Modeling the evolution of the structural anisotropy of snow

The structural anisotropy of snow characterizes the spatially anisotropic distribution of the ice and air microstructure and is a key parameter for improving parameterizations of physical properties. To enable the use of the anisotropy in snowpack models as an internal variable, we propose a simple...

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Published in:The Cryosphere
Main Authors: Leinss, Silvan, Löwe, Henning, Proksch, Martin, Kontu, Anna
Format: Text
Language:English
Published: 2020
Subjects:
Online Access:https://doi.org/10.5194/tc-14-51-2020
https://tc.copernicus.org/articles/14/51/2020/
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spelling ftcopernicus:oai:publications.copernicus.org:tc75445 2023-05-15T18:20:17+02:00 Modeling the evolution of the structural anisotropy of snow Leinss, Silvan Löwe, Henning Proksch, Martin Kontu, Anna 2020-01-14 application/pdf https://doi.org/10.5194/tc-14-51-2020 https://tc.copernicus.org/articles/14/51/2020/ eng eng doi:10.5194/tc-14-51-2020 https://tc.copernicus.org/articles/14/51/2020/ eISSN: 1994-0424 Text 2020 ftcopernicus https://doi.org/10.5194/tc-14-51-2020 2020-07-20T16:22:29Z The structural anisotropy of snow characterizes the spatially anisotropic distribution of the ice and air microstructure and is a key parameter for improving parameterizations of physical properties. To enable the use of the anisotropy in snowpack models as an internal variable, we propose a simple model based on a rate equation for the temporal evolution. The model is validated with a comprehensive set of anisotropy profiles and time series from X-ray microtomography (CT) and radar measurements. The model includes two effects, namely temperature gradient metamorphism and settling, and can be forced by any snowpack model that predicts temperature and density. First, we use CT time series from lab experiments to validate the proposed effect of temperature gradient metamorphism. Next, we use SNOWPACK simulations to calibrate the model with radar time series from the NoSREx campaigns in Sodankylä, Finland. Finally we compare the simulated anisotropy profiles against field-measured full-depth CT profiles. Our results confirm that the creation of vertical structures is mainly controlled by the vertical water vapor flux through the snow volume. Our results further indicate a yet undocumented effect of snow settling on the creation of horizontal structures. Overall the model is able to reproduce the characteristic anisotropy variations in radar time series of four different winter seasons with a very limited set of calibration parameters. Text Sodankylä Copernicus Publications: E-Journals Sodankylä ENVELOPE(26.600,26.600,67.417,67.417) The Cryosphere 14 1 51 75
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description The structural anisotropy of snow characterizes the spatially anisotropic distribution of the ice and air microstructure and is a key parameter for improving parameterizations of physical properties. To enable the use of the anisotropy in snowpack models as an internal variable, we propose a simple model based on a rate equation for the temporal evolution. The model is validated with a comprehensive set of anisotropy profiles and time series from X-ray microtomography (CT) and radar measurements. The model includes two effects, namely temperature gradient metamorphism and settling, and can be forced by any snowpack model that predicts temperature and density. First, we use CT time series from lab experiments to validate the proposed effect of temperature gradient metamorphism. Next, we use SNOWPACK simulations to calibrate the model with radar time series from the NoSREx campaigns in Sodankylä, Finland. Finally we compare the simulated anisotropy profiles against field-measured full-depth CT profiles. Our results confirm that the creation of vertical structures is mainly controlled by the vertical water vapor flux through the snow volume. Our results further indicate a yet undocumented effect of snow settling on the creation of horizontal structures. Overall the model is able to reproduce the characteristic anisotropy variations in radar time series of four different winter seasons with a very limited set of calibration parameters.
format Text
author Leinss, Silvan
Löwe, Henning
Proksch, Martin
Kontu, Anna
spellingShingle Leinss, Silvan
Löwe, Henning
Proksch, Martin
Kontu, Anna
Modeling the evolution of the structural anisotropy of snow
author_facet Leinss, Silvan
Löwe, Henning
Proksch, Martin
Kontu, Anna
author_sort Leinss, Silvan
title Modeling the evolution of the structural anisotropy of snow
title_short Modeling the evolution of the structural anisotropy of snow
title_full Modeling the evolution of the structural anisotropy of snow
title_fullStr Modeling the evolution of the structural anisotropy of snow
title_full_unstemmed Modeling the evolution of the structural anisotropy of snow
title_sort modeling the evolution of the structural anisotropy of snow
publishDate 2020
url https://doi.org/10.5194/tc-14-51-2020
https://tc.copernicus.org/articles/14/51/2020/
long_lat ENVELOPE(26.600,26.600,67.417,67.417)
geographic Sodankylä
geographic_facet Sodankylä
genre Sodankylä
genre_facet Sodankylä
op_source eISSN: 1994-0424
op_relation doi:10.5194/tc-14-51-2020
https://tc.copernicus.org/articles/14/51/2020/
op_doi https://doi.org/10.5194/tc-14-51-2020
container_title The Cryosphere
container_volume 14
container_issue 1
container_start_page 51
op_container_end_page 75
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