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Faillettaz J.,University of Zurich | 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.

Macelloni G.,CNR Institute of Applied Physics Nello Carrara | Brogioni M.,CNR Institute of Applied Physics Nello Carrara | Pettinato S.,CNR Institute of Applied Physics Nello Carrara | Montomoli F.,CNR Institute of Applied Physics Nello Carrara | Monti F.,Institute for Snow and Avalanche Research SLF
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2013

In recent decades, with the development of low-frequency missions such as SMOS and Aquarius, which have a large antenna, the need has arisen to find stable areas for the external calibration of L-band radiometers. 'Cold sky' and 'calm ocean' are routinely used as low reference temperatures, and Antarctica, in particular the East Antarctic Plateau, has been investigated in recent years as a potential candidate for higher reference temperatures. The reason for this interest lies in its geographical location (it can be seen several times a day by polar-orbiting satellites), as well as in the size, structure, spatial homogeneity, and thermal stability of this area. In particular the area of Dome-C, where the Italian-French base is located, was monitored in the past years using ground based radiometer and satellite data. Data acquired in new experiment, started in 2012, are described in the present study together to an analysis of SMOS data collected in the same area. The results pointed out that the brightness temperature over that region is very stable both in space and time and have individuated a large area able to contain several footprints of space-borne radiometers and thus is suitable for cross calibration between the sensors. © 2013 IEEE.

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.

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).

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).

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