss S.,ETH Zurich |
Lowe H.,Institute for Snow and Avalanche Research SLF |
Proksch M.,Institute for Snow and Avalanche Research SLF |
Lemmetyinen J.,Finnish Meteorological Institute |
And 3 more authors.
Cryosphere | Year: 2016
The snow microstructure, i.e., the spatial distribution of ice and pores, generally shows an anisotropy which is driven by gravity and temperature gradients and commonly determined from stereology or computer tomography. This structural anisotropy induces anisotropic mechanical, thermal, and dielectric properties. We present a method based on radio-wave birefringence to determine the depth-averaged, dielectric anisotropy of seasonal snow with radar instruments from space, air, or ground. For known snow depth and density, the birefringence allows determination of the dielectric anisotropy by measuring the copolar phase difference (CPD) between linearly polarized microwaves propagating obliquely through the snowpack. The dielectric and structural anisotropy are linked by Maxwell- Garnett-type mixing formulas. The anisotropy evolution of a natural snowpack in Northern Finland was observed over four winters (2009-2013) with the ground-based radar instrument "SnowScat". The radar measurements indicate horizontal structures for fresh snow and vertical structures in old snow which is confirmed by computer tomographic in situ measurements. The temporal evolution of the CPD agreed in ground-based data compared to space-borne measurements from the satellite TerraSAR-X. The presented dataset provides a valuable basis for the development of new snow metamorphism models which include the anisotropy of the snow microstructure. © Author(s) 2016.
Groot Zwaaftink C.D.,Institute for Snow and Avalanche Research SLF |
Groot Zwaaftink C.D.,Ecole Polytechnique Federale de Lausanne |
Cagnati A.,ARPAV CVA |
Crepaz A.,ARPAV CVA |
And 5 more authors.
Cryosphere | Year: 2013
Antarctic surface snow has been studied by means of continuous measurements and observations over a period of 3 yr at Dome C. Snow observations include solid deposits in form of precipitation, diamond dust, or hoar, snow temperatures at several depths, records of deposition and erosion on the surface, and snow profiles. Together with meteorological data from automatic weather stations, this forms a unique dataset of snow conditions on the Antarctic Plateau. Large differences in snow amounts and density exist between solid deposits measured 1 m above the surface and deposition at the surface. We used the snow-cover model SNOWPACK to simulate the snow-cover evolution for different deposition parameterizations. The main adaptation of the model described here is a new event-driven deposition scheme. The scheme assumes that snow is added to the snow cover permanently only during periods of strong winds. This assumption followed from the comparison between observations of solid deposits and daily records of changes in snow height: solid deposits could be observed on tables 1 m above the surface on 94 out of 235 days (40%) while deposition at the surface occurred on 59 days (25%) during the same period, but both happened concurrently on 33 days (14%) only. This confirms that precipitation is not necessarily the driving force behind non-temporary snow height changes. A comparison of simulated snow height to stake farm measurements over 3 yr showed that we underestimate the total accumulation by at least 33%, when the total snow deposition is constrained by the measurements of solid deposits on tables 1 m above the surface. During shorter time periods, however, we may miss over 50% of the deposited mass. This suggests that the solid deposits measured above the surface and used to drive the model, even though comparable to ECMWF forecasts in its total magnitude, should be seen as a lower boundary. As a result of the new deposition mechanism, we found a good agreement between model results and measurements of snow temperatures and recorded snow profiles. In spite of the underestimated deposition, the results thus suggest that we can obtain quite realistic simulations of the Antarctic snow cover by the introduction of event-driven snow deposition. © 2013 Author(s).
Havens S.,Boise State University |
Marshall H.-P.,Boise State University |
Pielmeier C.,Institute for Snow and Avalanche Research SLF |
Elder K.,Rocky Research
IEEE Transactions on Geoscience and Remote Sensing | Year: 2013
Snow microstructure plays an important role in the remote sensing of snow water equivalent (SWE) for both passive and active microwave radars. The accuracy of microwave SWE retrieval algorithms is sensitive to (usually unknown) changes in microstructure. These algorithms could be improved with high-resolution estimates of microstructural properties by using an advanced instrument such as the Snow Micro Penetrometer (SMP), which measures penetration force at the millimeter scale and is sensitive to microstructure. The SMP can also take full micromechanical measurements at much greater speed and resolution and without observer bias than a traditional snow pit. Previous studies have shown that the snowpack stratigraphy and grain type can be accurately classified with one SMP measurement using basic statistics and classification trees (CTs). For this study, we used basic statistical measures of the penetration force and micromechanical estimates from an SMP inversion algorithm to significantly improve the classification accuracy of grain type and layer discrimination. We applied random forest (RF) techniques to classify three snow grain types (new snow, rounds, and facets) from SMP measurements collected in Switzerland and Grand Mesa, Colorado. RFs performed up to 8% better than single CTs, with overall misclassification errors between 17% and 40%. The coefficient of variation of the penetration force proved to be the most important variable, followed by variables that contain information about grain size like microscale strength and the number of ruptures. © 1980-2012 IEEE.
Faillettaz J.,University of Zürich |
Or D.,ETH Zurich |
Reiweger I.,Institute for Snow and Avalanche Research SLF
Geophysical Research Letters | Year: 2016
A simple method for real-time early warning of gravity-driven rupture that considers both the heterogeneity of natural media and characteristics of acoustic emissions attenuation is proposed. The method capitalizes on codetection of elastic waves emanating from microcracks by multiple and spatially separated sensors. Event codetection is considered as surrogate for large event size with more frequent codetected events marking imminence of catastrophic failure. Using a spatially explicit fiber bundle numerical model with spatially correlated mechanical strength and two load redistribution rules, we constructed a range of mechanical failure scenarios and associated failure events (mapped into acoustic emission) in space and time. Analysis considering hypothetical arrays of sensors and consideration of signal attenuation demonstrate the potential of the codetection principles even for insensitive sensors to provide early warning for imminent global failure. © 2016. American Geophysical Union. All Rights Reserved.
Casteller A.,CONICET |
Casteller A.,Institute for Snow and Avalanche Research SLF |
Villalba R.,CONICET |
Araneo D.,CONICET |
Stockli V.,Institute for Snow and Avalanche Research SLF
Cold Regions Science and Technology | Year: 2011
Snow avalanches recurrently cause substantial damage to infrastructure and losses in human lives in mountainous environments around the world. Densely populated regions have suffered more intensely the destructive forces of avalanches; however, settlers of these regions have developed tools to mitigate avalanche risk, including avalanche hazard maps. To design detailed hazard maps, accurate information on avalanche runout and frequency is necessary. In areas where avalanches are mostly undocumented, like in the Andes, dendrochronological methods become a valuable tool for reconstructing spatio-temporal avalanche patterns. At Lago del Desierto (southern Patagonian Andes, Argentina), trees from nine avalanche tracks were sampled. Nothofagus pumilio, a winter deciduous broad-leaved tree, was sampled in all cases. Avalanche activity is recognized based on the presence of scars, changes in stem eccentricity, reaction wood and abrupt growth changes. A rating system was used to define the relative importance of each tree-ring indicator in the reconstructed chronology of events. According to this chronology, widespread avalanche activity on the slope was found for the years 1918, 1930, 1931, 1971, 1995 and 1998. Superposed Epoch Analysis indicated that total monthly precipitation during the three snowiest months from May to October of 1971, 1995 and 1998 (years for which climatic data exists for validation) was significantly greater than for years without large avalanche activity. In contrast, no significant correlations were found between monthly temperature variations and years with large avalanche activity on the slope. Atmospheric circulation patterns associated with years of major avalanche activity show features typically observed during the cold phase of the El Niño-Southern Oscillation cycle, i.e. La Niña. For those cases, results also show an increase in the westerlies across the South Pacific and southern South America, resulting in both higher precipitation and stronger winds over the study area that favor snow avalanche episodes. We point out the need of a more systematic sampling strategy in order to reconstruct spatial avalanche patterns in the southern Andes, which are a complement of temporal patterns to design hazard maps. © 2011 Elsevier B.V.
Reiweger I.,Institute for Snow and Avalanche Research SLF |
Schweizer J.,Institute for Snow and Avalanche Research SLF
Cryosphere | Year: 2013
Understanding failure initiation within weak snow layers is essential for modeling and predicting dry-snow slab avalanches. We therefore performed laboratory experiments with snow samples containing a weak layer consisting of either faceted crystals or depth hoar. During these experiments the samples were loaded with different loading rates and at various tilt angles until fracture. The strength of the samples decreased with increasing loading rate and increasing tilt angle. Additionally, we took pictures of the side of four samples with a high-speed video camera and calculated the displacement using a particle image velocimetry (PIV) algorithm. The fracture process within the weak layer could thus be observed in detail. Catastrophic failure started due to a shear fracture just above the interface between the depth hoar layer and the underlying crust. © Author(s) 2013. CC Attribution 3.0 License.
Schweizer J.,Institute for Snow and Avalanche Research SLF |
Reuter B.,Institute for Snow and Avalanche Research SLF
Natural Hazards and Earth System Sciences | Year: 2015
Snow slope stability evaluation requires considering weak layer as well as slab properties-and in particular their interaction. We developed a stability index from snow micro-penetrometer (SMP) measurements and compared it to 129 concurrent point observations with the compression test (CT). The index considers the SMP-derived micro-structural strength and the additional load, which depends on the hardness of the surface layers. The new quantitative measure of stability discriminated well between point observations rated as either "poor" or "fair" (CT < 19) and those rated as "good" (CT g¥ 19). However, discrimination power within the intermediate range was low. We then applied the index to gridded snow micro-penetrometer measurements from 11 snow slopes to explore the spatial structure and possibly relate it to slope stability. Stability index distributions on the 11 slopes reflected various possible strength and load (stress) distributions that can naturally occur. Their relation to slope stability was poor, possibly because the index does not consider crack propagation. Hence, the relation between spatial patterns of point stability and slope stability remains elusive. Whereas this is the first attempt of a truly quantitative measure of stability, future developments should consider a better reference of stability and incorporate a measure of crack propagation. © 2015 Author(s).