Articles | Volume 16, issue 10
https://doi.org/10.5194/tc-16-4343-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-4343-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Oct 2022
Research article |
| 18 Oct 2022
| 18 Oct 2022
A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics
Theodore Letcher
CORRESPONDING AUTHOR
US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, NH, United States of America
Julie Parno
US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, NH, United States of America
Zoe Courville
US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, NH, United States of America
Lauren Farnsworth
US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, NH, United States of America
Jason Olivier
US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, NH, United States of America
Related authors
Sandra L. LeGrand, Theodore W. Letcher, Gregory S. Okin, Nicholas P. Webb, Alex R. Gallagher, Saroj Dhital, Taylor S. Hodgdon, Nancy P. Ziegler, and Michelle L. Michaels
Geosci. Model Dev., 16, 1009–1038, https://doi.org/10.5194/gmd-16-1009-2023, https://doi.org/10.5194/gmd-16-1009-2023, 2023
Short summary
Short summary
Ground cover affects dust emissions by reducing wind flow over the immediate soil surface. This study reviews a method for estimating ground cover effects on wind erosion from satellite-detected terrain shadows. We conducted a case study for a US dust event using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Adding the shadow-based method for ground cover effects markedly improved simulated results and may lead to better dust modeling outcomes in vegetated drylands.
Sandra L. LeGrand, Chris Polashenski, Theodore W. Letcher, Glenn A. Creighton, Steven E. Peckham, and Jeffrey D. Cetola
Geosci. Model Dev., 12, 131–166, https://doi.org/10.5194/gmd-12-131-2019, https://doi.org/10.5194/gmd-12-131-2019, 2019
Short summary
Short summary
This paper reviews the history, code, and performance of the three dust emission schemes embedded in the WRF-Chem model, including the GOCART, AFWA, and UoC dust emission schemes, and provides the first full documentation of the AFWA scheme. A simulation case study is provided to explore differences in model output. Results highlight the relative strengths of each scheme, indicate reasons for disagreement, and demonstrate the need for improved terrain characterization in dust emission models.
Sandra L. LeGrand, Theodore W. Letcher, Gregory S. Okin, Nicholas P. Webb, Alex R. Gallagher, Saroj Dhital, Taylor S. Hodgdon, Nancy P. Ziegler, and Michelle L. Michaels
Geosci. Model Dev., 16, 1009–1038, https://doi.org/10.5194/gmd-16-1009-2023, https://doi.org/10.5194/gmd-16-1009-2023, 2023
Short summary
Short summary
Ground cover affects dust emissions by reducing wind flow over the immediate soil surface. This study reviews a method for estimating ground cover effects on wind erosion from satellite-detected terrain shadows. We conducted a case study for a US dust event using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Adding the shadow-based method for ground cover effects markedly improved simulated results and may lead to better dust modeling outcomes in vegetated drylands.
Sandra L. LeGrand, Chris Polashenski, Theodore W. Letcher, Glenn A. Creighton, Steven E. Peckham, and Jeffrey D. Cetola
Geosci. Model Dev., 12, 131–166, https://doi.org/10.5194/gmd-12-131-2019, https://doi.org/10.5194/gmd-12-131-2019, 2019
Short summary
Short summary
This paper reviews the history, code, and performance of the three dust emission schemes embedded in the WRF-Chem model, including the GOCART, AFWA, and UoC dust emission schemes, and provides the first full documentation of the AFWA scheme. A simulation case study is provided to explore differences in model output. Results highlight the relative strengths of each scheme, indicate reasons for disagreement, and demonstrate the need for improved terrain characterization in dust emission models.
Related subject area
Discipline: Snow | Subject: Snow Physics
Wind tunnel experiments to quantify the effect of aeolian snow transport on the surface snow microstructure
Spatial variation in the specific surface area of surface snow measured along the traverse route from the coast to Dome Fuji, Antarctica, during austral summer
Microstructure-based simulations of the viscous densification of snow and firn
A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism
A microstructure-based parameterization of the effective anisotropic elasticity tensor of snow, firn, and bubbly ice
Seismic attenuation in Antarctic firn
Temporospatial variability of snow's thermal conductivity on Arctic sea ice
Multiscale modeling of heat and mass transfer in dry snow: influence of the condensation coefficient and comparison with experiments
Heterogeneous grain growth and vertical mass transfer within a snow layer under a temperature gradient
Impact of the sampling procedure on the specific surface area of snow measurements with the IceCube
Wind conditions for snow cornice formation in a wind tunnel
Stochastic analysis of micro-cone penetration tests in snow
Coherent backscatter enhancement in bistatic Ku- and X-band radar observations of dry snow
Effect of snowfall on changes in relative seismic velocity measured by ambient noise correlation
Orientation selective grain sublimation–deposition in snow under temperature gradient metamorphism observed with diffraction contrast tomography
Experimental and model-based investigation of the links between snow bidirectional reflectance and snow microstructure
Impact of water vapor diffusion and latent heat on the effective thermal conductivity of snow
Enhancement of snow albedo reduction and radiative forcing due to coated black carbon in snow
An exploratory modelling study of perennial firn aquifers in the Antarctic Peninsula for the period 1979–2016
Macroscopic water vapor diffusion is not enhanced in snow
Snow albedo sensitivity to macroscopic surface roughness using a new ray-tracing model
A model for French-press experiments of dry snow compaction
Identification of blowing snow particles in images from a Multi-Angle Snowflake Camera
Modeling snow slab avalanches caused by weak-layer failure – Part 1: Slabs on compliant and collapsible weak layers
Modeling snow slab avalanches caused by weak-layer failure – Part 2: Coupled mixed-mode criterion for skier-triggered anticracks
Modeling the evolution of the structural anisotropy of snow
Motion of dust particles in dry snow under temperature gradient metamorphism
Influence of light-absorbing particles on snow spectral irradiance profiles
Saharan dust events in the European Alps: role in snowmelt and geochemical characterization
On the suitability of the Thorpe–Mason model for calculating sublimation of saltating snow
The influence of layering and barometric pumping on firn air transport in a 2-D model
Benjamin Walter, Hagen Weigel, Sonja Wahl, and Henning Löwe
The Cryosphere, 18, 3633–3652, https://doi.org/10.5194/tc-18-3633-2024, https://doi.org/10.5194/tc-18-3633-2024, 2024
Short summary
Short summary
The topmost layer of a snowpack forms the interface to the atmosphere and is critical for the reflectance of solar radiation and avalanche formation. The effect of wind on the surface snow microstructure during precipitation events is poorly understood and quantified. We performed controlled lab experiments in a ring wind tunnel to systematically quantify the snow microstructure for different wind speeds, temperatures and precipitation intensities and to identify the relevant processes.
Ryo Inoue, Teruo Aoki, Shuji Fujita, Shun Tsutaki, Hideaki Motoyama, Fumio Nakazawa, and Kenji Kawamura
The Cryosphere, 18, 3513–3531, https://doi.org/10.5194/tc-18-3513-2024, https://doi.org/10.5194/tc-18-3513-2024, 2024
Short summary
Short summary
We measured the snow specific surface area (SSA) at ~2150 surfaces between the coast near Syowa Station and Dome Fuji, East Antarctica, in summer 2021–2022. The observed SSA shows no elevation dependence between 15 and 500 km from the coast and increases toward the dome area beyond the range. SSA varies depending on surface morphologies and meteorological events. The spatial variation of SSA can be explained by snow metamorphism, snowfall frequency, and wind-driven inhibition of snow deposition.
Kévin Fourteau, Johannes Freitag, Mika Malinen, and Henning Löwe
The Cryosphere, 18, 2831–2846, https://doi.org/10.5194/tc-18-2831-2024, https://doi.org/10.5194/tc-18-2831-2024, 2024
Short summary
Short summary
Understanding the settling of snow under its own weight has applications from avalanche forecasts to ice core interpretations. We study how this settling can be modeled using 3D images of the internal structure of snow and ice deformation mechanics. We found that classical ice mechanics, as used, for instance, in glacier flow, explain the compaction of dense polar snow but not that of lighter seasonal snow. How, exactly, the ice deforms during light snow compaction thus remains an open question.
Anna Braun, Kévin Fourteau, and Henning Löwe
The Cryosphere, 18, 1653–1668, https://doi.org/10.5194/tc-18-1653-2024, https://doi.org/10.5194/tc-18-1653-2024, 2024
Short summary
Short summary
The specific surface of snow dictates key physical properties and continuously evolves in natural snowpacks. This is referred to as metamorphism. This work develops a rigorous physical model for this evolution, which is able to reproduce X-ray tomography measurements without using unphysical tuning parameters. Our results emphasize that snow crystal growth at the micrometer scale ultimately controls the pace of metamorphism.
Kavitha Sundu, Johannes Freitag, Kévin Fourteau, and Henning Löwe
The Cryosphere, 18, 1579–1596, https://doi.org/10.5194/tc-18-1579-2024, https://doi.org/10.5194/tc-18-1579-2024, 2024
Short summary
Short summary
Ice crystals often show a rod-like, vertical orientation in snow and firn; they are said to be anisotropic. The stiffness in the vertical direction therefore differs from the horizontal, which, for example, impacts the propagation of seismic waves. To quantify this anisotropy, we conducted finite-element simulations of 391 snow, firn, and ice core microstructures obtained from X-ray tomography. We then derived a parameterization that may be employed for advanced seismic studies in polar regions.
Stefano Picotti, José M. Carcione, and Mauro Pavan
The Cryosphere, 18, 169–186, https://doi.org/10.5194/tc-18-169-2024, https://doi.org/10.5194/tc-18-169-2024, 2024
Short summary
Short summary
A physical explanation of the seismic attenuation in the polar snow and ice masses is essential to gaining insight into the ice sheet and deeper geological formations. We estimate the P- and S-wave attenuation profiles of the Whillans Ice Stream from the spectral analysis of three-component active-source seismic data. The firn and ice quality factors are then modeled using a rock-physics theory that combines White's mesoscopic attenuation theory of interlayer flow with that of Biot/squirt flow.
Amy R. Macfarlane, Henning Löwe, Lucille Gimenes, David N. Wagner, Ruzica Dadic, Rafael Ottersberg, Stefan Hämmerle, and Martin Schneebeli
The Cryosphere, 17, 5417–5434, https://doi.org/10.5194/tc-17-5417-2023, https://doi.org/10.5194/tc-17-5417-2023, 2023
Short summary
Short summary
Snow acts as an insulating blanket on Arctic sea ice, keeping the underlying ice "warm", relative to the atmosphere. Knowing the snow's thermal conductivity is essential for understanding winter ice growth. During the MOSAiC expedition, we measured the thermal conductivity of snow. We found spatial and vertical variability to overpower any temporal variability or dependency on underlying ice type and the thermal resistance to be directly influenced by snow height.
Lisa Bouvet, Neige Calonne, Frédéric Flin, and Christian Geindreau
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-148, https://doi.org/10.5194/tc-2023-148, 2023
Revised manuscript accepted for TC
Short summary
Short summary
Three different macroscopic heat and mass transfer models have been derived for a large range of condensation coefficient values by an upscaling method. A comprehensive evaluation of the models is presented based on experimental datasets and numerical examples. The models reproduce the trend of experimental temperature and density profiles, but underestimate the magnitude of the processes. Possible causes of these discrepancies and potential improvements for the models are suggested.
Lisa Bouvet, Neige Calonne, Frédéric Flin, and Christian Geindreau
The Cryosphere, 17, 3553–3573, https://doi.org/10.5194/tc-17-3553-2023, https://doi.org/10.5194/tc-17-3553-2023, 2023
Short summary
Short summary
This study presents two new experiments of temperature gradient metamorphism in a snow layer using tomographic time series and focusing on the vertical extent. The results highlight two little known phenomena: the development of morphological vertical heterogeneities from an initial uniform layer, which is attributed to the temperature range and the vapor pressure distribution, and the quantification of the mass loss at the base caused by the vertical vapor fluxes and the dry lower boundary.
Julia Martin and Martin Schneebeli
The Cryosphere, 17, 1723–1734, https://doi.org/10.5194/tc-17-1723-2023, https://doi.org/10.5194/tc-17-1723-2023, 2023
Short summary
Short summary
The grain size of snow determines how light is reflected and other physical properties. The IceCube measures snow grain size at the specific near-infrared wavelength of 1320 nm. In our study, the preparation of snow samples for the IceCube creates a thin layer of small particles. Comparisons of the grain size with computed tomography, particle counting and numerical simulation confirm the aforementioned observation. We conclude that measurements at this wavelength underestimate the grain size.
Hongxiang Yu, Guang Li, Benjamin Walter, Michael Lehning, Jie Zhang, and Ning Huang
The Cryosphere, 17, 639–651, https://doi.org/10.5194/tc-17-639-2023, https://doi.org/10.5194/tc-17-639-2023, 2023
Short summary
Short summary
Snow cornices lead to the potential risk of causing snow avalanche hazards, which are still unknown so far. We carried out a wind tunnel experiment in a cold lab to investigate the environmental conditions for snow cornice accretion recorded by a camera. The length growth rate of the cornices reaches a maximum for wind speeds approximately 40 % higher than the threshold wind speed. Experimental results improve our understanding of the cornice formation process.
Pyei Phyo Lin, Isabel Peinke, Pascal Hagenmuller, Matthias Wächter, M. Reza Rahimi Tabar, and Joachim Peinke
The Cryosphere, 16, 4811–4822, https://doi.org/10.5194/tc-16-4811-2022, https://doi.org/10.5194/tc-16-4811-2022, 2022
Short summary
Short summary
Characterization of layers of snowpack with highly resolved micro-cone penetration tests leads to detailed fluctuating signals. We used advanced stochastic analysis to differentiate snow types by interpreting the signals as a mixture of continuous and discontinuous random fluctuations. These two types of fluctuation seem to correspond to different mechanisms of drag force generation during the experiments. The proposed methodology provides new insights into the characterization of snow layers.
Marcel Stefko, Silvan Leinss, Othmar Frey, and Irena Hajnsek
The Cryosphere, 16, 2859–2879, https://doi.org/10.5194/tc-16-2859-2022, https://doi.org/10.5194/tc-16-2859-2022, 2022
Short summary
Short summary
The coherent backscatter opposition effect can enhance the intensity of radar backscatter from dry snow by up to a factor of 2. Despite widespread use of radar backscatter data by snow scientists, this effect has received notably little attention. For the first time, we characterize this effect for the Earth's snow cover with bistatic radar experiments from ground and from space. We are also able to retrieve scattering and absorbing lengths of snow at Ku- and X-band frequencies.
Antoine Guillemot, Alec van Herwijnen, Eric Larose, Stephanie Mayer, and Laurent Baillet
The Cryosphere, 15, 5805–5817, https://doi.org/10.5194/tc-15-5805-2021, https://doi.org/10.5194/tc-15-5805-2021, 2021
Short summary
Short summary
Ambient noise correlation is a broadly used method in seismology to monitor tiny changes in subsurface properties. Some environmental forcings may influence this method, including snow. During one winter season, we studied this snow effect on seismic velocity of the medium, recorded by a pair of seismic sensors. We detected and modeled a measurable effect during early snowfalls: the fresh new snow layer modifies rigidity and density of the medium, thus decreasing the recorded seismic velocity.
Rémi Granger, Frédéric Flin, Wolfgang Ludwig, Ismail Hammad, and Christian Geindreau
The Cryosphere, 15, 4381–4398, https://doi.org/10.5194/tc-15-4381-2021, https://doi.org/10.5194/tc-15-4381-2021, 2021
Short summary
Short summary
In this study on temperature gradient metamorphism in snow, we investigate the hypothesis that there exists a favourable crystal orientation relative to the temperature gradient. We measured crystallographic orientations of the grains and their microstructural evolution during metamorphism using in situ time-lapse diffraction contrast tomography. Faceted crystals appear during the evolution, and we observe higher sublimation–deposition rates for grains with their c axis in the horizontal plane.
Marie Dumont, Frederic Flin, Aleksey Malinka, Olivier Brissaud, Pascal Hagenmuller, Philippe Lapalus, Bernard Lesaffre, Anne Dufour, Neige Calonne, Sabine Rolland du Roscoat, and Edward Ando
The Cryosphere, 15, 3921–3948, https://doi.org/10.5194/tc-15-3921-2021, https://doi.org/10.5194/tc-15-3921-2021, 2021
Short summary
Short summary
The role of snow microstructure in snow optical properties is only partially understood despite the importance of snow optical properties for the Earth system. We present a dataset combining bidirectional reflectance measurements and 3D images of snow. We show that the snow reflectance is adequately simulated using the distribution of the ice chord lengths in the snow microstructure and that the impact of the morphological type of snow is especially important when ice is highly absorptive.
Kévin Fourteau, Florent Domine, and Pascal Hagenmuller
The Cryosphere, 15, 2739–2755, https://doi.org/10.5194/tc-15-2739-2021, https://doi.org/10.5194/tc-15-2739-2021, 2021
Short summary
Short summary
The thermal conductivity of snow is an important physical property governing the thermal regime of a snowpack and its substrate. We show that it strongly depends on the kinetics of water vapor sublimation and that previous experimental data suggest a rather fast kinetics. In such a case, neglecting water vapor leads to an underestimation of thermal conductivity by up to 50 % for light snow. Moreover, the diffusivity of water vapor in snow is then directly related to the thermal conductivity.
Wei Pu, Tenglong Shi, Jiecan Cui, Yang Chen, Yue Zhou, and Xin Wang
The Cryosphere, 15, 2255–2272, https://doi.org/10.5194/tc-15-2255-2021, https://doi.org/10.5194/tc-15-2255-2021, 2021
Short summary
Short summary
We have explicitly resolved optical properties of coated BC in snow for explaining complex enhancement of snow albedo reduction due to coating effect in real environments. The parameterizations are developed for climate models to improve the understanding of BC in snow on global climate. We demonstrated that the contribution of BC coating effect to snow light absorption has exceeded dust over north China and will significantly contribute to the retreat of Arctic sea ice and Tibetan glaciers.
J. Melchior van Wessem, Christian R. Steger, Nander Wever, and Michiel R. van den Broeke
The Cryosphere, 15, 695–714, https://doi.org/10.5194/tc-15-695-2021, https://doi.org/10.5194/tc-15-695-2021, 2021
Short summary
Short summary
This study presents the first modelled estimates of perennial firn aquifers (PFAs) in Antarctica. PFAs are subsurface meltwater bodies that do not refreeze in winter due to the isolating effects of the snow they are buried underneath. They were first identified in Greenland, but conditions for their existence are also present in the Antarctic Peninsula. These PFAs can have important effects on meltwater retention, ice shelf stability, and, consequently, sea level rise.
Kévin Fourteau, Florent Domine, and Pascal Hagenmuller
The Cryosphere, 15, 389–406, https://doi.org/10.5194/tc-15-389-2021, https://doi.org/10.5194/tc-15-389-2021, 2021
Short summary
Short summary
There has been a long controversy to determine whether the effective diffusion coefficient of water vapor in snow is superior to that in free air. Using theory and numerical modeling, we show that while water vapor diffuses more than inert gases thanks to its interaction with the ice, the effective diffusion coefficient of water vapor in snow remains inferior to that in free air. This suggests that other transport mechanisms are responsible for the large vapor fluxes observed in some snowpacks.
Fanny Larue, Ghislain Picard, Laurent Arnaud, Inès Ollivier, Clément Delcourt, Maxim Lamare, François Tuzet, Jesus Revuelto, and Marie Dumont
The Cryosphere, 14, 1651–1672, https://doi.org/10.5194/tc-14-1651-2020, https://doi.org/10.5194/tc-14-1651-2020, 2020
Short summary
Short summary
The effect of surface roughness on snow albedo is often overlooked,
although a small change in albedo may strongly affect the surface energy
budget. By carving artificial roughness in an initially smooth snowpack,
we highlight albedo reductions of 0.03–0.04 at 700 nm and 0.06–0.10 at 1000 nm. A model using photon transport is developed to compute albedo considering roughness and applied to understand the impact of roughness as a function of snow properties and illumination conditions.
Colin R. Meyer, Kaitlin M. Keegan, Ian Baker, and Robert L. Hawley
The Cryosphere, 14, 1449–1458, https://doi.org/10.5194/tc-14-1449-2020, https://doi.org/10.5194/tc-14-1449-2020, 2020
Short summary
Short summary
We describe snow compaction laboratory data with a new mathematical model. Using a compression device that is similar to a French press with snow instead of coffee grounds, Wang and Baker (2013) compacted numerous snow samples of different densities at a constant velocity to determine the force required for snow compaction. Our mathematical model for compaction includes airflow through snow and predicts the required force, in agreement with the experimental data.
Mathieu Schaer, Christophe Praz, and Alexis Berne
The Cryosphere, 14, 367–384, https://doi.org/10.5194/tc-14-367-2020, https://doi.org/10.5194/tc-14-367-2020, 2020
Short summary
Short summary
Wind and precipitation often occur together, making the distinction between particles coming from the atmosphere and those blown by the wind difficult. This is however a crucial task to accurately close the surface mass balance. We propose an algorithm based on Gaussian mixture models to separate blowing snow and precipitation in images collected by a Multi-Angle Snowflake Camera (MASC). The algorithm is trained and (positively) evaluated using data collected in the Swiss Alps and in Antarctica.
Philipp L. Rosendahl and Philipp Weißgraeber
The Cryosphere, 14, 115–130, https://doi.org/10.5194/tc-14-115-2020, https://doi.org/10.5194/tc-14-115-2020, 2020
Short summary
Short summary
Dry-snow slab avalanche release is preceded by a fracture process within the snowpack. Recognizing weak layer collapse as an integral part of the fracture process is crucial and explains phenomena such as whumpf sounds and remote triggering of avalanches from low-angle terrain. In this first part of the two-part work we propose a novel closed-form analytical model for a snowpack that provides a highly efficient and precise analysis of the mechanical response of a loaded snowpack.
Philipp L. Rosendahl and Philipp Weißgraeber
The Cryosphere, 14, 131–145, https://doi.org/10.5194/tc-14-131-2020, https://doi.org/10.5194/tc-14-131-2020, 2020
Short summary
Short summary
Dry-snow slab avalanche release is preceded by a fracture process within the snowpack. Recognizing weak layer collapse as an integral part of the fracture process is crucial and explains phenomena such as whumpf sounds and remote triggering of avalanches from low-angle terrain. In this second part of the two-part work we propose a novel mixed-mode coupled stress and energy failure criterion for nucleation of weak layer failure due to external loading of the snowpack.
Silvan Leinss, Henning Löwe, Martin Proksch, and Anna Kontu
The Cryosphere, 14, 51–75, https://doi.org/10.5194/tc-14-51-2020, https://doi.org/10.5194/tc-14-51-2020, 2020
Short summary
Short summary
The anisotropy of the snow microstructure, given by horizontally aligned ice crystals and vertically interlinked crystal chains, is a key quantity to understand mechanical, dielectric, and thermodynamical properties of snow. We present a model which describes the temporal evolution of the anisotropy. The model is driven by snow temperature, temperature gradient, and the strain rate. The model is calibrated by polarimetric radar data (CPD) and validated by computer tomographic 3-D snow images.
Pascal Hagenmuller, Frederic Flin, Marie Dumont, François Tuzet, Isabel Peinke, Philippe Lapalus, Anne Dufour, Jacques Roulle, Laurent Pézard, Didier Voisin, Edward Ando, Sabine Rolland du Roscoat, and Pascal Charrier
The Cryosphere, 13, 2345–2359, https://doi.org/10.5194/tc-13-2345-2019, https://doi.org/10.5194/tc-13-2345-2019, 2019
Short summary
Short summary
Light–absorbing particles (LAPs, e.g. dust or black carbon) in snow are a potent climate forcing agent. Their presence darkens the snow surface and leads to higher solar energy absorption. Several studies have quantified this radiative impact by assuming that LAPs were motionless in dry snow, without any clear evidence of this assumption. Using time–lapse X–ray tomography, we show that temperature gradient metamorphism of snow induces downward motion of LAPs, leading to self–cleaning of snow.
Francois Tuzet, Marie Dumont, Laurent Arnaud, Didier Voisin, Maxim Lamare, Fanny Larue, Jesus Revuelto, and Ghislain Picard
The Cryosphere, 13, 2169–2187, https://doi.org/10.5194/tc-13-2169-2019, https://doi.org/10.5194/tc-13-2169-2019, 2019
Short summary
Short summary
Here we present a novel method to estimate the impurity content (e.g. black carbon or mineral dust) in Alpine snow based on measurements of light extinction profiles. This method is proposed as an alternative to chemical measurements, allowing rapid retrievals of vertical concentrations of impurities in the snowpack. In addition, the results provide a better understanding of the impact of impurities on visible light extinction in snow.
Biagio Di Mauro, Roberto Garzonio, Micol Rossini, Gianluca Filippa, Paolo Pogliotti, Marta Galvagno, Umberto Morra di Cella, Mirco Migliavacca, Giovanni Baccolo, Massimiliano Clemenza, Barbara Delmonte, Valter Maggi, Marie Dumont, François Tuzet, Matthieu Lafaysse, Samuel Morin, Edoardo Cremonese, and Roberto Colombo
The Cryosphere, 13, 1147–1165, https://doi.org/10.5194/tc-13-1147-2019, https://doi.org/10.5194/tc-13-1147-2019, 2019
Short summary
Short summary
The snow albedo reduction due to dust from arid regions alters the melting dynamics of the snowpack, resulting in earlier snowmelt. We estimate up to 38 days of anticipated snow disappearance for a season that was characterized by a strong dust deposition event. This process has a series of further impacts. For example, earlier snowmelts may alter the hydrological cycle in the Alps, induce higher sensitivity to late summer drought, and finally impact vegetation and animal phenology.
Varun Sharma, Francesco Comola, and Michael Lehning
The Cryosphere, 12, 3499–3509, https://doi.org/10.5194/tc-12-3499-2018, https://doi.org/10.5194/tc-12-3499-2018, 2018
Short summary
Short summary
The Thorpe-Mason (TM) model describes how an ice grain sublimates during aeolian transport. We revisit this classic model using simple numerical experiments and discover that for many common scenarios, the model is likely to underestimate the amount of ice loss. Extending this result to drifting and blowing snow using high-resolution turbulent flow simulations, the study shows that current estimates for ice loss due to sublimation in regions such as Antarctica need to be significantly updated.
Benjamin Birner, Christo Buizert, Till J. W. Wagner, and Jeffrey P. Severinghaus
The Cryosphere, 12, 2021–2037, https://doi.org/10.5194/tc-12-2021-2018, https://doi.org/10.5194/tc-12-2021-2018, 2018
Short summary
Short summary
Ancient air enclosed in bubbles of the Antarctic ice sheet is a key source of information about the Earth's past climate. However, a range of physical processes in the snow layer atop an ice sheet may change the trapped air's chemical composition before it is occluded in the ice. We developed the first detailed 2-D computer simulation of these processes and found a new method to improve the reconstruction of past climate from air in ice cores bubbles.
Cited articles
Adolph, A. C., Albert, M. R., Lazarcik, J., Dibb, J. E., Amante, J. M., and
Price, A.: Dominance of grain size impacts on seasonal snow albedo at open
sites in New Hampshire, J. Geophys. Res.-Atmos., 122,
121–139, 2017. a
Attene, M.: A lightweight approach to repairing digitized polygon meshes, The
visual computer, 26, 1393–1406, 2010. a
Bair, E. H., Rittger, K., Skiles, S. M., and Dozier, J.: An examination of snow
albedo estimates from MODIS and their impact on snow water equivalent
reconstruction, Water Resour. Res., 55, 7826–7842, 2019. a
Bohren, C. F. and Beschta, R. L.: Snowpack albedo and snow density, Cold Reg. Sci. Technol., 1, 47–50, 1979. a
Carmagnola, C. M., Domine, F., Dumont, M., Wright, P., Strellis, B., Bergin, M., Dibb, J., Picard, G., Libois, Q., Arnaud, L., and Morin, S.: Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack, The Cryosphere, 7, 1139–1160, https://doi.org/10.5194/tc-7-1139-2013, 2013. a
Chernyaev, E.: Marching cubes 33: Construction of topologically correct
isosurfaces, Tech. rep., in: CERN Report, CN/95-17, http://wwwinfo.cern.ch/asdoc/psdir (last access: February 2022), 1995. a
Dang, C., Fu, Q., and Warren, S. G.: Effect of snow grain shape on snow albedo,
J. Atmos. Sci., 73, 3573–3583, 2016. a
Déry, S. J. and Brown, R. D.: Recent Northern Hemisphere snow cover extent
trends and implications for the snow-albedo feedback, Geophys. Res.
Lett., 34, L22504, https://doi.org/10.1029/2007GL031474, 2007. a
Dickinson, R. E.: Biosphere atmosphere transfer scheme (BATS) version 1e as
coupled to the NCAR community climate model, NCAR Tech. Note TH-387+ STR,
1993. a
Doherty, S. J., Warren, S. G., Grenfell, T. C., Clarke, A. D., and Brandt, R. E.: Light-absorbing impurities in Arctic snow, Atmos. Chem. Phys., 10, 11647–11680, https://doi.org/10.5194/acp-10-11647-2010, 2010. a
Dumont, M., Brissaud, O., Picard, G., Schmitt, B., Gallet, J.-C., and Arnaud, Y.: High-accuracy measurements of snow Bidirectional Reflectance Distribution Function at visible and NIR wavelengths – comparison with modelling results, Atmos. Chem. Phys., 10, 2507–2520, https://doi.org/10.5194/acp-10-2507-2010, 2010. a
Dumont, M., Brun, E., Picard, G., Michou, M., Libois, Q., Petit, J., Geyer, M.,
Morin, S., and Josse, B.: Contribution of light-absorbing impurities in snow
to Greenland’s darkening since 2009, Nat. Geosci., 7, 509–512, 2014. a
Dumont, M., Flin, F., Malinka, A., Brissaud, O., Hagenmuller, P., Lapalus, P., Lesaffre, B., Dufour, A., Calonne, N., Rolland du Roscoat, S., and Ando, E.: Experimental and model-based investigation of the links between snow bidirectional reflectance and snow microstructure, The Cryosphere, 15, 3921–3948, https://doi.org/10.5194/tc-15-3921-2021, 2021. a, b
Flanner, M. G. and Zender, C. S.: Linking snowpack microphysics and albedo
evolution, J. Geophys. Res.-Atmos., 111, D12208, https://doi.org/10.1029/2005JD006834, 2006. a
Flanner, M. G., Shell, K. M., Barlage, M., Perovich, D. K., and Tschudi, M.:
Radiative forcing and albedo feedback from the Northern Hemisphere cryosphere
between 1979 and 2008, Nat. Geosci., 4, 151–155, 2011. a
Gardner, A. S. and Sharp, M. J.: A review of snow and ice albedo and the
development of a new physically based broadband albedo parameterization,
J. Geophys. Res.-Earth Surf., 115, F01009, https://doi.org/10.1029/2009JF001444, 2010. a
Grenfell, T. C. and Perovich, D. K.: Radiation absorption coefficients of
polycrystalline ice from 400–1400 nm, J. Geophys. Res.-Oceans, 86, 7447–7450, 1981. a
Hagenmuller, P., Flin, F., Dumont, M., Tuzet, F., Peinke, I., Lapalus, P., Dufour, A., Roulle, J., Pézard, L., Voisin, D., Ando, E., Rolland du Roscoat, S., and Charrier, P.: Motion of dust particles in dry snow under temperature gradient metamorphism, The Cryosphere, 13, 2345–2359, https://doi.org/10.5194/tc-13-2345-2019, 2019. a
Hall, A.: The role of surface albedo feedback in climate, J. Climate,
17, 1550–1568, 2004. a
Haussener, S., Gergely, M., Schneebeli, M., and Steinfeld, A.: Determination of
the macroscopic optical properties of snow based on exact morphology and
direct pore-level heat transfer modeling, J. Geophys. Res.-Earth Surf., 117, F03009, https://doi.org/10.1029/2012JF002332, 2012. a, b, c
He, C. and Flanner, M.: Snow Albedo and Radiative Transfer: Theory, Modeling,
and Parameterization, in: Springer Series in Light Scattering,
Springer, 67–133, https://doi.org/10.1007/978-3-030-38696-2_3, 2020. a
Hudson, S. R., Warren, S. G., Brandt, R. E., Grenfell, T. C., and Six, D.:
Spectral bidirectional reflectance of Antarctic snow: Measurements and
parameterization, J. Geophys. Res.-Atmos., 111, D18106, https://doi.org/10.1029/2006JD007290, 2006. a
Ishimoto, H., Adachi, S., Yamaguchi, S., Tanikawa, T., Aoki, T., and Masuda,
K.: Snow particles extracted from X-ray computed microtomography imagery and
their single-scattering properties, J. Quant. Spectrosc.
Ra., 209, 113–128, 2018. a
Jiao, Z., Ding, A., Kokhanovsky, A., Schaaf, C., Bréon, F.M., Dong, Y., Wang, Z., Liu, Y., Zhang, X., Yin, S., and Cui, L: Development of a snow kernel
to better model the anisotropic reflectance of pure snow in a kernel-driven
BRDF model framework, Remote Sens. Environ., 221, 198–209, 2019. a
Letcher, T. and Parno, J.: CRREL-GOSRT/CRREL-GOSRT: CRREL-GOSRT First Public
Release, Zenodo [code], https://doi.org/10.5281/zenodo.7086881, 2022a. a
Letcher, T. and Parno, J.: CRREL-GOSRT/TC_Paper_Supporting_Data: Supporting
Data, Zenodo [data set], https://doi.org/10.5281/zenodo.7083432, 2022b. a
Letcher, T. W. and Minder, J. R.: Characterization of the simulated regional
snow albedo feedback using a regional climate model over complex terrain,
J. Climate, 28, 7576–7595, 2015. a
Li, S. and Zhou, X.: Accuracy assessment of snow surface direct beam spectral
albedo derived from reciprocity approach through radiative transfer
simulation, in: IGARSS 2003. 2003 IEEE International Geoscience and Remote
Sensing Symposium, Proceedings (IEEE Cat. No. 03CH37477), 2,
839–841, IEEE, 2003. a
Liou, K., Takano, Y., and Yang, P.: Light absorption and scattering by
aggregates: Application to black carbon and snow grains, J.
Quant. Spectrosc. Ra., 112, 1581–1594, 2011. a
Lorensen, W. E. and Cline, H. E.: Marching cubes: A high resolution 3D surface
construction algorithm, ACM siggraph computer graphics, 21, 163–169, 1987. a
Natarajan, B. K.: On generating topologically consistent isosurfaces from
uniform samples, The Visual Computer, 11, 52–62, 1994. a
Neshyba, S. P., Grenfell, T. C., and Warren, S. G.: Representation of a
nonspherical ice particle by a collection of independent spheres for
scattering and absorption of radiation: 2. Hexagonal columns and plates,
J. Geophys. Res.-Atmos., 108, 4448, https://doi.org/10.1029/2002JD003302, 2003. a
Nielson, G. M. and Hamann, B.: The asymptotic decider: resolving the ambiguity
in Marching Cubes., IEEE visualization, 91, 83–91, 1991. a
Painter, T. H., Bryant, A. C., and Skiles, S. M.: Radiative forcing by light
absorbing impurities in snow from MODIS surface reflectance data, Geophys.
Res. Lett., 39, L17502, https://doi.org/10.1029/2012GL052457, 2012. a
Perovich, D. K. and Govoni, J. W.: Absorption coefficients of ice from 250 to
400 nm, Geophys. Res. Lett., 18, 1233–1235, 1991. a
Picard, G., Arnaud, L., Domine, F., and Fily, M.: Determining snow specific
surface area from near-infrared reflectance measurements: Numerical study of
the influence of grain shape, Cold Reg. Sci. Technol., 56,
10–17, 2009. a
Picard, G., Libois, Q., and Arnaud, L.: Refinement of the ice absorption spectrum in the visible using radiance profile measurements in Antarctic snow, The Cryosphere, 10, 2655–2672, https://doi.org/10.5194/tc-10-2655-2016, 2016. a
Saito, M., Yang, P., Loeb, N. G., and Kato, S.: A novel parameterization of
snow albedo based on a two-layer snow model with a mixture of grain habits,
J. Atmos. Sci., 76, 1419–1436, 2019. a
Schroeder, W. J., Lorensen, B., and Martin, K.: The visualization toolkit: an
object-oriented approach to 3D graphics, Prentice-Hall, Upper Saddle River, NJ, 1996. a
Scopigno, R.: A modified look-up table for implicit disambiguation of Marching
Cubes, The visual computer, 10, 353–355, 1994. a
Shi, T., Cui, J., Chen, Y., Zhou, Y., Pu, W., Xu, X., Chen, Q., Zhang, X., and Wang, X.: Enhanced light absorption and reduced snow albedo due to internally mixed mineral dust in grains of snow, Atmos. Chem. Phys., 21, 6035–6051, https://doi.org/10.5194/acp-21-6035-2021, 2021. a
Skiles, S. M. and Painter, T. H.: Toward understanding direct absorption and
grain size feedbacks by dust radiative forcing in snow with coupled snow
physical and radiative transfer modeling, Water Resour. Res., 55,
7362–7378, 2019. a
Skiles, S. M., Painter, T. H., Deems, J. S., Bryant, A. C., and Landry, C. C.:
Dust radiative forcing in snow of the Upper Colorado River Basin: 2.
Interannual variability in radiative forcing and snowmelt rates, Water Resour. Res., 48, W07522, https://doi.org/10.1029/2012WR011986, 2012. a
Skiles, S. M., Painter, T. H., Belnap, J., Holland, L., Reynolds, R. L.,
Goldstein, H. L., and Lin, J.: Regional variability in dust-on-snow processes
and impacts in the Upper Colorado River Basin, Hydrol. Process., 29,
5397–5413, 2015. a
Stamnes, K. and Stamnes, J. J.: Radiative transfer in coupled environmental systems. Wiley VCH Verlag GmbH and co., Weinheim, Germany, 18 March 2016, ISBN 978-3-527-41138-2,
2016. a
Sullivan, C. B. and Kaszynski, A.: PyVista: 3D plotting and mesh analysis
through a streamlined interface for the Visualization Toolkit (VTK),
J. Open Source Softw., 4, 1450, https://doi.org/10.21105/joss.01450, 2019. a
Thackeray, C. W. and Fletcher, C. G.: Snow albedo feedback: Current knowledge,
importance, outstanding issues and future directions, Prog. Phys.
Geogr., 40, 392–408, 2016. a
Van de Hülst, H. C: Light Scattering by Small Particles, Wiley, New York, 1957. a
Van der Walt, S., Schönberger, J. L., Nunez-Iglesias, J., Boulogne, F.,
Warner, J. D., Yager, N., Gouillart, E., and Yu, T.: scikit-image: image
processing in Python, PeerJ, 2, e453, https://doi.org/10.7717/peerj.453, 2014. a
Verseghy, D. L.: CLASS – A Canadian land surface scheme for GCMs. I. Soil
model, Int. J. Climatol., 11, 111–133, 1991. a
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012. a
Warren, S. G.: Can black carbon in snow be detected by remote sensing?, J. Geophys. Res.-Atmos., 118, 779–786, 2013. a
Warren, S. G. and Brandt, R. E.: Optical constants of ice from the ultraviolet
to the microwave: A revised compilation, J. Geophys. Res.-Atmos., 113, D14220, https://doi.org/10.1029/2007JD009744, 2008. a, b
Warren, S. G. and Wiscombe, W. J.: A model for the spectral albedo of snow. II:
Snow containing atmospheric aerosols, J. Atmos. Sci., 37,
2734–2745, 1980. a
West, B. A., Hodgdon, T. S., Parno, M. D., and Song, A. J.: Improved workflow
for unguided multiphase image segmentation, Comput. Geosci., 118,
91–99, 2018. a
Whitney, B. A.: Monte Carlo radiative transfer, in: Fluid Flows To Black Holes:
A Tribute to S Chandrasekhar on His Birth Centenary, World
Scientific, 151–176, https://doi.org/10.1142/9789814374774_0011, 2011. a
Wiscombe, W. J.: Improved Mie scattering algorithms, Appl. Optics, 19,
1505–1509, 1980. a
Short summary
We present a radiative transfer model that uses ray tracing to determine optical properties from computer-generated 3D renderings of snow resolved at the microscale and to simulate snow spectral reflection and transmission for visible and near-infrared light. We expand ray-tracing techniques applied to sub-1 cm3 snow samples to model an entire snowpack column. The model is able to reproduce known snow surface optical properties, and simulations compare well against field observations.
We present a radiative transfer model that uses ray tracing to determine optical properties from...
