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The snow thermodynamic multi-layer model SNOWPACK was developed to address the risk of avalanches by simulating the vertical properties of snow. Risk and stability assessments are based on the simulation of the vertical variability of snow microstructure, as well as on snow cohesion parameters. Previous research has shown systematic error in grain size simulations (equivalent optical grain size) over several areas in northern Canada. To quantify the simulated errors in snow grain size and uncertainties in stability, the snow specific surface area (SSA) was measured with a laser-based instrument. Optical grain size was retrieved to validate the optical equivalent grain radius from SNOWPACK. The two study plots are located in Glacier National Park, BC, and Jasper National Park, AB, Canada. Profiles for density and stratigraphic analysis were obtained as well as grain size profiles, combined with snow micropenetrometer (SMP) measurements. Density analysis showed good agreement with the simulated values (R2 = 0.76). Optical grain size analysis showed systematic overestimation of the modeled values, in agreement with the current literature. The error in SSA evolution for a rounding environment was mostly constant, whereas error for conditions driven by a temperature gradient was linked to the size of the facetted grains.  相似文献   
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Abstract

As interest in outdoor activities in remote areas is increasing, there is a strong need for improved avalanche forecasting at the regional scale. Due to important logistical and safety matters, avalanche terrain measurements (avalanche observations, snowpack profiles, and stability tests) are not always possible for practitioners/forecasters. An interesting alternative would be to analyze the snowpack without these challenges by using snow model outputs. The SNOWPACK model is currently used operationally for avalanche forecasting and research in the Swiss Alps. Thus, this paper presents a summary of analyses that have been conducted to assess the potential of using the SNOWPACK model driven with both in-situ and forecasted meteorological data in three different Canadian climate and geomorphological contexts. A comparison of meteorological data from in-situ and predicted datasets for two winters shows that the GEMLAM weather model is the most accurate for the three climatic contexts of this project, but also showed a bias proportional to precipitation intensity/rate. Snow simulations forced with GEMLAM are the closest to field measurements. Finally, predictions of persistent weak layers have been validated using the InfoEx platform from Avalanche Canada. Crust and surface hoar formation dates agree with the information reported in InfoEx.  相似文献   
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Cepheids are key to establishing the cosmic distance scale. Therefore it’s important to assess the viability of QZ Nor, V340 Nor, and GU Nor as calibrators for Leavitt’s law via their purported membership in the open cluster NGC 6067. The following suite of evidence confirms that QZ Nor and V340 Nor are members of NGC 6067, whereas GU Nor likely lies in the foreground: (i) existing radial velocities for QZ Nor and V340 Nor agree with that established for the cluster ( $-39.4\pm0.2(\sigma_{\bar {x}}) \pm1.2 (\sigma)~\mbox{km/s}$ ) to within 1 km/s, whereas GU Nor exhibits a markedly smaller value; (ii) a steep velocity-distance gradient characterizes the sight-line toward NGC 6067, thus implying that objects sharing common velocities are nearly equidistant; (iii) a radial profile constructed for NGC 6067 indicates that QZ Nor is within the cluster bounds, despite being 20′ from the cluster center; (iv) new BVJH photometry for NGC 6067 confirms the cluster lies d=1.75±0.10 kpc distant, a result that matches Wesenheit distances computed for QZ Nor/V340 Nor using the Benedict et al. (Astron. J. 133:1810, 2007, HST parallaxes) calibration. QZ Nor is a cluster Cepheid that should be employed as a calibrator for the cosmic distance scale.  相似文献   
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