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Journal articles on the topic 'Optical properties of snow'
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1
Pomeroy, J. W., and D. H. Male. "Optical Properties of Blowing Snow." Journal of Glaciology 34, no. 116 (1988): 3–10. http://dx.doi.org/10.1017/s0022143000008996.
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Abstract Calculation procedures are developed and results shown for the exact calculation of extinction and meteorological visual range using the blowing-snow mass in the atmosphere and particle radius. Results of the calculations show: (1) For monochromatic radiation, geometrical optics approximations of the extinction efficiency are found to provide results of only moderate accuracy in calculating the extinction of radiation by a single particle. (2) For broad-band radiation, the geometrical optics approximation is sufficiently accurate for many single-particle measurement instruments and applications, except in the infra-red band where Mie theory should be used. (3) For typical blowing-snow particle-size distributions, the shape parameter of the distribution of particle radii and the mean particle radius are very important in broad-band extinction and visual-range modelling. Estimates of blowing-snow quantities from broad-band extinction measurements or visual range from blowing-snow quantities should address the shape and mean value of the snow-particle radius distribution.
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Pomeroy, J. W., and D. H. Male. "Optical Properties of Blowing Snow." Journal of Glaciology 34, no. 116 (1988): 3–10. http://dx.doi.org/10.3189/s0022143000008996.
Full textAbstract:
AbstractCalculation procedures are developed and results shown for the exact calculation of extinction and meteorological visual range using the blowing-snow mass in the atmosphere and particle radius. Results of the calculations show: (1) For monochromatic radiation, geometrical optics approximations of the extinction efficiency are found to provide results of only moderate accuracy in calculating the extinction of radiation by a single particle. (2) For broad-band radiation, the geometrical optics approximation is sufficiently accurate for many single-particle measurement instruments and applications, except in the infra-red band where Mie theory should be used. (3) For typical blowing-snow particle-size distributions, the shape parameter of the distribution of particle radii and the mean particle radius are very important in broad-band extinction and visual-range modelling. Estimates of blowing-snow quantities from broad-band extinction measurements or visual range from blowing-snow quantities should address the shape and mean value of the snow-particle radius distribution.
3
Sergent, Claude, Evelyne Pougatch, Marcel Sudul, and Barbara Bourdelles. "Experimental investigation of optical snow properties." Annals of Glaciology 17 (1993): 281–87. http://dx.doi.org/10.1017/s0260305500012970.
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The authors have developed an experimental device in a cold laboratory with the purpose of measuring optical parameters of natural snow depending on grain-size, impurity content and density. Snow samples were prepared from homogeneous layers in order to measure the radiative properties of clearly identified snow types. The first part of this paper describes the working assumptions and the experimental device. In the second part, experiment results are described and discussed. We have compared albedo measurements of different natural snow types with theoretical values derived from physical optics, based on Mie scattering. The albedo evolution of three different snow types submitted to temperature-gradient metamorphism is analyzed.
4
Sergent, Claude, Evelyne Pougatch, Marcel Sudul, and Barbara Bourdelles. "Experimental investigation of optical snow properties." Annals of Glaciology 17 (1993): 281–87. http://dx.doi.org/10.3189/s0260305500012970.
Full textAbstract:
The authors have developed an experimental device in a cold laboratory with the purpose of measuring optical parameters of natural snow depending on grain-size, impurity content and density. Snow samples were prepared from homogeneous layers in order to measure the radiative properties of clearly identified snow types. The first part of this paper describes the working assumptions and the experimental device. In the second part, experiment results are described and discussed. We have compared albedo measurements of different natural snow types with theoretical values derived from physical optics, based on Mie scattering. The albedo evolution of three different snow types submitted to temperature-gradient metamorphism is analyzed.
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Warren, Stephen G. "Optical properties of ice and snow." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, no. 2146 (April 15, 2019): 20180161. http://dx.doi.org/10.1098/rsta.2018.0161.
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The interactions of electromagnetic radiation with ice, and with ice-containing media such as snow and clouds, are determined by the refractive index and absorption coefficient (the ‘optical constants’) of pure ice as functions of wavelength. Bulk reflectance, absorptance and transmittance are further influenced by grain size (for snow), bubbles (for glacier ice and lake ice) and brine inclusions (for sea ice). Radiative transfer models for clouds can also be applied to snow; the important differences in their radiative properties are that clouds are optically thinner and contain smaller ice crystals than snow. Absorption of visible and near-ultraviolet radiation by ice is so weak that absorption of sunlight at these wavelengths in natural snow is dominated by trace amounts of light-absorbing impurities such as dust and soot. In the thermal infrared, ice is moderately absorptive, so snow is nearly a blackbody, with emissivity 98–99%. The absorption spectrum of liquid water resembles that of ice from the ultraviolet to the mid-infrared. At longer wavelengths they diverge, so microwave emission can be used to detect snowmelt on ice sheets, and to discriminate between sea ice and open water, by remote sensing. Snow and ice are transparent to radio waves, so radar can be used to infer ice-sheet thickness.This article is part of the theme issue ‘The physics and chemistry of ice: scaffolding across scales, from the viability of life to the formation of planets’.
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Kaasalainen, S., M. Kaasalainen, T. Mielonen, J. Suomalainen, J. I. Peltoniemi, and J. Näränen. "Optical properties of snow in backscatter." Journal of Glaciology 52, no. 179 (2006): 574–84. http://dx.doi.org/10.3189/172756506781828421.
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AbstractWe present an overview and the first systematic results on the backscatter properties of snow samples with different grain properties. During a 2 year study we investigated the effect of the apparent characteristics of the samples on the intensity enhancement in the direction of exact backscatter (retroreflection), using a specific instrument designed for backscatter measurements. We observed that a sharp peak in intensity (the hot spot) occurs for most types of snow, which is not observable with traditional goniometers. The key factors in the peak properties are the temperature (related to the changes in grain structure) and grain shape and size. These results form the basis of a larger backscatter data archive which is being applied in the systematic study and exploitation of ‘hot spots’ in remote sensing of natural targets, as well as in the development of airborne laser intensity measurement.
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Saito, Masanori, Ping Yang, Norman G. Loeb, and Seiji Kato. "A Novel Parameterization of Snow Albedo Based on a Two-Layer Snow Model with a Mixture of Grain Habits." Journal of the Atmospheric Sciences 76, no. 5 (May 1, 2019): 1419–36. http://dx.doi.org/10.1175/jas-d-18-0308.1.
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Abstract Snow albedo plays a critical role in the surface energy budget in snow-covered regions and is subject to large uncertainty due to variable physical and optical characteristics of snow. We develop an optically and microphysically consistent snow grain habit mixture (SGHM) model, aiming at an improved representation of bulk snow properties in conjunction with considering the particle size distribution, particle shape, and internally mixed black carbon (BC). Spectral snow albedos computed with two snow layers with the SGHM model implemented in an adding–doubling radiative transfer model agree with observations. Top-snow-layer optical properties essentially determine spectral snow albedo when the top-layer snow water equivalent (SWE) is large. When the top-layer SWE is less than 1 mm, the second-snow-layer optical properties have nonnegligible impacts on the albedo of the snow surface. Snow albedo enhancement with increasing solar zenith angle (SZA) largely depends on snow particle effective radius and also internally mixed BC. Based on the SGHM model and various sensitivity studies, single- and two-layer snow albedos are parameterized for six spectral bands used in NASA Langley Research Center’s modified Fu–Liou broadband radiative transfer model. Parameterized albedo is expressed as a function of snow particle effective radii of the two layers, SWE in the top layer, internally mixed BC mass fraction in both layers, and SZA. Both single-layer and two-layer parameterizations provide band-mean snow albedo consistent with rigorous calculations, achieving correlation coefficients close to 0.99 for all bands.
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Beres, Nicholas D., Deep Sengupta, Vera Samburova, Andrey Y. Khlystov, and Hans Moosmüller. "Deposition of brown carbon onto snow: changes in snow optical and radiative properties." Atmospheric Chemistry and Physics 20, no. 10 (May 26, 2020): 6095–114. http://dx.doi.org/10.5194/acp-20-6095-2020.
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Abstract. Light-absorbing organic carbon aerosol – colloquially known as brown carbon (BrC) – is emitted from combustion processes and has a brownish or yellowish visual appearance, caused by enhanced light absorption at shorter visible and ultraviolet wavelengths (0.3 µm≲λ≲0.5 µm). Recently, optical properties of atmospheric BrC aerosols have become the topic of intense research, but little is known about how BrC deposition onto snow surfaces affects the spectral snow albedo, which can alter the resulting radiative forcing and in-snow photochemistry. Wildland fires in close proximity to the cryosphere, such as peatland fires that emit large quantities of BrC, are becoming more common at high latitudes, potentially affecting nearby snow and ice surfaces. In this study, we describe the artificial deposition of BrC aerosol with known optical, chemical, and physical properties onto the snow surface, and we monitor its spectral radiative impact and compare it directly to modeled values. First, using small-scale combustion of Alaskan peat, BrC aerosols were artificially deposited onto the snow surface. UV–Vis absorbance and total organic carbon (TOC) concentration of snow samples were measured for samples with and without artificial BrC deposition. These measurements were used to first derive a BrC (mass) specific absorption (m2 g−1) across the UV–Vis spectral range. We then estimate the imaginary part of the refractive index of deposited BrC aerosol using a volume mixing rule. Single-particle optical properties were calculated using Mie theory, and these values were used to show that the measured spectral snow albedo of snow with deposited BrC was in general agreement with modeled spectral snow albedo using calculated BrC optical properties. The instantaneous radiative forcing per unit mass of total organic carbon deposited to the ambient snowpack was found to be 1.23 (+0.14/-0.11) W m−2 per part per million (ppm). We estimate the same deposition onto a pure snowpack without light-absorbing impurities would have resulted in an instantaneous radiative forcing per unit mass of 2.68 (+0.27/-0.22) W m−2 per ppm of BrC deposited.
9
Lamare, M. L., J. Lee-Taylor, and M. D. King. "The impact of atmospheric mineral aerosol deposition on the albedo of snow and sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?" Atmospheric Chemistry and Physics Discussions 15, no. 16 (August 27, 2015): 23131–72. http://dx.doi.org/10.5194/acpd-15-23131-2015.
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Abstract. Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiative-transfer model (TUV-snow) show that the effects of mineral aerosol deposits is strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass-ratio of mineral dust has little effect on albedo. On the contrary, multiple layers of mineral aerosols deposited during episodic events evenly distributed play a similar role in the surface albedo of snow as a loading distributed throughout, even when the layers are further apart. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.
10
France, J. L., M. D. King, M. M. Frey, J. Erbland, G. Picard, A. MacArthur, and J. Savarino. "Snow optical properties at Dome C, Antarctica – implications for snow emissions and snow chemistry of reactive nitrogen." Atmospheric Chemistry and Physics Discussions 11, no. 4 (April 18, 2011): 11959–93. http://dx.doi.org/10.5194/acpd-11-11959-2011.
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Abstract. Measurements of $e$-folding depth, nadir reflectivity and stratigraphy of the snowpack around Concordia station (Dome C, 75.10° S, 123.31° E) were undertaken and used to determine wavelength dependent coefficients (350 nm to 550 nm) for light scattering and absorption and to calculate potential fluxes of nitrogen dioxide (NO2) from the snowpack due to nitrate photolysis within the snowpack. The stratigraphy of the top 80 cm of Dome C snowpack generally consists of three main layers: a surface of soft windpack (not ubiquitous), a hard windpack and a hoar-like layer beneath the windpack(s). The $e$-folding depths are ~10 cm for the two windpack layers and ~20 cm for the hoar-like layer for solar radiation at a wavelength of 400 nm, about a factor 2–4 larger than previous model estimates for South Pole. Depth integrated photochemical reaction rates of nitrate photolysis in the Dome C snowpack were calculated to give molecular fluxes of NO2 of 5.3×1012 molecules m−2 s−1, 2.3×1012 molecules m−2 s−1 and 8×1011 molecules m−2 s−1 for solar zenith angles of 60°, 70° and 80° respectively for clear sky conditions using the TUV-snow radiative-transfer model. Depending upon the snowpack stratigraphy, a minimum of 85% of the NO2 originates from within the top 20 cm of the Dome C snowpack. It is found that on a multi-annual scale, nitrate photolysis can remove up to 80% of nitrate from surface snow, confirming independent isotopic evidence that photolysis is an important driver of nitrate loss occurring in the EAIS snowpack. However, the model cannot account for the total observed nitrate loss of 90–95% or the shape of the observed nitrate depth profile. A more complete model will need to include also physical processes such as evaporation, re-deposition or diffusion between the quasi-liquid layer on snow grains and firn air to account for the discrepancies.
11
Domine, F., M. Albert, T. Huthwelker, H. W. Jacobi, A. A. Kokhanovsky, M. Lehning, G. Picard, and W. R. Simpson. "Snow physics as relevant to snow photochemistry." Atmospheric Chemistry and Physics 8, no. 2 (January 16, 2008): 171–208. http://dx.doi.org/10.5194/acp-8-171-2008.
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Abstract. Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, thermal conductivity, permeability, gas diffusivity and optical properties. Inasmuch as possible, equations to parameterize these properties as functions of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth are discussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.
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Domine, F., M. Albert, T. Huthwelker, H. W. Jacobi, A. A. Kokhanovsky, M. Lehning, G. Picard, and W. R. Simpson. "Snow physics as relevant to snow photochemistry." Atmospheric Chemistry and Physics Discussions 7, no. 3 (May 8, 2007): 5941–6036. http://dx.doi.org/10.5194/acpd-7-5941-2007.
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Abstract. Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires the knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, optical properties, thermal conductivity, permeability and gas diffusivity. Inasmuch as possible, equations to parameterize these properties as a function of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth are discussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.
13
Lamare, M. L., J. Lee-Taylor, and M. D. King. "The impact of atmospheric mineral aerosol deposition on the albedo of snow & sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?" Atmospheric Chemistry and Physics 16, no. 2 (January 25, 2016): 843–60. http://dx.doi.org/10.5194/acp-16-843-2016.
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Abstract. Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light-absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiative-transfer model (TUV-snow) show that the effects of mineral aerosol deposits are strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass ratio of mineral dust has little effect on albedo. On the contrary, the surface albedo of two snowpacks of equal depth, containing the same mineral aerosol mass ratio, is similar, whether the loading is uniformly distributed or concentrated in multiple layers, regardless of their position or spacing. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.
14
Zdorovennova, G., R. Zdorovennov, N. Palshin, and A. Terzhevik. "Optical properties of the ice cover on Vendyurskoe lake, Russian Karelia (1995–2012)." Annals of Glaciology 54, no. 62 (2013): 121–24. http://dx.doi.org/10.3189/2013aog62a179.
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AbstractSolar radiation penetrating the ice is one of the most important factors that determine the functioning of lake ecosystem in late winter. Parameterization of the attenuation of solar radiation in the snow-ice sheet is an essential tool in the study of the light regime of ice-covered lakes. The optical properties of the snow-ice sheet in Vendyurskoe lake, northwestern Russia, are investigated on the basis of long-term field observations (1995–2012). The four-layer approach (snow, white ice, slush and congelation ice) is used to study the attenuation of the downwelling planar irradiance in the snow-ice sheet. The bulk attenuation coefficients for four layers (18.8 m–1 for snow, 6 m−1 for white ice, 3.5 m−1 for slush and 2.1 m−1 for congelation ice) are calculated by the quasi-Newton method. A comparison of observed and calculated values of the irradiance beneath the ice shows that the determined coefficients adequately describe the attenuation of the downwelling irradiance by snow-ice cover.
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France, J. L., M. D. King, M. M. Frey, J. Erbland, G. Picard, S. Preunkert, A. MacArthur, and J. Savarino. "Snow optical properties at Dome C (Concordia), Antarctica; implications for snow emissions and snow chemistry of reactive nitrogen." Atmospheric Chemistry and Physics 11, no. 18 (September 21, 2011): 9787–801. http://dx.doi.org/10.5194/acp-11-9787-2011.
Full textAbstract:
Abstract. Measurements of e-folding depth, nadir reflectivity and stratigraphy of the snowpack around Concordia station (Dome C, 75.10° S, 123.31° E) were undertaken to determine wavelength dependent coefficients (350 nm to 550 nm) for light scattering and absorption and to calculate potential fluxes (depth-integrated production rates) of nitrogen dioxide (NO2) from the snowpack due to nitrate photolysis within the snowpack. The stratigraphy of the top 80 cm of Dome C snowpack generally consists of three main layers:- a surface of soft windpack (not ubiquitous), a hard windpack, and a hoar-like layer beneath the windpack(s). The e-folding depths are ~10 cm for the two windpack layers and ~20 cm for the hoar-like layer for solar radiation at a wavelength of 400 nm; about a factor 2–4 larger than previous model estimates for South Pole. The absorption cross-section due to impurities in each snowpack layer are consistent with a combination of absorption due to black carbon and HULIS (HUmic LIke Substances), with amounts of 1–2 ng g−1 of black carbon for the surface snow layers. Depth-integrated photochemical production rates of NO2 in the Dome C snowpack were calculated as 5.3 × 1012 molecules m−2 s−1, 2.3 × 1012 molecules m−2 s−1 and 8 × 1011 molecules m−2 s−1 for clear skies and solar zenith angles of 60°, 70° and 80° respectively using the TUV-snow radiative-transfer model. Depending upon the snowpack stratigraphy, a minimum of 85% of the NO2 may originate from the top 20 cm of the Dome C snowpack. It is found that on a multi-annual time-scale photolysis can remove up to 80% of nitrate from surface snow, confirming independent isotopic evidence that photolysis is an important driver of nitrate loss occurring in the EAIS (East Antarctic Ice Sheet) snowpack. However, the model cannot completely account for the total observed nitrate loss of 90–95 % or the shape of the observed nitrate concentration depth profile. A more complete model will need to include also physical processes such as evaporation, re-deposition or diffusion between the quasi-liquid layer on snow grains and firn air to account for the discrepancies.
16
He, Cenlin, Yoshi Takano, Kuo-Nan Liou, Ping Yang, Qinbin Li, and Fei Chen. "Impact of Snow Grain Shape and Black Carbon–Snow Internal Mixing on Snow Optical Properties: Parameterizations for Climate Models." Journal of Climate 30, no. 24 (December 2017): 10019–36. http://dx.doi.org/10.1175/jcli-d-17-0300.1.
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A set of parameterizations is developed for spectral single-scattering properties of clean and black carbon (BC)-contaminated snow based on geometric-optics surface wave (GOS) computations, which explicitly resolves BC–snow internal mixing and various snow grain shapes. GOS calculations show that, compared with nonspherical grains, volume-equivalent snow spheres show up to 20% larger asymmetry factors and hence stronger forward scattering, particularly at wavelengths <1 μm. In contrast, snow grain sizes have a rather small impact on the asymmetry factor at wavelengths <1 μm, whereas size effects are important at longer wavelengths. The snow asymmetry factor is parameterized as a function of effective size, aspect ratio, and shape factor and shows excellent agreement with GOS calculations. According to GOS calculations, the single-scattering coalbedo of pure snow is predominantly affected by grain sizes, rather than grain shapes, with higher values for larger grains. The snow single-scattering coalbedo is parameterized in terms of the effective size that combines shape and size effects, with an accuracy of >99%. Based on GOS calculations, BC–snow internal mixing enhances the snow single-scattering coalbedo at wavelengths <1 μm, but it does not alter the snow asymmetry factor. The BC-induced enhancement ratio of snow single-scattering coalbedo, independent of snow grain size and shape, is parameterized as a function of BC concentration with an accuracy of >99%. Overall, in addition to snow grain size, both BC–snow internal mixing and snow grain shape play critical roles in quantifying BC effects on snow optical properties. The present parameterizations can be conveniently applied to snow, land surface, and climate models including snowpack radiative transfer processes.
17
Pirazzini, R., P. Räisänen, T. Vihma, M. Johansson, and E. M. Tastula. "Measurements and modelling of snow particle size and shortwave infrared albedo over a melting Antarctic ice sheet." Cryosphere 9, no. 6 (December 15, 2015): 2357–81. http://dx.doi.org/10.5194/tc-9-2357-2015.
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Abstract. The albedo of a snowpack depends on the single-scattering properties of individual snow crystals, which have a variety of shapes and sizes, and are often bounded in clusters. From the point of view of optical modelling, it is essential to identify the geometric dimensions of the population of snow particles that synthesize the scattering properties of the snowpack surface. This involves challenges related to the complexity of modelling the radiative transfer in such an irregular medium, and to the difficulty of measuring microphysical snow properties. In this paper, we illustrate a method to measure the size distribution of a snow particle parameter, which roughly corresponds to the smallest snow particle dimension, from two-dimensional macro photos of snow particles taken in Antarctica at the surface layer of a melting ice sheet. We demonstrate that this snow particle metric corresponds well to the optically equivalent effective radius utilized in radiative transfer modelling, in particular when snow particles are modelled with the droxtal shape. The surface albedo modelled on the basis of the measured snow particle metric showed an excellent match with the observed albedo when there was fresh or drifted snow at the surface. In the other cases, a good match was present only for wavelengths longer than 1.4 μm. For shorter wavelengths, our modelled albedo generally overestimated the observations, in particular when surface hoar and faceted polycrystals were present at the surface and surface roughness was increased by millimetre-scale cavities generated during melting. Our results indicate that more than just one particle metric distribution is needed to characterize the snow scattering properties at all optical wavelengths, and suggest an impact of millimetre-scale surface roughness on the shortwave infrared albedo.
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Pirazzini, R., P. Räisänen, T. Vihma, M. Johansson, and E. M. Tastula. "Measurements and modelling of snow particle size and shortwave infrared albedo over a melting Antarctic ice sheet." Cryosphere Discussions 9, no. 3 (June 30, 2015): 3405–74. http://dx.doi.org/10.5194/tcd-9-3405-2015.
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Abstract. The albedo of a snowpack depends on the single-scattering properties of individual snow crystals, which have a variety of shapes and sizes, and are often bounded in clusters. From the point of view of optical modelling, it is essential to identify the geometric dimensions of the population of snow particles that synthetize the scattering properties of the snowpack surface. This involves challenges related to the complexity of modelling the radiative transfer in such an irregular medium, and to the difficulty of measuring microphysical snow properties. In this paper, we illustrate a method to measure the size distribution of a snow particle parameter, which roughly corresponds to the smallest snow particle dimension, from two-dimensional macro-photos of snow particles taken in Antarctica at the surface layer of a melting ice sheet. We demonstrate that this snow particle metric corresponds well to the optically equivalent effective radius utilized in radiative transfer modelling, in particular when snow particles are modelled with the droxtal shape. The surface albedo modelled on the basis of the measured snow particle metric showed an excellent match with the observed albedo when there was fresh or drifted snow at the surface. In the other cases, a good match was present only for wavelengths longer than 1.4 μm. For shorter wavelengths, our modelled albedo generally overestimated the observations, in particular when surface hoar and faceted polycrystals were present at the surface and surface roughness was increased by millimetre-scale cavities generated during melting. Our results indicate that more than just one particle metric distribution is needed to characterize the snow scattering properties at all optical wavelengths, and suggest an impact of millimetre-scale surface roughness on the shortwave infrared albedo.
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Dumont, Marie, Frederic Flin, Aleksey Malinka, Olivier Brissaud, Pascal Hagenmuller, Philippe Lapalus, Bernard Lesaffre, et al. "Experimental and model-based investigation of the links between snow bidirectional reflectance and snow microstructure." Cryosphere 15, no. 8 (August 20, 2021): 3921–48. http://dx.doi.org/10.5194/tc-15-3921-2021.
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Abstract. Snow stands out from materials at the Earth’s surface owing to its unique optical properties. Snow optical properties are sensitive to the snow microstructure, triggering potent climate feedbacks. The impacts of snow microstructure on its optical properties such as reflectance are, to date, only partially understood. However, precise modelling of snow reflectance, particularly bidirectional reflectance, are required in many problems, e.g. to correctly process satellite data over snow-covered areas. This study presents a dataset that combines bidirectional reflectance measurements over 500–2500 nm and the X-ray tomography of the snow microstructure for three snow samples of two different morphological types. The dataset is used to evaluate the stereological approach from Malinka (2014) that relates snow optical properties to the chord length distribution in the snow microstructure. The mean chord length and specific surface area (SSA) retrieved with this approach from the albedo spectrum and those measured by the X-ray tomography are in excellent agreement. The analysis of the 3D images has shown that the random chords of the ice phase obey the gamma distribution with the shape parameter m taking the value approximately equal to or a little greater than 2. For weak and intermediate absorption (high and medium albedo), the simulated bidirectional reflectances reproduce the measured ones accurately but tend to slightly overestimate the anisotropy of the radiation. For such absorptions the use of the exponential law for the ice chord length distribution instead of the one measured with the X-ray tomography does not affect the simulated reflectance. In contrast, under high absorption (albedo of a few percent), snow microstructure and especially facet orientation at the surface play a significant role in the reflectance, particularly at oblique viewing and incidence.
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SKILES, S. McKENZIE, THOMAS PAINTER, and GREGORY S. OKIN. "A method to retrieve the spectral complex refractive index and single scattering optical properties of dust deposited in mountain snow." Journal of Glaciology 63, no. 237 (December 14, 2016): 133–47. http://dx.doi.org/10.1017/jog.2016.126.
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ABSTRACTDust deposition to snow can have regionally important climatic and hydrologic impacts resulting from direct reduction of surface albedo and indirectly from the initiation of snow albedo feedbacks. Modeling the radiative impacts of dust deposited in snow requires knowledge of the optical properties of both components. Here we present an inversion technique to retrieve the effective optical properties of dust deposited in mountain snow cover from measurements of hemispherical dust reflectance and particle size distributions using radiative transfer modeling. First, modeled reflectance is produced from single scattering properties modeled with Mie theory for a specified grain size distribution over a range of values for the imaginary part of the complex refractive index (k = 0.00001–0.1). Then, a multi-step look-up table process is employed to retrieve kλ and single scattering optical properties by matching measured to modeled reflectance across the shortwave and near infrared. The real part of the complex refractive index, n, for dust aerosols ranges between 1.5 and 1.6 and a sensitivity analysis shows the method is relatively insensitive to the choice of n within this range, 1.525 was used here. Using the values retrieved by this method to update dust optical properties in a snow + aerosol radiative transfer model reduces errors in springtime albedo modeling by 50–70%.
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Malinka, Aleksey, Eleonora Zege, Georg Heygster, and Larysa Istomina. "Reflective properties of white sea ice and snow." Cryosphere 10, no. 6 (November 2, 2016): 2541–57. http://dx.doi.org/10.5194/tc-10-2541-2016.
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Abstract. White ice (ice with a highly scattering granular layer on top of its surface) and snow-covered ice occupy a large part of the sea ice area in the Arctic, the former in summer, the latter in the cold period. The inherent optical properties (IOPs) and the reflectance of these types of ice are considered from the point of view of the light scattering and radiative transfer theories. The IOPs – the extinction and absorption coefficients and the scattering phase function – are derived with the assumption that both the snow cover and the scattering layer of white ice are random mixtures of air and ice with the characteristic grain size significantly larger than the wavelength of incident light. Simple analytical formulas are put forward to calculate the bidirectional reflectance factor (BRF), albedo at direct incidence (the directional–hemispherical reflectance), and albedo at diffuse incidence (the bihemispherical reflectance). The optical model developed is verified with the data of the in situ measurements made during the R/V Polarstern expedition ARK-XXVII/3 in 2012.
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Mei, Linlu, Vladimir Rozanov, Christine Pohl, Marco Vountas, and John P. Burrows. "The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study." Cryosphere 15, no. 6 (June 18, 2021): 2757–80. http://dx.doi.org/10.5194/tc-15-2757-2021.
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Abstract. The eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm has been designed for the top-of-atmosphere reflectance measured by the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board Sentinel-3 to derive snow properties: snow grain size (SGS), snow particle shape (SPS) and specific surface area (SSA) under cloud-free conditions. This is the first part of the paper, to describe the retrieval method and the sensitivity study. Nine pre-defined SPSs (aggregate of 8 columns, droxtal, hollow bullet rosette, hollow column, plate, aggregate of 5 plates, aggregate of 10 plates, solid bullet rosette, column) are used to describe the snow optical properties. The optimal SGS and SPS are estimated iteratively utilizing a look-up-table (LUT) approach. The SSA is then calculated using another pre-calculated LUT for the retrieved SGS and SPS. The optical properties (e.g., phase function) of the ice crystals can reproduce the wavelength-dependent and angular-dependent snow reflectance features, compared to laboratory measurements. A comprehensive study to understand the impact of aerosols, SPS, ice crystal surface roughness, cloud contamination, instrument spectral response function, the snow habit mixture model and snow vertical inhomogeneity in the retrieval accuracy of snow properties has been performed based on SCIATRAN radiative transfer simulations. The main findings are (1) snow angular and spectral reflectance features can be described by the predefined ice crystal properties only when both SGS and SPS can be optimally and iteratively obtained; (2) the impact of ice crystal surface roughness on the retrieval results is minor; (3) SGS and SSA show an inverse linear relationship; (4) the retrieval of SSA assuming a non-convex particle shape, compared to a convex particle shape (e.g., sphere), shows larger retrieval results; (5) aerosol/cloud contamination due to unperfected atmospheric correction and cloud screening introduces underestimation of SGS, “inaccurate” SPS and overestimation of SSA; (6) the impact of the instrument spectral response function introduces an overestimation into retrieved SGS, introduces an underestimation into retrieved SSA and has no impact on retrieved SPS; and (7) the investigation, by taking an ice crystal particle size distribution and habit mixture into account, reveals that XBAER-retrieved SGS agrees better with the mean size, rather than with the mode size, for a given particle size distribution.
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Hodson, A. J., A. Nowak, J. Cook, M. Sabacka, E. S. Wharfe, D. A. Pearce, P. Convey, and G. Vieira. "Microbes influence the biogeochemical and optical properties of maritime Antarctic snow." Journal of Geophysical Research: Biogeosciences 122, no. 6 (June 2017): 1456–70. http://dx.doi.org/10.1002/2016jg003694.
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Gerland, Sebastian, Jan-Gunnar Winther, Jon Børre Ørbæk, Glen E. Liston, Nils Are Øritsland, Alberto Blanco, and Boris Ivanov. "Physical and optical properties of snow covering Arctic tundra on Svalbard." Hydrological Processes 13, no. 14-15 (October 1999): 2331–43. http://dx.doi.org/10.1002/(sici)1099-1085(199910)13:14/15<2331::aid-hyp855>3.0.co;2-w.
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Davis, Robert E., Anne W. Nolin, Rachel Jordan, and Jeff Dozier. "Towards predicting temporal changes of the spectral signature of snow in visible and near-infrared wavelengths." Annals of Glaciology 17 (1993): 143–48. http://dx.doi.org/10.1017/s026030550001274x.
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This study links two models, one that simulates changes in snow microstructure and one that recovers microstructure properties from measurements of snow reflectance. An energy and mass transfer model, SNTHERM.89, was used to calculate snow grain growth. Grain-sizes from the model and measurements of grain bond areas provided estimates of the surface-to-volume ratio of the bulk snow, which were transformed to geometrically-equivalent sphere sizes. An inversion technique based on a discrete-ordinate model of the directional reflectance recovered optically-equivalent sphere sizes from reflectance measurements at 1.075 μm. The predictions of equivalent sphere sizes from the snow model and the recovered optical sphere sizes from the inversion method were compared with stereological measurements from snow sections. The geometrically-equivalent and optically-equivalent grain-sizes showed good agreement with each other and with stereological measurements from snow a few days old. The predictions of the reflectance inversion method also compared favorably with geometrically-equivalent grain-sizes measured from a melt-freeze surface crust. This investigation showed the potential for fully coupling snow property simulations with models to predict the spectral reflectance of snow.
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Davis, Robert E., Anne W. Nolin, Rachel Jordan, and Jeff Dozier. "Towards predicting temporal changes of the spectral signature of snow in visible and near-infrared wavelengths." Annals of Glaciology 17 (1993): 143–48. http://dx.doi.org/10.3189/s026030550001274x.
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This study links two models, one that simulates changes in snow microstructure and one that recovers microstructure properties from measurements of snow reflectance. An energy and mass transfer model, SNTHERM.89, was used to calculate snow grain growth. Grain-sizes from the model and measurements of grain bond areas provided estimates of the surface-to-volume ratio of the bulk snow, which were transformed to geometrically-equivalent sphere sizes. An inversion technique based on a discrete-ordinate model of the directional reflectance recovered optically-equivalent sphere sizes from reflectance measurements at 1.075 μm. The predictions of equivalent sphere sizes from the snow model and the recovered optical sphere sizes from the inversion method were compared with stereological measurements from snow sections. The geometrically-equivalent and optically-equivalent grain-sizes showed good agreement with each other and with stereological measurements from snow a few days old. The predictions of the reflectance inversion method also compared favorably with geometrically-equivalent grain-sizes measured from a melt-freeze surface crust. This investigation showed the potential for fully coupling snow property simulations with models to predict the spectral reflectance of snow.
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He, Cenlin, Kuo-Nan Liou, and Yoshi Takano. "Resolving Size Distribution of Black Carbon Internally Mixed With Snow: Impact on Snow Optical Properties and Albedo." Geophysical Research Letters 45, no. 6 (March 25, 2018): 2697–705. http://dx.doi.org/10.1002/2018gl077062.
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Leppänen, L., A. Kontu, J. Vehviläinen, J. Lemmetyinen, and J. Pulliainen. "Comparison of traditional and optical grain-size field measurements with SNOWPACK simulations in a taiga snowpack." Journal of Glaciology 61, no. 225 (2015): 151–62. http://dx.doi.org/10.3189/2015jog14j026.
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AbstractKnowledge of snow microstructure is relevant for modelling the physical properties of snow cover and for simulating the propagation of electromagnetic waves in remote-sensing applications. Characterization of the microstructure in field conditions is, however, a challenging task due to the complex, sintered and variable nature of natural snow cover. A traditional measure applied as a proxy of snow microstructure, which can also be determined in field conditions, is the visually estimated snow grain size. Developing techniques also allow measurement, for example, of the specific surface area (SSA) of snow, from which the optical-equivalent grain size can be derived. The physical snow model SNOWPACK simulates evolution of snow parameters from meteorological forcing data. In this study we compare an extensive experimental dataset of measurements of traditional grain size and SSA-derived optical grain size with SNOWPACK simulations of grain-size parameters. On average, a scaling factor of 1.2 is required to match traditional grain-size observations with the corresponding SNOWPACK simulation; a scaling factor of 2.1 was required for the optical equivalent grain size. Standard deviations of scaling factors for the winters of 2011/12 and 2012/13 were 0.36 and 0.42, respectively. The largest scaling factor was needed in early winter and under melting conditions.
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Ehrlich, André, Eike Bierwirth, Larysa Istomina, and Manfred Wendisch. "Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing." Atmospheric Measurement Techniques 10, no. 9 (September 4, 2017): 3215–30. http://dx.doi.org/10.5194/amt-10-3215-2017.
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Abstract. The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.
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Cook, Joseph M., Andrew J. Hodson, Alex S. Gardner, Mark Flanner, Andrew J. Tedstone, Christopher Williamson, Tristram D. L. Irvine-Fynn, Johan Nilsson, Robert Bryant, and Martyn Tranter. "Quantifying bioalbedo: a new physically based model and discussion of empirical methods for characterising biological influence on ice and snow albedo." Cryosphere 11, no. 6 (November 17, 2017): 2611–32. http://dx.doi.org/10.5194/tc-11-2611-2017.
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Abstract. The darkening effects of biological impurities on ice and snow have been recognised as a control on the surface energy balance of terrestrial snow, sea ice, glaciers and ice sheets. With a heightened interest in understanding the impacts of a changing climate on snow and ice processes, quantifying the impact of biological impurities on ice and snow albedo (bioalbedo) and its evolution through time is a rapidly growing field of research. However, rigorous quantification of bioalbedo has remained elusive because of difficulties in isolating the biological contribution to ice albedo from that of inorganic impurities and the variable optical properties of the ice itself. For this reason, isolation of the biological signature in reflectance data obtained from aerial/orbital platforms has not been achieved, even when ground-based biological measurements have been available. This paper provides the cell-specific optical properties that are required to model the spectral signatures and broadband darkening of ice. Applying radiative transfer theory, these properties provide the physical basis needed to link biological and glaciological ground measurements with remotely sensed reflectance data. Using these new capabilities we confirm that biological impurities can influence ice albedo, then we identify 10 challenges to the measurement of bioalbedo in the field with the aim of improving future experimental designs to better quantify bioalbedo feedbacks. These challenges are (1) ambiguity in terminology, (2) characterising snow or ice optical properties, (3) characterising solar irradiance, (4) determining optical properties of cells, (5) measuring biomass, (6) characterising vertical distribution of cells, (7) characterising abiotic impurities, (8) surface anisotropy, (9) measuring indirect albedo feedbacks, and (10) measurement and instrument configurations. This paper aims to provide a broad audience of glaciologists and biologists with an overview of radiative transfer and albedo that could support future experimental design.
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Istomina, L. G., W. von Hoyningen-Huene, A. A. Kokhanovsky, and J. P. Burrows. "The detection of cloud free snow covered areas using AATSR measurements." Atmospheric Measurement Techniques Discussions 3, no. 2 (March 24, 2010): 1099–132. http://dx.doi.org/10.5194/amtd-3-1099-2010.
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Abstract. A new method to detect cloud free snow covered areas is developed using the measurements by the Advanced Along Track Scanning Radiometer (AATSR) on board the ENVISAT satellite in order to discriminate clear snow fields for the retrieval of aerosol optical thickness or snow properties. The algorithm uses seven AATSR channels from VIS to TIR and analyzes the spectral behavior of each pixel in order to recognize the spectral signature of snow. The algorithm includes a set of relative thresholds and combines all seven channels into one flexible criterion, which allows us to filter out all the pixels with spectral behavior similar to that of snow. The algorithm does not use any kind of morphological criteria and does not require the studied surface to have any special structure. The snow spectral shape criterion was determined by a comprehensive theoretical study, which included radiative transfer simulations for various atmospheric conditions as well as studying existing models and measurements of snow optical and physical properties in different spectral bands. The method has been optimized to detect cloud free snow covered areas, and does not produce cloud/land/ocean/snow mask. However, the algorithm can be extended and be able to discriminate various kinds of surfaces. The presented method has been validated against Micro Pulse Lidar data and compared to MODIS cloud mask over snow covered areas, showing quite good correspondence to each other.
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Gallet, J. C., F. Domine, and M. Dumont. "Measuring the specific surface area of wet snow using 1310 nm reflectance." Cryosphere Discussions 7, no. 5 (October 31, 2013): 5255–79. http://dx.doi.org/10.5194/tcd-7-5255-2013.
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Abstract. The specific surface area (SSA) of snow can be used as an objective measurement of grain size and is therefore a central variable to describe snow physical properties such as albedo. Snow SSA can now be easily measured in the field using optical methods based on infrared reflectance. However, existing optical methods have only been validated for dry snow. Here we test the possibility to use the DUFISSS instrument, based on the measurement of the 1310 nm reflectance of snow with an integrating sphere, to measure the SSA of wet snow. We perform cold room experiments where we measure the SSA of a wet snow sample, freeze it and measure it again, to quantify the difference in reflectance between frozen and wet snow. We study snow samples in the SSA range 12–37 m2 kg−1 and in the mass liquid water content range 5–32%. We conclude that the SSA of wet snow can be obtained from the measurement of its 1310 nm reflectance using three simple steps. In most cases, the SSA thus obtained is less than 10% different from the value that would have been obtained if the sample had been considered dry, so that the three simple steps constitute a minor correction. We also run two optical models to interpret the results, but no model reproduces correctly the water-ice distribution in wet snow, so that their predictions of wet snow reflectance are imperfect.
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Seidel, Felix C., Karl Rittger, S. McKenzie Skiles, Noah P. Molotch, and Thomas H. Painter. "Case study of spatial and temporal variability of snow cover, grain size, albedo and radiative forcing in the Sierra Nevada and Rocky Mountain snowpack derived from imaging spectroscopy." Cryosphere 10, no. 3 (June 15, 2016): 1229–44. http://dx.doi.org/10.5194/tc-10-1229-2016.
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Abstract. Quantifying the spatial distribution and temporal change in mountain snow cover, microphysical and optical properties is important to improve our understanding of the local energy balance and the related snowmelt and hydrological processes. In this paper, we analyze changes of snow cover, optical-equivalent snow grain size (radius), snow albedo and radiative forcing by light-absorbing impurities in snow and ice (LAISI) with respect to terrain elevation and aspect at multiple dates during the snowmelt period. These snow properties are derived from the NASA/JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data from 2009 in California's Sierra Nevada and from 2011 in Colorado's Rocky Mountains, USA. Our results show a linearly decreasing snow cover during the ablation period in May and June in the Rocky Mountains and a snowfall-driven change in snow cover in the Sierra Nevada between February and May. At the same time, the snow grain size is increasing primarily at higher elevations and north-facing slopes from 200 microns to 800 microns on average. We find that intense snowmelt renders the mean grain size almost invariant with respect to elevation and aspect. Our results confirm the inverse relationship between snow albedo and grain size, as well as between snow albedo and radiative forcing by LAISI. At both study sites, the mean snow albedo value decreases from approximately 0.7 to 0.5 during the ablation period. The mean snow grain size increased from approximately 150 to 650 microns. The mean radiative forcing increases from 20 W m−2 up to 200 W m−2 during the ablation period. The variability of snow albedo and grain size decreases in general with the progression of the ablation period. The spatial variability of the snow albedo and grain size decreases through the melt season while the spatial variability of radiative forcing remains constant.
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Istomina, L. G., W. von Hoyningen-Huene, A. A. Kokhanovsky, and J. P. Burrows. "The detection of cloud-free snow-covered areas using AATSR measurements." Atmospheric Measurement Techniques 3, no. 4 (August 3, 2010): 1005–17. http://dx.doi.org/10.5194/amt-3-1005-2010.
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Abstract. A new method to detect cloud-free snow-covered areas has been developed using the measurements by the Advanced Along Track Scanning Radiometer (AATSR) on board the ENVISAT satellite in order to discriminate clear snow fields for the retrieval of aerosol optical thickness or snow properties. The algorithm uses seven AATSR channels from visible (VIS) to thermal infrared (TIR) and analyses the spectral behaviour of each pixel in order to recognize the spectral signature of snow. The algorithm includes a set of relative thresholds and combines all seven channels into one flexible criterion, which allows us to filter out all the pixels with spectral behaviour similar to that of snow. The algorithm does not use any kind of morphological criteria and does not require the studied surface to have any special structure. The snow spectral shape criterion was determined by a comprehensive theoretical study, which included radiative transfer simulations for various atmospheric conditions as well as studying existing models and measurements of optical and physical properties of snow in different spectral bands. The method has been optimized to detect cloud-free snow-covered areas, and does not produce cloud/land/ocean/snow mask. However, the algorithm can be extended and able to discriminate various kinds of surfaces. The presented method has been validated against Micro Pulse Lidar data and compared to Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask over snow-covered areas, showing quite good correspondence to each other. Comparison of both MODIS cloud mask and presented snow mask to AATSR operational cloud mask showed that in some cases of snow surface the accuracy of AATSR operational cloud mask is questionable.
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Lamare, Maxim, Marie Dumont, Ghislain Picard, Fanny Larue, François Tuzet, Clément Delcourt, and Laurent Arnaud. "Simulating optical top-of-atmosphere radiance satellite images over snow-covered rugged terrain." Cryosphere 14, no. 11 (November 14, 2020): 3995–4020. http://dx.doi.org/10.5194/tc-14-3995-2020.
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Abstract. The monitoring of snow-covered surfaces on Earth is largely facilitated by the wealth of satellite data available, with increasing spatial resolution and temporal coverage over the last few years. Yet to date, retrievals of snow physical properties still remain complicated in mountainous areas, owing to the complex interactions of solar radiation with terrain features such as multiple scattering between slopes, exacerbated over bright surfaces. Existing physically based models of solar radiation across rough scenes are either too complex and resource-demanding for the implementation of systematic satellite image processing, not designed for highly reflective surfaces such as snow, or tied to a specific satellite sensor. This study proposes a new formulation, combining a forward model of solar radiation over rugged terrain with dedicated snow optics into a flexible multi-sensor tool that bridges a gap in the optical remote sensing of snow-covered surfaces in mountainous regions. The model presented here allows one to perform rapid calculations over large snow-covered areas. Good results are obtained even for extreme cases, such as steep shadowed slopes or, on the contrary, strongly illuminated sun-facing slopes. Simulations of Sentinel-3 OLCI (Ocean and Land Colour Instrument) scenes performed over a mountainous region in the French Alps allow us to reduce the bias by up to a factor of 6 in the visible wavelengths compared to methods that account for slope inclination only. Furthermore, the study underlines the contribution of the individual fluxes to the total top-of-atmosphere radiance, highlighting the importance of reflected radiation from surrounding slopes which, in midwinter after a recent snowfall (13 February 2018), accounts on average for 7 % of the signal at 400 nm and 16 % at 1020 nm (on 13 February 2018), as well as of coupled diffuse radiation scattered by the neighbourhood, which contributes to 18 % at 400 nm and 4 % at 1020 nm. Given the importance of these contributions, accounting for slopes and reflected radiation between terrain features is a requirement for improving the accuracy of satellite retrievals of snow properties over snow-covered rugged terrain. The forward formulation presented here is the first step towards this goal, paving the way for future retrievals.
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El Oufir, Mohamed Karim, Karem Chokmani, Anas El Alem, Hachem Agili, and Monique Bernier. "Seasonal Snowpack Classification Based on Physical Properties Using Near-Infrared Proximal Hyperspectral Data." Sensors 21, no. 16 (August 4, 2021): 5259. http://dx.doi.org/10.3390/s21165259.
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This paper proposes an innovative method for classifying the physical properties of the seasonal snowpack using near-infrared (NIR) hyperspectral imagery to discriminate the optical classes of snow at different degrees of metamorphosis. This imaging system leads to fast and non-invasive assessment of snow properties. Indeed, the spectral similarity of two samples indicates the similarity of their chemical composition and physical characteristics. This can be used to distinguish, without a priori recognition, between different classes of snow solely based on spectral information. A multivariate data analysis approach was used to validate this hypothesis. A principal component analysis (PCA) was first applied to the NIR spectral data to analyze field data distribution and to select the spectral range to be exploited in the classification. Next, an unsupervised classification was performed on the NIR spectral data to select the number of classes. Finally, a confusion matrix was calculated to evaluate the accuracy of the classification. The results allowed us to distinguish three snow classes of typical shape and size (weakly, moderately, and strongly metamorphosed snow). The evaluation of the proposed approach showed that it is possible to classify snow with a success rate of 85% and a kappa index of 0.75. This illustrates the potential of NIR hyperspectral imagery to distinguish between three snow classes with satisfactory success rates. This work will open new perspectives for the modelling of physical parameters of snow using spectral data.
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HORTON, SIMON, and BRUCE JAMIESON. "Spectral measurements of surface hoar crystals." Journal of Glaciology 63, no. 239 (March 8, 2017): 477–86. http://dx.doi.org/10.1017/jog.2017.6.
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ABSTRACTSurface hoar crystals are common on the surface of mountain snow covers. Once buried, layers of large plate-shaped surface hoar crystals are prone to releasing dangerous snow-slab avalanches. Since snow microstructure influences the optical properties of snow, remote sensors could potentially detect the formation of surface hoar and other snow types associated with avalanche release. The spectral reflectance of 377 snow samples was measured with a field spectrometer between 750 and 2500 nm, including 161 samples of surface hoar. Morphological snow shapes associated with critical avalanche layers (surface hoar, near-surface faceted particles and depth hoar) had lower average reflectance factors than non-critical snow shapes at infrared wavelengths. Needle-shaped surface hoar was more reflective than plate-shaped surface hoar, but there were no significant differences between different sizes of surface hoar. Normalized difference indices calculated with reflectance from two wavelength bands is presented as a potential method to classify critical snow surfaces remotely, although melt-freeze crusts near the surface complicated the classification. Accordingly, further studying on the effect of melt-freeze crusts and quantification of the bidirectional reflective properties of critical snow types is needed.
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Di Mauro, Biagio, Giovanni Baccolo, Roberto Garzonio, Claudia Giardino, Dario Massabò, Andrea Piazzalunga, Micol Rossini, and Roberto Colombo. "Impact of impurities and cryoconite on the optical properties of the Morteratsch Glacier (Swiss Alps)." Cryosphere 11, no. 6 (November 1, 2017): 2393–409. http://dx.doi.org/10.5194/tc-11-2393-2017.
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Abstract. The amount of reflected energy by snow and ice plays a fundamental role in their melting processes. Different non-ice materials (carbonaceous particles, mineral dust (MD), microorganisms, algae, etc.) can decrease the reflectance of snow and ice promoting the melt. The object of this paper is to assess the capability of field and satellite (EO-1 Hyperion) hyperspectral data to characterize the impact of light-absorbing impurities (LAIs) on the surface reflectance of ice and snow of the Vadret da Morteratsch, a large valley glacier in the Swiss Alps. The spatial distribution of both narrow-band and broad-band indices derived from Hyperion was analyzed in relation to ice and snow impurities. In situ and laboratory reflectance spectra were acquired to characterize the optical properties of ice and cryoconite samples. The concentrations of elemental carbon (EC), organic carbon (OC) and levoglucosan were also determined to characterize the impurities found in cryoconite. Multi-wavelength absorbance spectra were measured to compare the optical properties of cryoconite samples and local moraine sediments. In situ reflectance spectra showed that the presence of impurities reduced ice reflectance in visible wavelengths by 80–90 %. Satellite data also showed the outcropping of dust during the melting season in the upper parts of the glacier, revealing that seasonal input of atmospheric dust can decrease the reflectance also in the accumulation zone of the glacier. The presence of EC and OC in cryoconite samples suggests a relevant role of carbonaceous and organic material in the darkening of the ablation zone. This darkening effect is added to that caused by fine debris from lateral moraines, which is assumed to represent a large fraction of cryoconite. Possible input of anthropogenic activity cannot be excluded and further research is needed to assess the role of human activities in the darkening process of glaciers observed in recent years.
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Green, Robert O., Jeff Dozier, Dar Roberts, and Tom Painter. "Spectral snow-reflectance models for grain-size and liquid-water fraction in melting snow for the solar-reflected spectrum." Annals of Glaciology 34 (2002): 71–73. http://dx.doi.org/10.3189/172756402781817987.
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AbstractTwo spectral snow-reflectance models that account for the effects of grain-size and liquid-water fraction are described and initial validation results presented. The models are based upon the spectral complex refractive index of liquid water and ice in the region from 400 to 2500 nm. Mie scattering calculations are used to specify the essential optical properties of snow in the models. Two approaches are explored to model the effect of liquid water in the snow. The first accounts for the liquid water as separate spheres interspersed with ice spheres in the snow layer. The second accounts for the liquid water as coatings on ice grains in the snow layer. A discrete-ordinate radiative transfer code is used to model the spectral reflectance of the snow for the Mie-calculated optical properties. Both the interspersed- and coated-sphere models show that the snow-absorption feature at 1030 nm shifts to shorter wavelength as the liquid-water content increased. The expression of these shifts is different for the two models. A comparison of the models with a spectral measurement of frozen and melting snow shows better agreement with the coated-sphere model. A spectral fitting algorithm was developed and tested with the coated-sphere model to derive the grain-size and liquid-water fraction from snow spectral reflectance measurements. Consistent values of grain-size and liquid water were retrieved from the measured snow spectra. This research demonstrates the use of spectral models and spectral measurements to derive surface snow grain-size and liquid-water fraction. The results of this research may be extended to regional and greater scales using data acquired by airborne and spaceborne imaging spectrometers for contributions to energy balance and hydrological modeling.
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Gallet, J. C., F. Domine, and M. Dumont. "Measuring the specific surface area of wet snow using 1310 nm reflectance." Cryosphere 8, no. 4 (July 3, 2014): 1139–48. http://dx.doi.org/10.5194/tc-8-1139-2014.
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Abstract. The specific surface area (SSA) of snow can be used as an objective measurement of grain size and is therefore a central variable to describe snow physical properties such as albedo. Snow SSA can now be easily measured in the field using optical methods based on infrared reflectance. However, existing optical methods have only been validated for dry snow. Here we test the possibility to use the DUFISSS instrument, based on the measurement of the 1310 nm reflectance of snow with an integrating sphere, to measure the SSA of wet snow. We perform cold room experiments where we measure the SSA of a wet snow sample, freeze it and measure it again, to quantify the difference in reflectance between frozen and wet snow. We study snow samples in the SSA range 12–37 m2 kg−1 and in the mass liquid water content (LWC) range 5–32%. We conclude that the SSA of wet snow can be obtained from the measurement of its 1310 nm reflectance using three simple steps. In most cases, the SSA thus obtained is less than 10 {%} different from the value that would have been obtained if the sample had been considered dry, so that the three simple steps constitute a minor correction. We also run two optical models to interpret the results, but no model reproduces correctly the water–ice distribution in wet snow, so that their predictions of wet snow reflectance are imperfect. The correction on the determination of wet snow SSA using the DUFISSS instrument gives an overall uncertainty better than 11%, even if the LWC is unknown. If SSA is expressed as a surface to volume ratio (e.g., in mm−1), the uncertainty is then 13% because of additional uncertainties in the determination of the volume of ice and water when the LWC is unknown.
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Zatko, Maria, Joseph Erbland, Joel Savarino, Lei Geng, Lauren Easley, Andrew Schauer, Timothy Bates, et al. "The magnitude of the snow-sourced reactive nitrogen flux to the boundary layer in the Uintah Basin, Utah, USA." Atmospheric Chemistry and Physics 16, no. 21 (November 9, 2016): 13837–51. http://dx.doi.org/10.5194/acp-16-13837-2016.
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Abstract. Reactive nitrogen (Nr = NO, NO2, HONO) and volatile organic carbon emissions from oil and gas extraction activities play a major role in wintertime ground-level ozone exceedance events of up to 140 ppb in the Uintah Basin in eastern Utah. Such events occur only when the ground is snow covered, due to the impacts of snow on the stability and depth of the boundary layer and ultraviolet actinic flux at the surface. Recycling of reactive nitrogen from the photolysis of snow nitrate has been observed in polar and mid-latitude snow, but snow-sourced reactive nitrogen fluxes in mid-latitude regions have not yet been quantified in the field. Here we present vertical profiles of snow nitrate concentration and nitrogen isotopes (δ15N) collected during the Uintah Basin Winter Ozone Study 2014 (UBWOS 2014), along with observations of insoluble light-absorbing impurities, radiation equivalent mean ice grain radii, and snow density that determine snow optical properties. We use the snow optical properties and nitrate concentrations to calculate ultraviolet actinic flux in snow and the production of Nr from the photolysis of snow nitrate. The observed δ15N(NO3−) is used to constrain modeled fractional loss of snow nitrate in a snow chemistry column model, and thus the source of Nr to the overlying boundary layer. Snow-surface δ15N(NO3−) measurements range from −5 to 10 ‰ and suggest that the local nitrate burden in the Uintah Basin is dominated by primary emissions from anthropogenic sources, except during fresh snowfall events, where remote NOx sources from beyond the basin are dominant. Modeled daily averaged snow-sourced Nr fluxes range from 5.6 to 71 × 107 molec cm−2 s−1 over the course of the field campaign, with a maximum noontime value of 3.1 × 109 molec cm−2 s−1. The top-down emission estimate of primary, anthropogenic NOx in Uintah and Duchesne counties is at least 300 times higher than the estimated snow NOx emissions presented in this study. Our results suggest that snow-sourced reactive nitrogen fluxes are minor contributors to the Nr boundary layer budget in the highly polluted Uintah Basin boundary layer during winter 2014.
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Marks, A. A., and M. D. King. "The effect of snow/sea ice type on the response of albedo and light penetration depth (<i>e</i>-folding depth) to increasing black carbon." Cryosphere Discussions 8, no. 1 (February 7, 2014): 1023–56. http://dx.doi.org/10.5194/tcd-8-1023-2014.
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Abstract. The optical properties of snow/sea ice vary with age and by the processes they were formed, giving characteristic types of snow and sea ice. The response of albedo and light penetration depth (e-folding depth) to increasing mass-ratio of black carbon is shown to depend on the snow and sea ice type and the thickness of the snow or sea ice. The response of albedo and e-folding depth of three different types of snow (cold polar snow, windpacked snow and melting snow) and three sea ice (multi-year ice, first-year ice and melting sea ice) to increasing black carbon is calculated using a coupled atmosphere–snow/sea ice radiative-transfer model (TUV-snow), over the optical wavelengths of 300–700 nm. The snow and sea ice types are defined by a scattering-cross section, density and asymmetry parameter. The relative change in albedo of a melting snowpack is a factor of four more responsive to additions of black carbon compared to cold polar snow over a black carbon increase from 1 to 50 ng g−1. While the relative change in albedo of a melting sea ice is a factor of two more responsive to additions of black carbon compared to multi-year ice for the same black carbon mass-ratio increase. The response of e-folding depth is effectively not dependent on snow/sea ice type. The albedo of sea ice is more responsive to increased mass-ratios of black carbon than snow.
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Libois, Quentin, Ghislain Picard, Marie Dumont, Laurent Arnaud, Claude Sergent, Evelyne Pougatch, Marcel Sudul, and David Vial. "Experimental determination of the absorption enhancement parameter of snow." Journal of Glaciology 60, no. 222 (2014): 714–24. http://dx.doi.org/10.3189/2014j0g14j015.
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Abstract In optical models snow is commonly treated as a disperse collection of particles. In this representation, the penetration depth of solar radiation is sensitive to the shape of the particles, in particular to the absorption enhancement parameter, B, that quantifies the lengthening of the photon path inside grains due to internal multiple reflections. Spherical grains, with theoretical B = 1.25, are often used. We propose an experimental method to determine B, and apply it to 36 snow samples and 56 snow strata. The method is based on radiative transfer modeling and combined measurements of reflectance and irradiance profiles. Such measurements are performed in the laboratory and in the field, in Antarctica and the French Alps. The retrieved values of B are in the range 0.7–2.4, with a wide peak between 1.4 and 1.8. An analysis of measurement error propagation based on a Bayesian framework shows that the uncertainty on B is ± 0.1, which is the order of magnitude of variations between different snow types. Thus, no systematic link between B and snow type can be inferred. Here we recommend using shapes with B = 1.6 to model snow optical properties, rather than spherical grains.
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Libois, Quentin, Ghislain Picard, Marie Dumont, Laurent Arnaud, Claude Sergent, Evelyne Pougatch, Marcel Sudul, and David Vial. "Experimental determination of the absorption enhancement parameter of snow." Journal of Glaciology 60, no. 222 (2014): 714–24. http://dx.doi.org/10.3189/2014jog14j015.
Full textAbstract:
AbstractIn optical models snow is commonly treated as a disperse collection of particles. In this representation, the penetration depth of solar radiation is sensitive to the shape of the particles, in particular to the absorption enhancement parameter, B, that quantifies the lengthening of the photon path inside grains due to internal multiple reflections. Spherical grains, with theoretical B = 1.25, are often used. We propose an experimental method to determine B, and apply it to 36 snow samples and 56 snow strata. The method is based on radiative transfer modeling and combined measurements of reflectance and irradiance profiles. Such measurements are performed in the laboratory and in the field, in Antarctica and the French Alps. The retrieved values of B are in the range 0.7–2.4, with a wide peak between 1.4 and 1.8. An analysis of measurement error propagation based on a Bayesian framework shows that the uncertainty on B is ± 0.1, which is the order of magnitude of variations between different snow types. Thus, no systematic link between B and snow type can be inferred. Here we recommend using shapes with B = 1.6 to model snow optical properties, rather than spherical grains.
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Wang, Jun Fa, Xiao Xia Li, Ya Qin Li, and Teng Fei Zhuang. "Experimental Analysis on Fracture Characteristics and Material Properties of Compacted Ice and Snow." Applied Mechanics and Materials 540 (April 2014): 43–47. http://dx.doi.org/10.4028/www.scientific.net/amm.540.43.
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It is benefit to improve the snow clearing effect, reduce energy consumption, conserve resources and enhance the performance of the machine was pointed. Using the depth into show, concave disc spacing and the angle between marching directions as factors, snow pack volume flaking, fracture width and snow clearing resistance as objective the three factors five levels orthogonal rotation test was conducted. The interaction between effect spacing of tools ,the fractures great influence on clearing efficiency and energy consumption when clearing the compacted ice and snow by using multi-blade cutting mode was found through the concave disc cutting test. The relation response surface graph was obtained through the analysis of test data by using the Design-Expert 6.0 software. The optimal parameters are: the angle between marching directions is 13°, depth into snow is 38mm~44mm, concave disc spacing is 14mm~17mm, which made the snow pack volume flaking is 124cm3~130cm3, the fracture width is 79mm~80mm, the snow clearing resistance is 0.6KN~0.65KN.
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Willeit, Matteo, and Andrey Ganopolski. "The importance of snow albedo for ice sheet evolution over the last glacial cycle." Climate of the Past 14, no. 5 (May 31, 2018): 697–707. http://dx.doi.org/10.5194/cp-14-697-2018.
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Abstract. The surface energy and mass balance of ice sheets strongly depends on the amount of solar radiation absorbed at the surface, which is mainly controlled by the albedo of snow and ice. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the representation of snow albedo in the model. It is well known that the albedo of snow depends strongly on snow grain size and the content of light-absorbing impurities. Excluding either the snow aging effect or the dust darkening effect on snow albedo leads to an excessive ice build-up during glacial times and consequently to a failure in simulating deglaciation. While the effect of snow grain growth on snow albedo is well constrained, the albedo reduction due to the presence of dust in snow is much more uncertain because the light-absorbing properties of dust vary widely as a function of dust mineral composition. We also show that assuming slightly different optical properties of dust leads to very different ice sheet and climate evolutions in the model. Conversely, ice sheet evolution is less sensitive to the choice of ice albedo in the model. We conclude that a proper representation of snow albedo is a fundamental prerequisite for a successful simulation of glacial cycles.
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Krol, Quirine, and Henning Löwe. "Relating optical and microwave grain metrics of snow: the relevance of grain shape." Cryosphere 10, no. 6 (November 21, 2016): 2847–63. http://dx.doi.org/10.5194/tc-10-2847-2016.
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Abstract. Grain shape is commonly understood as a morphological characteristic of snow that is independent of the optical diameter (or specific surface area) influencing its physical properties. In this study we use tomography images to investigate two objectively defined metrics of grain shape that naturally extend the characterization of snow in terms of the optical diameter. One is the curvature length λ2, related to the third-order term in the expansion of the two-point correlation function, and the other is the second moment μ2 of the chord length distributions. We show that the exponential correlation length, widely used for microwave modeling, can be related to the optical diameter and λ2. Likewise, we show that the absorption enhancement parameter B and the asymmetry factor gG, required for optical modeling, can be related to the optical diameter and μ2. We establish various statistical relations between all size metrics obtained from the two-point correlation function and the chord length distribution. Overall our results suggest that the characterization of grain shape via λ2 or μ2 is virtually equivalent since both capture similar aspects of size dispersity. Our results provide a common ground for the different grain metrics required for optical and microwave modeling of snow.
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Mcdonald, Shaun, Theodoro Koulis, Jens Ehn, Karley Campbell, Michel Gosselin, and C. J. Mundy. "A functional regression model for predicting optical depth and estimating attenuation coefficients in sea-ice covers near Resolute Passage, Canada." Annals of Glaciology 56, no. 69 (2015): 147–54. http://dx.doi.org/10.3189/2015aog69a004.
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AbstractThe spectral dependence of natural light transmittance on ice algae concentration and snow depth in Arctic sea ice provides the potential to study the changing bottom-ice ecosystem using optical relationships. In this paper, we consider the use of functional data analysis techniques to describe such relationships. Specifically, we created a functional regression model describing spectral optical depth as a function of chlorophyllaconcentration, snow depth and ice thickness. Measurements of the aforementioned covariates and surface and transmitted spectral irradiance were collected on landfast first-year sea ice in the High Arctic near Resolute Passage, Canada, during the spring of 2011 and used as model input. The derived model explains 75–84.5% of the variation in the observed spectral optical depth curves. No prior assumptions of snow/sea-ice optical properties are required in the application of this technique, as the model estimates the attenuation coefficients of each covariate using only the measurements mentioned above. The quality and simplicity of the model highlight the potential of functional data analysis to study the Arctic marine ecosystem.
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Marks, A. A., and M. D. King. "The effect of snow/sea ice type on the response of albedo and light penetration depth (<i>e</i>-folding depth) to increasing black carbon." Cryosphere 8, no. 5 (September 3, 2014): 1625–38. http://dx.doi.org/10.5194/tc-8-1625-2014.
Full textAbstract:
Abstract. The optical properties of snow/sea ice vary with age and by the processes they were formed, giving characteristic types of snow and sea ice. The response of albedo and light penetration depth (e-folding depth) to increasing mass ratio of black carbon is shown to depend on the snow and sea ice type and the thickness of the snow or sea ice. The response of albedo and e-folding depth of three different types of snow (cold polar snow, wind-packed snow and melting snow) and three sea ice (multi-year ice, first-year ice and melting sea ice) to increasing mass ratio of black carbon is calculated using a coupled atmosphere–snow/sea ice radiative-transfer model (TUV-snow), over the optical wavelengths of 300–800 nm. The snow and sea ice types are effectively defined by a scattering cross-section, density and asymmetry parameter. The relative change in albedo and e-folding depth of each of the three snow and three sea ice types with increasing mass ratio of black carbon is considered relative to a base case of 1 ng g−1 of black carbon. The relative response of each snow and sea ice type is intercompared to examine how different types of snow and sea ice respond relative to each other. The relative change in albedo of a melting snowpack is a factor of four more responsive to additions of black carbon compared to cold polar snow over a black carbon increase from 1 to 50 ng g−1, while the relative change in albedo of a melting sea ice is a factor of two more responsive to additions of black carbon compared to multi-year ice for the same increase in mass ratio of black carbon. The response of e-folding depth is effectively not dependent on snow/sea ice type. The albedo of sea ice is more responsive to increasing mass ratios of black carbon than snow.
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Carlsen, Tim, Gerit Birnbaum, André Ehrlich, Veit Helm, Evelyn Jäkel, Michael Schäfer, and Manfred Wendisch. "Parameterizing anisotropic reflectance of snow surfaces from airborne digital camera observations in Antarctica." Cryosphere 14, no. 11 (November 12, 2020): 3959–78. http://dx.doi.org/10.5194/tc-14-3959-2020.
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Abstract. The surface reflection of solar radiation comprises an important boundary condition for solar radiative transfer simulations. In polar regions above snow surfaces, the surface reflection is particularly anisotropic due to low Sun elevations and the highly anisotropic scattering phase function of the snow crystals. The characterization of this surface reflection anisotropy is essential for satellite remote sensing over both the Arctic and Antarctica. To quantify the angular snow reflection properties, the hemispherical-directional reflectance factor (HDRF) of snow surfaces was derived from airborne measurements in Antarctica during austral summer in 2013/14. For this purpose, a digital 180∘ fish-eye camera (green channel, 490–585 nm wavelength band) was used. The HDRF was measured for different surface roughness conditions, optical-equivalent snow grain sizes, and solar zenith angles. The airborne observations covered an area of around 1000 km × 1000 km in the vicinity of Kohnen Station (75∘0′ S, 0∘4′ E) at the outer part of the East Antarctic Plateau. The observations include regions with higher (coastal areas) and lower (inner Antarctica) precipitation amounts and frequencies. The digital camera provided upward, angular-dependent radiance measurements from the lower hemisphere. The comparison of the measured HDRF derived for smooth and rough snow surfaces (sastrugi) showed significant differences, which are superimposed on the diurnal cycle. By inverting a semi-empirical kernel-driven bidirectional reflectance distribution function (BRDF) model, the measured HDRF of snow surfaces was parameterized as a function of solar zenith angle, surface roughness, and optical-equivalent snow grain size. This allows a direct comparison of the HDRF measurements with the BRDF derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite product MCD43. For the analyzed cases, MODIS observations (545–565 nm wavelength band) generally underestimated the anisotropy of the surface reflection. The largest deviations were found for the volumetric model weight fvol (average underestimation by a factor of 10). These deviations are likely linked to short-term changes in snow properties.