Spectral Albedo Of Snow Research Articles

Optical effect of Andean mineral dust onto snow surface spectral albedo

Light absorbing particles (LAPs) present high absorbance and contribute to reducing the snow albedo when deposited on snow surfaces. This deposition can be caused by aerosols transported from natural or anthropogenic, either distant or nearby sources. In this study, snow was artificially contaminated with soil samples collected in the Central Andes (near El Yeso dam) to simulate the most common nearby source of Mineral Dust (MD) deposition onto snow surface. Andean soil samples previously conditioned were characterized through Single Particle Optical Sizing (SPOS), X-ray diffraction (XRD) analysis, and Scanning Electron Microscope (SEM) for the determination of optical properties. Spectral snow albedo was measured in situ with a spectroradiometric system. To evaluate the heterogeneity of the particle distribution over the snow surface, aerial photographs were taken with a drone to apply a visual color segmentation of the surface and to determine the equivalent MD concentration. Experimental snow albedo was compared with theoretical values obtained with the OptiPar radiative transfer model. Inputs for the model were: the MD refractive index (calculated from the mineralogical composition and morphology of MD) and particle size, cloudiness, snow density, surface roughness, snow grain size, and LAPs concentration (obtained from the snow samples collected during the experiments and analyzed in the laboratory). Small black carbon concentrations were found in natural snow and considered in the simulations. Spectral albedo measurements showed high albedo reductions in the UV and VIS range (300–800 nm), being less significant in the NIR range (800–1700 nm). A nonlinear behavior was observed in broadband albedo when increasing MD concentration. For lower values of MD concentration (lower than 1500 mg⋅kg−1), a significant albedo reduction rate of 0.1 units per 1000 mg⋅kg−1 was found, while at higher concentrations (¿ 3500 mg⋅kg−1), such reduction tends to the minimum. Simulated values with OptiPar are in agreement with measured albedo, but some differences are observed, probably due to the refractive index considered, the snow surface roughness, and the non-uniform MD concentration in snow.

Changes in Snow Surface Albedo and Radiative Forcing in the Chilean Central Andes Measured by In Situ and Remote Sensing Data

Snow-covered regions are the main source of reflection of incident shortwave radiation on the Earth’s surface. The deposition of light-absorbing particles on these regions increases the capacity of snow to absorb radiation and decreases surface snow albedo, which intensifies the radiative forcing, leading to accelerated snowmelt and modifications of the hydrologic cycle. In this work, the changes in surface snow albedo and radiative forcing were investigated, induced by light-absorbing particles in the Upper Aconcagua River Basin (Chilean Central Andes) using remote sensing satellite data (MODIS), in situ spectral snow albedo measurements, and the incident shortwave radiation during the austral winter months (May to August) for the 2004–2016 period. To estimate the changes in snow albedo and radiative forcing, two spectral ranges were defined: (i) an enclosed range between 841 and 876 nm, which isolates the effects of black carbon, an important light-absorbing particle derived from anthropogenic activities, and (ii) a broadband range between 300 and 2500 nm. The results indicate that percent variations in snow albedo in the enclosed range are higher than in the broadband range, regardless of the total amount of radiation received, which may be attributed to the presence of light-absorbing particles, as these particles have a greater impact on surface snow albedo at wavelengths in the enclosed band than in the broadband band.

A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics

Abstract. A majority of snow radiative transfer models (RTMs) treat snow as a collection of idealized grains rather than an organized ice–air matrix. Here we present a generalized multi-layer photon-tracking RTM that simulates light reflectance and transmittance of snow based on X-ray microtomography images, treating snow as a coherent 3D structure rather than a collection of grains. The model uses a blended approach to expand ray-tracing techniques applied to sub-1 cm3 snow samples to snowpacks of arbitrary depths. While this framework has many potential applications, this study's effort is focused on simulating reflectance and transmittance in the visible and near infrared (NIR) through thin snowpacks as this is relevant for surface energy balance and remote sensing applications. We demonstrate that this framework fits well within the context of previous work and capably reproduces many known optical properties of a snow surface, including the dependence of spectral reflectance on the snow specific surface area and incident zenith angle as well as the surface bidirectional reflectance distribution function (BRDF). To evaluate the model, we compare it against reflectance data collected with a spectroradiometer at a field site in east-central Vermont. In this experiment, painted panels were inserted at various depths beneath the snow to emulate thin snow. The model compares remarkably well against the reflectance measured with a spectroradiometer, with an average RMSE of 0.03 in the 400–1600 nm range. Sensitivity simulations using this model indicate that snow transmittance is greatest in the visible wavelengths, limiting light penetration to the top 6 cm of the snowpack for fine-grain snow but increasing to 12 cm for coarse-grain snow. These results suggest that the 5 % transmission depth in snow can vary by over 6 cm according to the snow type.

Sensitivity of Antarctic surface climate to a new spectral snow albedo and radiative transfer scheme in RACMO2.3p3

Abstract. This study investigates the sensitivity of modeled surface melt and subsurface heating on the Antarctic ice sheet to a new spectral snow albedo and radiative transfer scheme in the Regional Atmospheric Climate Model (RACMO), version 2.3p3 (Rp3). We tune Rp3 to observations by performing several sensitivity experiments and assess the impact on temperature and melt by incrementally changing one parameter at a time. When fully tuned, Rp3 compares well with in situ and remote sensing observations of surface mass and energy balance, melt, near-surface and (sub)surface temperature, albedo and snow grain specific surface area. Near-surface snow temperature is especially sensitive to the prescribed fresh snow specific surface area and fresh dry snow metamorphism. These processes, together with the refreezing water grain size and subsurface heating, are important for melt around the margins of the Antarctic ice sheet. Moreover, small changes in the albedo and the aforementioned processes can lead to an order of magnitude overestimation of melt, locally leading to runoff and a reduced surface mass balance.

SNICAR-ADv3: a community tool for modeling spectral snow albedo

Abstract. The Snow, Ice, and Aerosol Radiative (SNICAR) model has been used in various capacities over the last 15 years to model the spectral albedo of snow with light-absorbing constituents (LACs). Recent studies have extended the model to include an adding-doubling two-stream solver and representations of non-spherical ice particles; carbon dioxide snow; snow algae; and new types of mineral dust, volcanic ash, and brown carbon. New options also exist for ice refractive indices and solar-zenith-angle-dependent surface spectral irradiances used to derive broadband albedo. The model spectral range was also extended deeper into the ultraviolet for studies of extraterrestrial and high-altitude cryospheric surfaces. Until now, however, these improvements and capabilities have not been merged into a unified code base. Here, we document the formulation and evaluation of the publicly available SNICAR-ADv3 source code, web-based model, and accompanying library of constituent optical properties. The use of non-spherical ice grains, which scatter less strongly into the forward direction, reduces the simulated albedo perturbations from LACs by ∼9 %–31 %, depending on which of the three available non-spherical shapes are applied. The model compares very well against measurements of snow albedo from seven studies, though key properties affecting snow albedo are not fully constrained with measurements, including ice effective grain size of the top sub-millimeter of the snowpack, mixing state of LACs with respect to ice grains, and site-specific LAC optical properties. The new default ice refractive indices produce extremely high pure snow albedo (>0.99) in the blue and ultraviolet part of the spectrum, with such values only measured in Antarctica so far. More work is needed particularly in the representation of snow algae, including experimental verification of how different pigment expressions and algal cell concentrations affect snow albedo. Representations and measurements of the influence of liquid water on spectral snow albedo are also needed.

A versatile method for computing optimized snow albedo from spectrally fixed radiative variables: VALHALLA v1.0

Abstract. In climate models, the snow albedo scheme generally calculates only a narrowband or broadband albedo, which leads to significant uncertainties. Here, we present the Versatile ALbedo calculation metHod based on spectrALLy fixed radiative vAriables (VALHALLA version 1.0) to optimize spectral snow albedo calculation. For this optimization, the energy absorbed by the snowpack is calculated by the spectral albedo model Two-streAm Radiative TransfEr in Snow (TARTES) and the spectral irradiance model Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). This calculation takes into account the spectral characteristics of the incident radiation and the optical properties of the snow based on an analytical approximation of the radiative transfer of snow. For this method, 30 wavelengths, called tie points (TPs), and 16 reference irradiance profiles are calculated to incorporate the absorbed energy and the reference irradiance. The absorbed energy is then interpolated for each wavelength between two TPs with adequate kernel functions derived from radiative transfer theory for snow and the atmosphere. We show that the accuracy of the absorbed energy calculation primarily depends on the adaptation of the irradiance of the reference profile to that of the simulation (absolute difference <1 W m−2 for broadband absorbed energy and absolute difference <0.005 for broadband albedo). In addition to the performance in terms of accuracy and calculation time, the method is adaptable to any atmospheric input (broadband, narrowband) and is easily adaptable for integration into a radiative scheme of a global or regional climate model.

Scripts and data used to generate all plots published in "SNICAR-AD v3: A Community Tool for Modeling Spectral Snow Albedo"

Scripts and data used to generate all plots published in "SNICAR-AD v3: A Community Tool for Modeling Spectral Snow Albedo"

Deposition of brown carbon onto snow: changes in snow optical and radiative properties

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.

Spectral Albedo Estimation of Snow Covers in Pakistan Using Landsat Data

Accurate snow spectral albedo measurements from satellite data can essentially help to determine the changes over the snow surface area. In the current study, spectral snow albedo is measured over the northern region of Pakistan using spatio-temporal imagery datasets taken by Landsat satellite series equipped with TM and ETM+ sensors. An Automatic Cloud Cover Assessment (ACCA) algorithm is used to mask cloudy pixels from further processing. Furthermore, an image independent model, Second Simulation of the Satellite Signal in the Solar Spectrum (6S) is used in the current research work to atmospherically correct the satellite data. The snow cover albedo of northern Pakistan is estimated using pixel values prior to correction, ACCA output values, and 6S model output values. The results of the study show that highest albedo values are estimated using Landsat band 4 data with albedo model. The results of the study also show that the albedo values measured (band 4) in the year 1992 (0.989) are reduced in the year 2000 (0.931). It is expected that the results of the study could be utilized to predict climatic variations for spring runoff estimation.

A Novel Parameterization of Snow Albedo Based on a Two-Layer Snow Model with a Mixture of Grain Habits

AbstractSnow 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.

Observations and model simulations of snow albedo reduction in seasonal snow due to insoluble light-absorbing particles during 2014 Chinese survey

Abstract. A snow survey was carried out to collect 13 surface snow samples (10 for fresh snow, and 3 for aged snow) and 79 subsurface snow samples in seasonal snow at 13 sites across northeastern China in January 2014. A spectrophotometer combined with chemical analysis was used to quantify snow particulate absorption by insoluble light-absorbing particles (ILAPs, e.g., black carbon, BC; mineral dust, MD; and organic carbon, OC) in snow. Snow albedo was measured using a field spectroradiometer. A new radiative transfer model (Spectral Albedo Model for Dirty Snow, or SAMDS) was then developed to simulate the spectral albedo of snow based on the asymptotic radiative transfer theory. A comparison between SAMDS and an existing model – the Snow, Ice, and Aerosol Radiation (SNICAR) – indicates good agreements in the model-simulated spectral albedos of pure snow. However, the SNICAR model values tended to be slightly lower than those of SAMDS when BC and MD were considered. Given the measured BC, MD, and OC mixing ratios of 100–5000, 2000–6000, and 1000–30 000 ng g−1, respectively, in surface snow across northeastern China, the SAMDS model produced a snow albedo in the range of 0.95–0.75 for fresh snow at 550 nm, with a snow grain optical effective radius (Reff) of 100 µm. The snow albedo reduction due to spherical snow grains assumed to be aged snow is larger than fresh snow such as fractal snow grains and hexagonal plate or column snow grains associated with the increased BC in snow. For typical BC mixing ratios of 100 ng g−1 in remote areas and 3000 ng g−1 in heavy industrial areas across northern China, the snow albedo for internal mixing of BC and snow is lower by 0.005 and 0.036 than that of external mixing for hexagonal plate or column snow grains with Reff of 100 µm. These results also show that the simulated snow albedos by both SAMDS and SNICAR agree well with the observed values at low ILAP mixing ratios but tend to be higher than surface observations at high ILAP mixing ratios.

East Antarctic sea ice in spring: spectral albedo of snow, nilas, frost flowers and slush, and light-absorbing impurities in snow

AbstractSpectral albedos of open water, nilas, nilas with frost flowers, slush, and first-year ice with both thin and thick snow cover were measured in the East Antarctic sea-ice zone during the Sea Ice Physics and Ecosystems eXperiment II (SIPEX II) from September to November 2012, near 65°S, 120°E. Albedo was measured across the ultraviolet (UV), visible and near-infrared (nIR) wavelengths, augmenting a dataset from prior Antarctic expeditions with spectral coverage extended to longer wavelengths, and with measurement of slush and frost flowers, which had not been encountered on the prior expeditions. At visible and UV wavelengths, the albedo depends on the thickness of snow or ice; in the nIR the albedo is determined by the specific surface area. The growth of frost flowers causes the nilas albedo to increase by 0.2–0.3 in the UV and visible wavelengths. The spectral albedos are integrated over wavelength to obtain broadband albedos for wavelength bands commonly used in climate models. The albedo spectrum for deep snow on first-year sea ice shows no evidence of light-absorbing particulate impurities (LAI), such as black carbon (BC) or organics, which is consistent with the extremely small quantities of LAI found by filtering snow meltwater. Estimated BC mixing ratios were in the range 0.1–0.5 ng of carbon per gram of snow.

A review of snow and ice albedo and the development of a new physically based broadband albedo parameterization

We present a computationally simple, theoretically based parameterization for the broadband albedo of snow and ice that can accurately reproduce the theoretical broadband albedo under a wide range of snow, ice, and atmospheric conditions. Depending on its application, this parameterization requires between one and five input parameters. These parameters are specific surface area of snow/ice, concentration of light‐absorbing carbon, solar zenith angle, cloud optical thickness, and snow depth. The parameterization is derived by fitting equations to albedo estimates generated with a 16‐stream plane‐parallel, discrete ordinates radiative transfer model of snow and ice that is coupled to a similar model of the atmosphere. Output from this model is also used to establish the physical determinants of the spectral albedo of snow and ice and evaluate the characteristics of spectral irradiance over snow‐covered surfaces. Broadband albedo estimates determined from the radiative transfer model are compared with results from a selection of previously proposed parameterizations. Compared to these parameterizations, the newly proposed parameterization produces accurate results for a much wider range of snow, ice, and atmospheric conditions.

The semi-analytical snow retrieval algorithm and its application to MODIS data

Grain size is a key parameter of a snowpack, affecting its thermodynamic state and influencing the spectral snow albedo. Differently from visible wavelengths, where the sensitivity to grain size is very low, in the near-infrared band there is a strong sensitivity of the reflectance to the grain size. This sensitivity provides the basis for the retrieval of grain size. In this paper we introduce a new snow retrieval algorithm that makes use of near-infrared measurements in which snow is modeled as a semi-infinite, weakly absorbing medium. It is assumed that the dense packing effects can be neglected and the radiative transport in snow can be studied using the standard radiative transfer equation extensively used, e.g., in cloud optics. The shape of grains is accounted for in the framework of fractal snow grain model. The performance of the algorithm is evaluated using ground-based measurements of snow albedo and results from a different retrieval algorithm. The technique is applied to study the changes of snow properties before and just after snow fall as seen by two MODIS sensors on TERRA and AQUA satellites. These satellites fly approximately 3 h and half apart (10:30 a.m. and 1:30 p.m. equator crossing time). The values of grain size retrieved from MODIS are also compared with values of grain size collected on ground. However, the area observed by MODIS including the locations of ground measurements was completely covered by clouds on the date of the measurements and the comparison could be performed only for the two previous days. A sensitivity analysis of the retrieval error due to atmospheric correction is also performed. Results show that the error on grain size retrieval induced by atmospheric correction ranges between ± 5% and ± 40%, depending on the grain size.

Measurements of spectral snow albedo at Neumayer, Antarctica

Abstract. Spectral albedo in high resolution, from 290 to 1050 nm, has been measured at Neumayer, Antarctica, (70°39' S, 8°15' W) during the austral summer 2003/2004. At 500 nm, the spectral albedo nearly reaches unity, with slightly lower values below and above 500 nm. Above 600 nm, the spectral albedo decreases to values between 0.45 and 0.75 at 1000 nm. For one cloudless case an albedo up to 1.01 at 500 nm could be determined. This can be explained by the larger directional component of the snow reflectivity for direct incidence, combined with a slightly mislevelled sensor and the snow surface not being perfectly horizontal. A possible explanation for an observed decline in albedo is an increase in snow grain size. The theoretically predicted increase in albedo with increasing solar zenith angle (SZA) could not be observed. This is explained by the small range of SZA during albedo measurements, combined with the effect of changing snow conditions outweighing the effect of changing SZA. The measured spectral albedo serves as input for radiative transfer models, describing radiation conditions in Antarctica.

Parameterization of Albedo on Snow/Ice Surface. A Review.

This paper reviews the historical development of the parameterization of albedo of snow/ice surfaces, including its theoretical basis and its applications. The theoretical description of spectral snow albedo considers both single scattering by each snow grain and the multiple-scattering approach in the snow layers. The theoretical algorithms have been greatly improved by the development of the bidirectional reflectance distribution function (BRDF) for solar radiation and approaches that parameterize the irregular shape of snow grains.The theoretical work provides a tool that is helpful in elucidating the factors determining snow spectral albedo. These factors can be classified into two groups: physical features of snow and external factors. The first group includes factors related to single and multiple scattering by snow particles. The second group includes the atmospheric condition and solar zenith angle. The very important factors that dominate snow albedo are grain size, impurities, snow depth, and solar zenith.A method of calculating snow/ice albedo had been developed mainly to monitor heat budgets and snow cover. Many empirical and semi-empirical equations for calculating albedo use dependent variables more frequently than independent variables, since the former are more easily quantified in the field.

A Model for the Spectral Albedo of Snow. I: Pure Snow

Abstract We present a method for calculating the spectral albedo of snow which can be used at any wavelength in the solar spectrum and which accounts for diffusely or directly incident radiation at any zenith angle. For deep snow, the model contains only one adjustable parameter, an effective grain size, which is close to observed grain sizes. A second parameter, the liquid-equivalent depth, is required only for relatively thin snow. In order for the model to make realistic predictions, it must account for the extreme anisotropy of scattering by snow particles. This is done by using the “delta-Eddington” approximation for multiple scattering, together with Mie theory for single scattering. The spectral albedo from 0.3 to 5 μm wavelength is examined as a function of the effective grain size, the solar zenith angle, the snowpack thickness, and the ratio of diffuse to direct solar incidence. The decrease in albedo due to snow aging can be mimicked by reasonable increases in grain size (50–100 μm for new snow...

A Model for the Spectral Albedo of Snow. II: Snow Containing Atmospheric Aerosols

Abstract Small highly absorbing particles, present in concentrations of only 1 part per million by weight (ppmw) or less, can lower snow albedo in the visible by 5–15% from the high values (96–99%) predicted for pure snow in Part I. These particles have, however, no effect on snow albedo beyond 0.9 μm wavelength where ice itself becomes a strong absorber. Thus we have an attractive explanation for the discrepancy between theory and observation described in Part I, a discrepancy which seemingly cannot be resolved on the basis of near-field scattering and nonsphericity effects. Desert dust and carbon soot are the most likely contaminants. But careful measurements of spectral snow albedo in the Arctic and Antarctic paint to a “grey” absorber, one whose imaginary refractive index is nearly constant across the visible spectrum. Thus carbon soot, rather than the red iron oxide normally present in desert dust, is strongly indicated at these sites. Soot particles of radius 0.1 μm, in concentrations of only 0.3 pp...