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

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,...

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Published in:The Cryosphere
Main Authors: T. Letcher, J. Parno, Z. Courville, L. Farnsworth, J. Olivier
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
Subjects:
geo
Online Access:https://doi.org/10.5194/tc-16-4343-2022
https://tc.copernicus.org/articles/16/4343/2022/tc-16-4343-2022.pdf
https://doaj.org/article/9aae1b31c379450b8a833ec6b1d4cb9b
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:9aae1b31c379450b8a833ec6b1d4cb9b 2023-05-15T18:32:19+02:00 A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics T. Letcher J. Parno Z. Courville L. Farnsworth J. Olivier 2022-10-01 https://doi.org/10.5194/tc-16-4343-2022 https://tc.copernicus.org/articles/16/4343/2022/tc-16-4343-2022.pdf https://doaj.org/article/9aae1b31c379450b8a833ec6b1d4cb9b en eng Copernicus Publications doi:10.5194/tc-16-4343-2022 1994-0416 1994-0424 https://tc.copernicus.org/articles/16/4343/2022/tc-16-4343-2022.pdf https://doaj.org/article/9aae1b31c379450b8a833ec6b1d4cb9b undefined The Cryosphere, Vol 16, Pp 4343-4361 (2022) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2022 fttriple https://doi.org/10.5194/tc-16-4343-2022 2023-01-22T19:35:12Z 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. Article in Journal/Newspaper The Cryosphere Unknown The Cryosphere 16 10 4343 4361
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic geo
envir
spellingShingle geo
envir
T. Letcher
J. Parno
Z. Courville
L. Farnsworth
J. Olivier
A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics
topic_facet geo
envir
description 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.
format Article in Journal/Newspaper
author T. Letcher
J. Parno
Z. Courville
L. Farnsworth
J. Olivier
author_facet T. Letcher
J. Parno
Z. Courville
L. Farnsworth
J. Olivier
author_sort T. Letcher
title A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics
title_short A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics
title_full A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics
title_fullStr A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics
title_full_unstemmed A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics
title_sort generalized photon-tracking approach to simulate spectral snow albedo and transmittance using x-ray microtomography and geometric optics
publisher Copernicus Publications
publishDate 2022
url https://doi.org/10.5194/tc-16-4343-2022
https://tc.copernicus.org/articles/16/4343/2022/tc-16-4343-2022.pdf
https://doaj.org/article/9aae1b31c379450b8a833ec6b1d4cb9b
genre The Cryosphere
genre_facet The Cryosphere
op_source The Cryosphere, Vol 16, Pp 4343-4361 (2022)
op_relation doi:10.5194/tc-16-4343-2022
1994-0416
1994-0424
https://tc.copernicus.org/articles/16/4343/2022/tc-16-4343-2022.pdf
https://doaj.org/article/9aae1b31c379450b8a833ec6b1d4cb9b
op_rights undefined
op_doi https://doi.org/10.5194/tc-16-4343-2022
container_title The Cryosphere
container_volume 16
container_issue 10
container_start_page 4343
op_container_end_page 4361
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