3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model

The development of reliable models of near surface snow-atmosphere interactions from small to large scale is motivated by the need for a better understanding of the fluid- and morpho-dynamic processes in Polar environments. These interactions drive observed spatial patterns of snow distribution, ice...

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Main Authors: Comola, Francesco, Giometto, Marco Giovanni, Trujillo Gomez, Ernesto, Leonard, Katherine Colby, Maksym, Ted, Lehning, Michael
Format: Text
Language:unknown
Published: 2015
Subjects:
Online Access:http://infoscience.epfl.ch/record/209285
id ftinfoscience:oai:infoscience.tind.io:209285
record_format openpolar
spelling ftinfoscience:oai:infoscience.tind.io:209285 2023-05-15T13:48:06+02:00 3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model Comola, Francesco Giometto, Marco Giovanni Trujillo Gomez, Ernesto Leonard, Katherine Colby Maksym, Ted Lehning, Michael 2015-07-01T13:30:12Z http://infoscience.epfl.ch/record/209285 unknown http://infoscience.epfl.ch/record/209285 http://infoscience.epfl.ch/record/209285 Text 2015 ftinfoscience 2023-02-13T22:27:35Z The development of reliable models of near surface snow-atmosphere interactions from small to large scale is motivated by the need for a better understanding of the fluid- and morpho-dynamic processes in Polar environments. These interactions drive observed spatial patterns of snow distribution, ice deformation, travel and distribution of sea ice, among many others. However, challenges arise when representing the detailed sequence of processes involved, such as aerodynamic entrainment, particle dynamics, feedback on fluid momentum and particle impact on the surface. Here, we test a Lagrangian Stochastic Model of snow particle transport coupled to a Large Eddy Simulation to represent particle dynamics in turbulent flows and momentum extraction caused by suspended particles. An Immersed Boundary Method is adopted to effectively reproduce surface erosion and deposition, both of which influence surface drag and turbulence statistics. The model is implemented to represent snow redistribution over an Antarctic sea ice floe over which pre- and post- storm snow distribution patterns were successfully quantified using a terrestrial laser scanner. The dataset collected in October 2012 as part of the SIPEX-2 indicates marked changes in the snow distribution as a result of particle transport processes, providing valuable testing grounds for the model. The modeled snow surface pattern and the spatially variable shear stress evolve and reciprocally interact, generating areas of preferential deposition and erosion consistent with the observations. Model results and future improvements are discussed. Text Antarc* Antarctic Sea ice EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne) Antarctic
institution Open Polar
collection EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne)
op_collection_id ftinfoscience
language unknown
description The development of reliable models of near surface snow-atmosphere interactions from small to large scale is motivated by the need for a better understanding of the fluid- and morpho-dynamic processes in Polar environments. These interactions drive observed spatial patterns of snow distribution, ice deformation, travel and distribution of sea ice, among many others. However, challenges arise when representing the detailed sequence of processes involved, such as aerodynamic entrainment, particle dynamics, feedback on fluid momentum and particle impact on the surface. Here, we test a Lagrangian Stochastic Model of snow particle transport coupled to a Large Eddy Simulation to represent particle dynamics in turbulent flows and momentum extraction caused by suspended particles. An Immersed Boundary Method is adopted to effectively reproduce surface erosion and deposition, both of which influence surface drag and turbulence statistics. The model is implemented to represent snow redistribution over an Antarctic sea ice floe over which pre- and post- storm snow distribution patterns were successfully quantified using a terrestrial laser scanner. The dataset collected in October 2012 as part of the SIPEX-2 indicates marked changes in the snow distribution as a result of particle transport processes, providing valuable testing grounds for the model. The modeled snow surface pattern and the spatially variable shear stress evolve and reciprocally interact, generating areas of preferential deposition and erosion consistent with the observations. Model results and future improvements are discussed.
format Text
author Comola, Francesco
Giometto, Marco Giovanni
Trujillo Gomez, Ernesto
Leonard, Katherine Colby
Maksym, Ted
Lehning, Michael
spellingShingle Comola, Francesco
Giometto, Marco Giovanni
Trujillo Gomez, Ernesto
Leonard, Katherine Colby
Maksym, Ted
Lehning, Michael
3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model
author_facet Comola, Francesco
Giometto, Marco Giovanni
Trujillo Gomez, Ernesto
Leonard, Katherine Colby
Maksym, Ted
Lehning, Michael
author_sort Comola, Francesco
title 3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model
title_short 3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model
title_full 3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model
title_fullStr 3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model
title_full_unstemmed 3-D simulations of snow transport, erosion and deposition using a Large Eddy Simulation coupled with a Lagrangian Stochastic Model
title_sort 3-d simulations of snow transport, erosion and deposition using a large eddy simulation coupled with a lagrangian stochastic model
publishDate 2015
url http://infoscience.epfl.ch/record/209285
geographic Antarctic
geographic_facet Antarctic
genre Antarc*
Antarctic
Sea ice
genre_facet Antarc*
Antarctic
Sea ice
op_source http://infoscience.epfl.ch/record/209285
op_relation http://infoscience.epfl.ch/record/209285
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