Preliminary Results of Research on Snow and Avalanches in Czechoslovakia

1957 ◽  
Vol 3 (21) ◽  
pp. 72-77
Author(s):  
Miloš Vrba ◽  
Bedřich Urbánek
Keyword(s):  
Thermal Properties ◽  
Snow Cover ◽  
Penetration Resistance ◽  
Preliminary Results ◽  
Avalanche Danger

AbstractThis paper gives a brief account of the results so far obtained in research in Czechoslovakia on the crystallographic, stratigraphical and thermal properties of snow cover, and the use of these data in avalanche investigations. Avalanche danger is predicted by comparing the penetration resistance of snow layers, measured with a rammsonde, with resistance graphs of typical avalanche situations.

Preliminary Results of Research on Snow and Avalanches in Czechoslovakia

1957 ◽  
Vol 3 (21) ◽  
pp. 72-77
Author(s):  
Miloš Vrba ◽  
Bedřich Urbánek
Keyword(s):  
Thermal Properties ◽  
Snow Cover ◽  
Penetration Resistance ◽  
Preliminary Results ◽  
Avalanche Danger

Abstract This paper gives a brief account of the results so far obtained in research in Czechoslovakia on the crystallographic, stratigraphical and thermal properties of snow cover, and the use of these data in avalanche investigations. Avalanche danger is predicted by comparing the penetration resistance of snow layers, measured with a rammsonde, with resistance graphs of typical avalanche situations.

scholarly journals Brief communication "Application of mobile laser scanning in snow cover profiling"

2011 ◽  
Vol 5 (1) ◽  
pp. 135-138 ◽  
Author(s):  
S. Kaasalainen ◽  
H. Kaartinen ◽  
A. Kukko ◽  
K. Anttila ◽  
A. Krooks
Keyword(s):  
Change Detection ◽  
Snow Cover ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Mobile Mapping ◽  
Preliminary Results ◽  
Geodetic Institute ◽  
Mapping System ◽  
Mobile Mapping System

Abstract. We present a snowmobile-based mobile mapping system and its first application to snow cover roughness and change detection measurement. The ROAMER mobile mapping system, constructed at the Finnish Geodetic Institute, consists of the positioning and navigating systems, a terrestrial laser scanner, and the carrying platform (a snowmobile sledge in this application). We demonstrate the applicability of the instrument to snow cover roughness profiling and change detection by presenting preliminary results from a mobile laser scanning (MLS) campaign. The results show the potential of MLS for fast and efficient snow profiling from large areas in a millimetre scale.

Reconnaissance for noble metals in Precambrian and Palaeogene rocks, Amdrup Fjord, southern East Greenland

2001 ◽  
pp. 76-80
Author(s):  
Bjørn Thomassen ◽  
Johan Ditlev Krebs
Keyword(s):  
Snow Cover ◽  
Major Part ◽  
Noble Metals ◽  
Field Work ◽  
High Mountain ◽  
East Greenland ◽  
Original Series ◽  
Preliminary Results ◽  
Hydrothermal Veins ◽  
Gold Bearing

NOTE: This article was published in a former series of GEUS Bulletin. Please use the original series name when citing this article, for example: Thomassen, B., & Krebs, J. D. (2001). Reconnaissance for noble metals in Precambrian and Palaeogene rocks, Amdrup Fjord, southern East Greenland. Geology of Greenland Survey Bulletin, 189, 76-80. https://doi.org/10.34194/ggub.v189.5161 _______________ A zone of hydrothermal veins in the Kangerlussuaq region, southern East Greenland, is the focus of a oneyear project by the Geological Survey of Denmark and Greenland (GEUS). The project aims to localise, map, sample and analyse silver-gold-bearing veins in a selected area of Precambrian and Palaeogene rocks north of Amdrup Fjord (Figs 1, 2). This report describes the field work and presents some preliminary results. The study area comprises a c. 3 km wide and 10 km long ridge between Amdrup Fjord and Søndre Syenitgletscher, centred on the 938 m high mountain Flammefjeld (Figs 2, 3). The area is of alpine character with small glaciers and with extensive snow cover most of the year. The field programme was chosen to coincide with the time of minimum snow cover, from 25 July – 23 August. During this period, the major part of the area was investigated on daily foot traverses from four fly camps, helped by helicopter lifts on two occasions. Logistically, the work was part of a larger expedition to East Greenland – EG 2000 – organised by the Danish Lithosphere Centre and GEUS, which is reported on elsewhere (Nielsen et al. 2001, this volume). A temporary field base in Sødalen, some 50 km east of Amdrup Fjord, supported the expedition’s Ecureuil AS 350 helicopter and provided services for the field teams of the various activities attached to EG 2000. Air connections with Iceland were maintained by Twin Otter aircraft operating from a gravel landing strip in Sødalen (Fig. 1).

scholarly journals Brief communication "Application of mobile laser scanning in snow cover profiling"

2010 ◽  
Vol 4 (4) ◽  
pp. 2513-2522 ◽  
Author(s):  
S. Kaasalainen ◽  
H. Kaartinen ◽  
A. Kukko ◽  
K. Anttila ◽  
A. Krooks
Keyword(s):  
Change Detection ◽  
Snow Cover ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Mobile Mapping ◽  
Preliminary Results ◽  
Geodetic Institute ◽  
Mapping System ◽  
Mobile Mapping System

Abstract. We present a snowmobile based mobile mapping system and its first application on snow cover roughness and change detection measurement. The ROAMER mobile mapping system, constructed at the Finnish Geodetic Institute, consists of the positioning and navigating systems, a terrestrial laser scanner, and the carrying platform (a snowmobile sledge in this application). We demonstrate the applicability of the instrument in snow cover roughness profiling and change detection by presenting preliminary results from a mobile laser scanning (MLS) campaign. The results show the potential of MLS for fast and efficient snow profiling from large areas in a millimetre scale.

scholarly journals Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland

2021 ◽  
Author(s):  
Cristina Pérez-Guillén ◽  
Frank Techel ◽  
Martin Hendrick ◽  
Michele Volpi ◽  
Alec van Herwijnen ◽  
...  
Keyword(s):  
Decision Support ◽  
Snow Cover ◽  
Heterogeneous Data ◽  
Swiss Alps ◽  
Data Driven ◽  
Weather Data ◽  
Data Set ◽  
Snow Conditions ◽  
Danger Level ◽  
Avalanche Danger

Abstract. Even today, the assessment of avalanche danger is by large a subjective, yet data-based decision-making process. Human experts analyze heterogeneous data volumes, diverse in scale, and conclude on the avalanche scenario based on their experience. Nowadays, modern machine learning methods and the rise in computing power in combination with physical snow cover modelling open up new possibilities for developing decision support tools for operational avalanche forecasting. Therefore, we developed a fully data-driven approach to predict the regional avalanche danger level, the key component in public avalanche forecasts, for dry-snow conditions in the Swiss Alps. Using a large data set of more than 20 years of meteorological data measured by a network of automated weather stations, which are located at the elevation of potential avalanche starting zones, and snow cover simulations driven with these input weather data, we trained two random forest (RF) classifiers. The first classifier (RF #1) was trained relying on the forecast danger levels published in the avalanche bulletin. Given the uncertainty related to a forecast danger level as a target variable, we trained a second classifier (RF #2), relying on a quality-controlled subset of danger level labels. We optimized the RF classifiers by selecting the best set of input features combining meteorological variables and features extracted from the simulated profiles. The accuracy of the danger level predictions ranged between 74 % and 76 % for RF #1, and between 72 % and 78 % for RF #2, with both models achieving better performance than previously developed methods. To assess the accuracy of the forecast, and thus the quality of our labels, we relied on nowcast assessments of avalanche danger by well-trained observers. The performance of both models was similar to the accuracy of the current experience-based Swiss avalanche forecasts (which is estimated to 76 %). The models performed consistently well throughout the Swiss Alps, thus in different climatic regions, albeit with some regional differences. A prototype model with the RF classifiers was already tested in a semi-operational setting by the Swiss avalanche warning service during the winter 2020-2021. The promising results suggest that the model may well have potential to become a valuable, supplementary decision support tool for avalanche forecasters when assessing avalanche hazard.

scholarly journals Spatial variability of micropenetration resistance in snow layers on a small slope

2004 ◽  
Vol 38 ◽  
pp. 202-208 ◽  
Author(s):  
Kalle Kronholm ◽  
Martin Schneebeli ◽  
Jürg Schweizer
Keyword(s):  
Spatial Variability ◽  
Spatial Variation ◽  
Snow Cover ◽  
Three Dimensional ◽  
Penetration Resistance ◽  
Snow Layer ◽  
Depositional Processes ◽  
Layer Deposition ◽  
Buried Layer ◽  
Linear Trends

AbstractThe mechanisms leading to dry-snow slab release are influenced by the three-dimensional variability of the snow cover. We measured 113 profiles of penetration resistance with a snow micropenetrometer on an alpine snow slope. Seven distinct layers were visually identified in all snow micropenetrometer profiles. The penetration resistance of adjacent layers did not change abruptly, but gradually across layer boundaries that were typically 2 mm thick. In two layers, penetration resistance varied around 200% over the grid, possibly due to wind effects during or after layer deposition. Penetration resistance varied around 25%in five layers. Statistically significant slope-scale linear trends were found for all layers. The semivariogram was used to describe the spatial variation. Penetration resistance was autocorrelated, but the scale of variation was layer-specific. A buried layer of surface hoar was the most critical weak layer. It had little spatial variation. The layers in the slab above had higher spatial variation. The penetration resistance of each snow layer had distinct geostatistical properties, caused by the depositional processes.

A random forest model to assess snow instability from simulated snow stratigraphy

2021 ◽  
Author(s):  
Stephanie Mayer ◽  
Alec van Herwijnen ◽  
Jürg Schweizer
Keyword(s):  
Random Forest ◽  
Snow Cover ◽  
Input Data ◽  
Weather Prediction ◽  
Classification Model ◽  
Weak Layer ◽  
Snow Stratigraphy ◽  
Meteorological Input ◽  
Weather Stations ◽  
Avalanche Danger

<p>Numerical snow cover models enable simulating present or future snow stratigraphy based on meteorological input data from automatic weather stations, numerical weather prediction or climate models. To assess avalanche danger for short-term forecasts or with respect to long-term trends induced by a warming climate, modeled snow stratigraphy has to be interpreted in terms of mechanical instability. Several instability metrics describing the mechanical processes of avalanche release have been implemented into the detailed snow cover model SNOWPACK. However, there exists no readily available method that combines these metrics to predict snow instability.</p><p>To overcome this issue, we compared a comprehensive dataset of almost 600 manual snow profiles with SNOWPACK simulations. The manual profiles were observed in the region of Davos over 17 different winter seasons and include a Rutschblock stability test as well as a local assessment of avalanche danger. To simulate snow stratigraphy at the locations of the manual profiles, we interpolated meteorological input data from a network of automatic weather stations. For each simulated profile, we manually determined the layer corresponding to the weakest layer indicated by the Rutschblock test in the corresponding observed snow profile. We then used the subgroups of the most unstable and the most stable profiles to train a random forest (RF) classification model on the observed stability described by a binary target variable (unstable vs. stable).</p><p>As potential explanatory variables, we considered all implemented stability indices calculated for the manually picked weak layers in the simulated profiles as well as further weak layer and slab properties (e.g. weak layer grain size or slab density).  After selecting the six most decisive features and tuning the hyper-parameters of the RF, the model was able to distinguish between unstable and stable profiles with a five-fold cross-validated accuracy of 88%.</p><p>Our RF model provides the probability of instability (POI) for any simulated snow layer given the features of this layer and the overlying slab. Applying the RF model to each layer of a complete snow profile thus enables the detection of the most unstable layers by considering the local maxima of the POI among all layers of the profile. To analyze the evolution of snow instability over a complete winter season, the RF model can provide the daily maximal POI values for a time series of snow profiles. By comparing this series of POI values with observed avalanche activity, the RF model can be validated.</p><p>The resulting statistical model is an important step towards exploiting numerical snow cover models for snow instability assessment.</p>

scholarly journals Variations in snow surface properties at the snowpack-depth, the slope and the basin scale

2008 ◽  
Vol 54 (188) ◽  
pp. 846-856 ◽  
Author(s):  
Jürg Schweizer ◽  
Achim Heilig ◽  
Sascha Bellaire ◽  
Charles Fierz
Keyword(s):  
Snow Cover ◽  
Surface Properties ◽  
Penetration Resistance ◽  
Snow Surface ◽  
Tree Line ◽  
Multi Scale ◽  
Basin Scale ◽  
Depth Scale ◽  
Snowpack Properties ◽  
Avalanche Formation

AbstractVariations of snow surface and snowpack properties affect avalanche formation. In up to four north-facing slopes above the tree line near Davos, Switzerland, snow surface properties were characterized. Penetration resistance was measured with a snow micro-penetrometer. The sampling scheme was designed to allow a multi-scale approach covering the snowpack depth scale (0.5–5 m), the slope scale (5–100 m) and the basin scale (100–1000 m). Observations and measurements were compared to the data of a nearby automatic weather station (AWS). The AWS data were also used to model snow-cover stratigraphy and its evolution with the numerical snow-cover model SNOWPACK. Comparing the four slopes showed that surface properties observed manually were similar among the three slopes that were sheltered, and often different from the slope that was wind-exposed. However, the penetration resistance of the surface layer was in most cases significantly different among slopes, although most values were <0.1 N, indicating very low hardness. These seemingly contradictory results follow from the different measurement support of the two methods. It is presently unclear which amount of variation at a given scale is relevant for avalanche formation. The geostatistical analysis and an analysis aimed at identifying the causes of variability were not conclusive. No patterns emerged that would allow conclusions regarding the effect on avalanche formation. Finding the causes of variability seems to require high-resolution terrain and weather models that are presently not readily available.

Selection, Shaping and Thermal Analysis of Y2Fe17-xCox Series for Magnetocaloric Heat Conversion

2016 ◽  
Vol 257 ◽  
pp. 68-71 ◽  
Author(s):  
Alexy Dianoux ◽  
Cyril Rado ◽  
Florence Servant ◽  
Yves Jannot ◽  
Thomas Mazet
Keyword(s):  
Thermal Analysis ◽  
Thermal Properties ◽  
Powder Metallurgy ◽  
Composition Dependence ◽  
Sintered Material ◽  
Industrial Scale ◽  
Preliminary Results ◽  
Decisive Influence ◽  
Magnetocaloric Properties

In this work, we first present the composition dependence of the magnetocaloric properties in the Y2Fe17-xCox series.Then, we show preliminary results on our shaping works. In order to use the Y2Fe17-xCox compounds in magnetocaloric heat conversion systems, we applied powder metallurgy technics at a semi industrial scale to shape it. That involves milling, sintering, and heat treatments.Finally, the emphasis has been laid on the thermal properties of the sintered material, considering their decisive influence on the performance of the system.

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