Seasonal evolution of snow permeability under equi-temperature and temperature-gradient conditions

Abstract. The permeability (K) of snow to air flow affects the transfer of energy, water vapor and chemical species between the snow and the atmosphere. Yet today little is known about the temporal evolution of snow permeability as a function of metamorphic regime. Furthermore, our ability to simulate snow permeability over the seasonal evolution of a snowpack has not been tested. Here we have measured the evolution of snow permeability in a subarctic snowpack subject to high temperature-gradient (TG) metamorphism. We have also measured the evolution of the same snowpack deposited over tables so that it evolved in the equi-temperature (ET) regime. Permeability varies in the range 31 × 10−10 (ET regime) to 650 × 10−10 m2 (TG regime). Permeability increases over time in TG conditions and decreases under ET conditions. Using measurements of density ρ and of specific surface area (SSA), from which the equivalent sphere radius r is determined, we show that the equation linking SSA, density ρ and permeability, K = 3.0 r2 e(−0.013 ρ) (with K in m2, r in m and ρ in kg m−3) obtained in a previous study adequately predicts permeability values. The detailed snowpack model Crocus is used to simulate the physical properties of the TG and ET snowpacks. For the most part, all variables are well reproduced. Simulated permeabilities are up to a factor of two greater than measurements for depth hoar layers, which we attribute to snow microstructure and its aerodynamic properties. Finally, the large difference in permeabilities between ET and TG metamorphic regimes will impact atmosphere-snow energy and mass exchanges. These effects deserve consideration in predicting the effect of climate change on snow properties and snow–atmosphere interactions.

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Seasonal evolution of snow permeability under equi-temperature and temperature-gradient conditions

The Cryosphere Discussions ◽

10.5194/tcd-7-2725-2013 ◽

2013 ◽

Vol 7 (3) ◽

pp. 2725-2759 ◽

Cited By ~ 1

Author(s):

F. Domine ◽

S. Morin ◽

E. Brun ◽

M. Lafaysse

Keyword(s):

Temperature Gradient ◽

Temporal Evolution ◽

Chemical Species ◽

Seasonal Evolution ◽

Snow Properties ◽

Aerodynamic Properties ◽

Equivalent Sphere ◽

Sphere Radius ◽

Snow Microstructure ◽

Over Time

Abstract. The permeability K of snow to air flow affects the transfer of energy, water vapor and chemical species between the snow and the atmosphere. Yet today little is known of the temporal evolution of snow permeability as a function of metamorphic regime. Furthermore, our ability to simulate snow permeability over the seasonal evolution of a snowpack has not been tested. Here we have measured the evolution of snow permeability in a subarctic snowpack subject to high temperature-gradient (TG) metamorphism. We have also measured the evolution of the same snowpack deposited over tables so that it evolved in the equi-temperature (ET) regime. Permeability varies in the range 31 × 10–10 (ET regime) to 650 × 10–10 m2 (TG regime). Permeability increases over time in TG conditions and decreases under ET conditions. Using measurements of density ρ and of specific surface area (SSA), from which the equivalent sphere radius r is determined, we show that the equation linking SSA, density ρ and permeability, K = 3.0 r2 e(–0.013 ρ) (with K in m2, r in m and ρ in kg m−3) obtained in a previous study adequately predicts permeability values. The detailed snowpack model Crocus is used to simulate the physical properties of the TG and ET snowpacks. For the most part, all variables are well reproduced. Simulated permeabilities are up to a factor of two greater than measurements for depth hoar layers, which we attribute to snow microstructure, as the aerodynamic properties of hollow depth hoar crystals are different from those of spheres. Finally, the large difference in permeabilities between ET and TG metamorphic regimes will impact atmosphere-snow energy and mass exchanges and these effects deserve consideration in predicting the effect of climate change on snow properties and snow-atmosphere interactions.

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Glimpse: A Gaze-Based Measure of Temporal Salience

Sensors ◽

10.3390/s21093099 ◽

2021 ◽

Vol 21 (9) ◽

pp. 3099

Author(s):

V. Javier Traver ◽

Judith Zorío ◽

Luis A. Leiva

Keyword(s):

Visual Attention ◽

Computational Models ◽

Temporal Evolution ◽

Temporal Consistency ◽

Visual Salience ◽

Temporal Dimension ◽

Spatial Perspective ◽

Spatio Temporal ◽

Scoring Algorithms ◽

Over Time

Temporal salience considers how visual attention varies over time. Although visual salience has been widely studied from a spatial perspective, its temporal dimension has been mostly ignored, despite arguably being of utmost importance to understand the temporal evolution of attention on dynamic contents. To address this gap, we proposed Glimpse, a novel measure to compute temporal salience based on the observer-spatio-temporal consistency of raw gaze data. The measure is conceptually simple, training free, and provides a semantically meaningful quantification of visual attention over time. As an extension, we explored scoring algorithms to estimate temporal salience from spatial salience maps predicted with existing computational models. However, these approaches generally fall short when compared with our proposed gaze-based measure. Glimpse could serve as the basis for several downstream tasks such as segmentation or summarization of videos. Glimpse’s software and data are publicly available.

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Vapor flux and recrystallization during dry snow metamorphism under a steady temperature gradient as observed by time-lapse micro-tomography

The Cryosphere ◽

10.5194/tc-6-1141-2012 ◽

2012 ◽

Vol 6 (5) ◽

pp. 1141-1155 ◽

Cited By ~ 85

Author(s):

B. R. Pinzer ◽

M. Schneebeli ◽

T. U. Kaempfer

Keyword(s):

Temperature Gradient ◽

Physical Properties ◽

Time Lapse ◽

Phase Changes ◽

External Temperature ◽

Vapor Flux ◽

Snow Metamorphism ◽

Diffusion Enhancement ◽

Micro Tomography ◽

Snow Microstructure

Abstract. 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.

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Study of a temperature gradient metamorphism of snow from 3-D images: time evolution of microstructures, physical properties and their associated anisotropy

The Cryosphere ◽

10.5194/tc-8-2255-2014 ◽

2014 ◽

Vol 8 (6) ◽

pp. 2255-2274 ◽

Cited By ~ 27

Author(s):

N. Calonne ◽

F. Flin ◽

C. Geindreau ◽

B. Lesaffre ◽

S. Rolland du Roscoat

Keyword(s):

Temperature Gradient ◽

Physical Properties ◽

Time Evolution ◽

Three Dimensional ◽

Vertical Direction ◽

Large Set ◽

Correlation Lengths ◽

Snow Properties ◽

Cold Room ◽

Anisotropy Coefficients

Abstract. We carried out a study to monitor the time evolution of microstructural and physical properties of snow during temperature gradient metamorphism: a snow slab was subjected to a constant temperature gradient in the vertical direction for 3 weeks in a cold room, and regularly sampled in order to obtain a series of three-dimensional (3-D) images using X-ray microtomography. A large set of properties was then computed from this series of 3-D images: density, specific surface area, correlation lengths, mean and Gaussian curvature distributions, air and ice tortuosities, effective thermal conductivity, and intrinsic permeability. Whenever possible, specific attention was paid to assess these properties along the vertical and horizontal directions, and an anisotropy coefficient defined as the ratio of the vertical over the horizontal values was deduced. The time evolution of these properties, as well as their anisotropy coefficients, was investigated, showing the development of a strong anisotropic behavior during the experiment. Most of the computed physical properties of snow were then compared with two analytical estimates (self-consistent estimates and dilute beds of spheroids) based on the snow density, and the size and anisotropy of the microstructure through the correlation lengths. These models, which require only basic microstructural information, offer rather good estimates of the properties and anisotropy coefficients for our experiment without any fitting parameters. Our results highlight the interplay between the microstructure and physical properties, showing that the physical properties of snow subjected to a temperature gradient cannot be described accurately using only isotropic parameters such as the density and require more refined information. Furthermore, this study constitutes a detailed database on the evolution of snow properties under a temperature gradient, which can be used as a guideline and a validation tool for snow metamorphism models at the micro- or macroscale.

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Spatial and Temporal Evolution of the Infiltration Characteristics of a Loess Landslide

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9010026 ◽

2020 ◽

Vol 9 (1) ◽

pp. 26 ◽

Cited By ~ 2

Author(s):

Dongdong Yang ◽

Haijun Qiu ◽

Yanqian Pei ◽

Sheng Hu ◽

Shuyue Ma ◽

...

Keyword(s):

Slope Stability ◽

Slope Failure ◽

Temporal Evolution ◽

Infiltration Rate ◽

Middle Part ◽

Loess Landslide ◽

Infiltration Rates ◽

Disturbed Soil ◽

Landslide Body ◽

Over Time

Infiltration plays an important role in influencing slope stability. However, the influences of slope failure on infiltration and the evolution of infiltration over time and space remain unclear. We studied and compared the infiltration rates in undisturbed loess and disturbed loess in different years and at different sites on loess landslide bodies. The results showed that the average initial infiltration rate in a new landslide body (triggered on 11 October 2017) were dramatically higher than those in a previous landslide body (triggered on 17 September 2011) and that the infiltration rates of both landslide types were higher than the rate of undisturbed loess. The initial infiltration rate in the new landslide body sharply decreased over the 4–5 months following the landslide because of the appearance of physical crusts. Our observations indicated that the infiltration rate of the disturbed soil in a landslide evolved over time and that the infiltration rate gradually approached that of undisturbed loess. Furthermore, in the undisturbed loess, both the initial and quasi-steady infiltration rates were slightly higher in the loess than in the paleosol, and in the previous landslide body, the infiltration rate was highest in the upper part, intermediate in the middle part, and lowest in the lower part. This study can help us to better understand the evolution process of infiltration in undisturbed loess, previous landslides, and new landslides.

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SMRT: an active–passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0)

Geoscientific Model Development ◽

10.5194/gmd-11-2763-2018 ◽

2018 ◽

Vol 11 (7) ◽

pp. 2763-2788 ◽

Cited By ~ 19

Author(s):

Ghislain Picard ◽

Melody Sandells ◽

Henning Löwe

Keyword(s):

Radiative Transfer ◽

Thermal Emission ◽

Electromagnetic Properties ◽

Radiative Transfer Model ◽

Transfer Model ◽

Hard Sphere Model ◽

Snow Layer ◽

Mathematical Basis ◽

Snow Properties ◽

Snow Microstructure

Abstract. The Snow Microwave Radiative Transfer (SMRT) thermal emission and backscatter model was developed to determine uncertainties in forward modeling through intercomparison of different model ingredients. The model differs from established models by the high degree of flexibility in switching between different electromagnetic theories, representations of snow microstructure, and other modules involved in various calculation steps. SMRT v1.0 includes the dense media radiative transfer theory (DMRT), the improved Born approximation (IBA), and independent Rayleigh scatterers to compute the intrinsic electromagnetic properties of a snow layer. In the case of IBA, five different formulations of the autocorrelation function to describe the snow microstructure characteristics are available, including the sticky hard sphere model, for which close equivalence between the IBA and DMRT theories has been shown here. Validation is demonstrated against established theories and models. SMRT was used to identify that several former studies conducting simulations with in situ measured snow properties are now comparable and moreover appear to be quantitatively nearly equivalent. This study also proves that a third parameter is needed in addition to density and specific surface area to characterize the microstructure. The paper provides a comprehensive description of the mathematical basis of SMRT and its numerical implementation in Python. Modularity supports model extensions foreseen in future versions comprising other media (e.g., sea ice, frozen lakes), different scattering theories, rough surface models, or new microstructure models.

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Spatio-temporal evolution of thin Alfven resonance layer

Journal of Plasma Physics ◽

10.1017/s002237781000022x ◽

2010 ◽

Vol 76 (5) ◽

pp. 709-734

Author(s):

I. S. DMITRIENKO

Keyword(s):

Large Scale ◽

Temporal Evolution ◽

Spatial Structures ◽

One Dimensional ◽

Resonance Detuning ◽

Different Types ◽

Temporal Structures ◽

Spatio Temporal ◽

Over Time ◽

Resonance Equation

AbstractWe describe the spatio-temporal evolution of one-dimensional Alfven resonance disturbance in the presence of various factors of resonance detuning: dispersion and absorption of Alfven disturbance, nonstationarity of large-scale wave generating resonant disturbance. Using analytical solutions to the resonance equation, we determine conditions for forming qualitatively different spatial and temporal structures of resonant Alfven disturbances. We also present analytical descriptions of quasi-stationary and non-stationary spatial structures formed in the resonant layer, and their evolution over time for cases of drivers of different types corresponding to large-scale waves localized in the direction of inhomogeneity and to nonlocalized large-scale waves.

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Study of a temperature gradient metamorphism of snow from 3-D images: time evolution of microstructures, physical properties and their associated anisotropy

The Cryosphere Discussions ◽

10.5194/tcd-8-1407-2014 ◽

2014 ◽

Vol 8 (1) ◽

pp. 1407-1451 ◽

Cited By ~ 5

Author(s):

N. Calonne ◽

F. Flin ◽

C. Geindreau ◽

B. Lesaffre ◽

S. Rolland du Roscoat

Keyword(s):

Temperature Gradient ◽

Physical Properties ◽

Time Evolution ◽

Analytical Models ◽

Correlation Lengths ◽

Snow Properties ◽

Cold Room ◽

Macro Scale ◽

Validation Tool ◽

Anisotropy Coefficients

Abstract. We carried out a study to monitor the time evolution of microstructural and physical properties of snow during a temperature gradient metamorphism: a snow slab was subjected to a constant temperature gradient along the vertical during three weeks in a cold-room, and regularly sampled in order to obtain a set of 3-D images using X-ray microtomography. A large panel of properties was then computed from this series of 3-D images: density, specific surface area, correlation length, mean and Gaussian curvature distributions, air and ice tortuosities, effective thermal conductivity, and intrinsic permeability. Whenever possible, a specific attention was paid to assess these properties along the vertical and horizontal directions, and an anisotropy coefficient defined as the ratio of the vertical over the horizontal values was deduced. The time evolution of these properties, as well as their anisotropy coefficients, was investigated, showing the development of a strong anisotropic behavior during the experiment. Most of the computed physical properties of snow were then compared with two analytical models (Self consistent estimates and Dilutes bed of spheroids) based on the snow density, and the size and anisotropy of the grains through the correlation lengths. These models, which require only basic microstructural information, offer rather good estimates of the properties and anisotropy coefficients for our experiment without any fitting parameters. Our results highlight the interplay between the microstructure and physical properties, showing that the physical properties of snow subjected to a temperature gradient cannot be described accurately using only isotropic parameters such as the density and require more refined information. Furthermore, this study constitutes a detailed database on the evolution of snow properties under a temperature gradient, which can be used as a guideline and a validation tool for snow metamorphism models at the micro or macro scale.

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Orientation selective grain sublimation-deposition in snow under temperature gradient metamorphism observed with Diffraction Contrast Tomography

10.5194/tc-2021-22 ◽

2021 ◽

Author(s):

Rémi Granger ◽

Frédéric Flin ◽

Wolfgang Ludwig ◽

Ismail Hammad ◽

Christian Geindreau

Keyword(s):

Temperature Gradient ◽

Horizontal Plane ◽

Time Lapse ◽

Snow Sample ◽

Crystalline Orientation ◽

Diffraction Contrast ◽

Crystallographic Facets ◽

Over Time ◽

Material Fluxes

Abstract. In this study on temperature gradient metamorphism in snow, we investigate the hypothesis that there exists a favorable crystalline orientation relative to the temperature gradient, giving rise to a faster formation of crystallographic facets. We applied in-situ time-lapse Diffraction Contrast Tomography on a snow sample with a density of 476 kg m−3 subject to a temperature gradient of 52 °C m−1 at mean temperatures in the range between −4.1 °C and −2.1 °C for three days. The orientations of about 900 grains along with their microstructural evolution are followed over time. Faceted crystals appear during the evolution and from the analysis of the material fluxes, we indeed observe higher sublimation-deposition rate for grains with their c-axis in the horizontal plane at the beginning of the metamorphism. This remains the case up to the end of the experiment for what concerns sublimation while the differences vanish for deposition. That latter observation is explained in terms of geometrical interactions between grains.

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Dynamic expressions of confidence within an evidence accumulation framework

10.1101/2020.02.18.953778 ◽

2020 ◽

Cited By ~ 1

Author(s):

Kobe Desender ◽

Tobias H. Donner ◽

Tom Verguts

Keyword(s):

Dynamic Model ◽

Temporal Evolution ◽

Human Behaviour ◽

Evidence Accumulation ◽

Decision Confidence ◽

Confidence Judgments ◽

Evidence Strength ◽

Dot Motion ◽

Over Time ◽

Random Dot Motion

AbstractHuman observers can reliably report their confidence in the choices they make. An influential framework conceptualizes decision confidence as the probability of a decision being correct, given the choice made and the evidence on which it was based. This framework accounts for three diagnostic signatures of human confidence reports, including an opposite dependence of confidence on evidence strength for correct and error trials. However, the framework does not account for the temporal evolution of these signatures, because it only describes the transformation of a static representation of evidence into choice and the associated confidence. Here, we combine this framework with another influential framework: dynamic accumulation of evidence over time, and build on the notion that confidence reflects the probability of being correct, given the choice and accumulated evidence up until that point. Critically, we show that such a dynamic model predicts that the diagnostic signatures of confidence depend on time; most critically, it predicts a stronger opposite dependence of confidence on evidence strength and choice correctness as a function of time. We tested, and confirmed, these predictions in human behaviour during random dot motion discrimination, in which confidence judgments were queried at different points in time. We conclude that human confidence reports reflect the dynamics of the probability of being correct given the accumulated evidence and choice.

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