2001: Remapping the thickness distribution in sea ice models

Abstract. In sea ice models with multiple thickness categories the ice thickness distribution evolves in time. The evolution of the thickness distribution as ice grows and melts is analogous to one-dimensional fluid transport and can be treated by similar numerical methods. One such method, remappin...

Full description

Bibliographic Details
Main Author: William H. Lipscomb
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.5801
http://oceans11.lanl.gov/svn/CICE/tags/release-4.0/doc/PDF/Lipscomb_JGR2001.pdf
id ftciteseerx:oai:CiteSeerX.psu:10.1.1.471.5801
record_format openpolar
spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.471.5801 2023-05-15T15:08:49+02:00 2001: Remapping the thickness distribution in sea ice models William H. Lipscomb The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.5801 http://oceans11.lanl.gov/svn/CICE/tags/release-4.0/doc/PDF/Lipscomb_JGR2001.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.5801 http://oceans11.lanl.gov/svn/CICE/tags/release-4.0/doc/PDF/Lipscomb_JGR2001.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://oceans11.lanl.gov/svn/CICE/tags/release-4.0/doc/PDF/Lipscomb_JGR2001.pdf text ftciteseerx 2016-01-08T07:19:14Z Abstract. In sea ice models with multiple thickness categories the ice thickness distribution evolves in time. The evolution of the thickness distribution as ice grows and melts is analogous to one-dimensional fluid transport and can be treated by similar numerical methods. One such method, remapping, is applied here. Thickness categories are represented as Lagrangian grid cells whose boundaries are projected forward in time. The thickness distribution is approximated as a linear or quadratic polynomial in each displaced category, and ice area and volume are transferred between categories so as to restore the original boundaries. In simple test problems and in a single-column model with forcing typical of the central Arctic, remapping performs significantly better than methods previously used in sea ice models. It is less diffusive than a scheme that fixes the ice thickness in each category and behaves better numerically than a scheme that represents the thickness distribution as a set of delta functions. Also, remapping converges faster (i.e., with fewer thickness categories) than the alternative schemes. With five to seven categories the errors due to finite resolution of the thickness distribution are much smaller than the errors due to other sources. Linear remapping performs as well as the more complex quadratic version and is recommended for climate modeling. Its computational cost is minimal compared to other sea ice model components. 1. Text Arctic Sea ice Unknown Arctic
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
description Abstract. In sea ice models with multiple thickness categories the ice thickness distribution evolves in time. The evolution of the thickness distribution as ice grows and melts is analogous to one-dimensional fluid transport and can be treated by similar numerical methods. One such method, remapping, is applied here. Thickness categories are represented as Lagrangian grid cells whose boundaries are projected forward in time. The thickness distribution is approximated as a linear or quadratic polynomial in each displaced category, and ice area and volume are transferred between categories so as to restore the original boundaries. In simple test problems and in a single-column model with forcing typical of the central Arctic, remapping performs significantly better than methods previously used in sea ice models. It is less diffusive than a scheme that fixes the ice thickness in each category and behaves better numerically than a scheme that represents the thickness distribution as a set of delta functions. Also, remapping converges faster (i.e., with fewer thickness categories) than the alternative schemes. With five to seven categories the errors due to finite resolution of the thickness distribution are much smaller than the errors due to other sources. Linear remapping performs as well as the more complex quadratic version and is recommended for climate modeling. Its computational cost is minimal compared to other sea ice model components. 1.
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author William H. Lipscomb
spellingShingle William H. Lipscomb
2001: Remapping the thickness distribution in sea ice models
author_facet William H. Lipscomb
author_sort William H. Lipscomb
title 2001: Remapping the thickness distribution in sea ice models
title_short 2001: Remapping the thickness distribution in sea ice models
title_full 2001: Remapping the thickness distribution in sea ice models
title_fullStr 2001: Remapping the thickness distribution in sea ice models
title_full_unstemmed 2001: Remapping the thickness distribution in sea ice models
title_sort 2001: remapping the thickness distribution in sea ice models
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.5801
http://oceans11.lanl.gov/svn/CICE/tags/release-4.0/doc/PDF/Lipscomb_JGR2001.pdf
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_source http://oceans11.lanl.gov/svn/CICE/tags/release-4.0/doc/PDF/Lipscomb_JGR2001.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.5801
http://oceans11.lanl.gov/svn/CICE/tags/release-4.0/doc/PDF/Lipscomb_JGR2001.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
_version_ 1766340104082685952