Ising model for melt ponds on Arctic sea ice
Perhaps the most iconic feature of melting Arctic sea ice is the distinctive ponds that form on its surface. The geometrical patterns describing how melt water is distributed over the surface largely determine the solar reflectance and transmittance of the sea ice cover, which are key parameters in...
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Online Access: | https://doi.org/10.1088/1367-2630/ab26db https://doaj.org/article/a35e34e39d574a6bba491b209e33c2d7 |
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ftdoajarticles:oai:doaj.org/article:a35e34e39d574a6bba491b209e33c2d7 2023-09-05T13:16:45+02:00 Ising model for melt ponds on Arctic sea ice Yi-Ping Ma Ivan Sudakov Courtenay Strong Kenneth M Golden 2019-01-01T00:00:00Z https://doi.org/10.1088/1367-2630/ab26db https://doaj.org/article/a35e34e39d574a6bba491b209e33c2d7 EN eng IOP Publishing https://doi.org/10.1088/1367-2630/ab26db https://doaj.org/toc/1367-2630 doi:10.1088/1367-2630/ab26db 1367-2630 https://doaj.org/article/a35e34e39d574a6bba491b209e33c2d7 New Journal of Physics, Vol 21, Iss 6, p 063029 (2019) Arctic sea ice melt ponds Ising model metastable states fractal geometry Science Q Physics QC1-999 article 2019 ftdoajarticles https://doi.org/10.1088/1367-2630/ab26db 2023-08-13T00:38:44Z Perhaps the most iconic feature of melting Arctic sea ice is the distinctive ponds that form on its surface. The geometrical patterns describing how melt water is distributed over the surface largely determine the solar reflectance and transmittance of the sea ice cover, which are key parameters in climate modeling and upper ocean ecology. In order to help develop a predictive theoretical approach to studying melting sea ice, and the resulting patterns of light and dark regions on its surface in particular, we look to the statistical mechanics of phase transitions and introduce a two-dimensional random field Ising model which accounts for only the most basic physics in the system. The ponds are identified as metastable states in the model, where the binary spin variable corresponds to the presence of melt water or ice on the sea ice surface. With the lattice spacing determined by snow topography data as the only measured parameter input into the model, energy minimization drives the system toward realistic pond configurations from an initially random state. The model captures the essential mechanism of pattern formation of Arctic melt ponds, with predictions that agree very closely with observed scaling of pond sizes and transition in pond fractal dimension. Article in Journal/Newspaper Arctic Sea ice Directory of Open Access Journals: DOAJ Articles Arctic New Journal of Physics 21 6 063029 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic sea ice melt ponds Ising model metastable states fractal geometry Science Q Physics QC1-999 |
spellingShingle |
Arctic sea ice melt ponds Ising model metastable states fractal geometry Science Q Physics QC1-999 Yi-Ping Ma Ivan Sudakov Courtenay Strong Kenneth M Golden Ising model for melt ponds on Arctic sea ice |
topic_facet |
Arctic sea ice melt ponds Ising model metastable states fractal geometry Science Q Physics QC1-999 |
description |
Perhaps the most iconic feature of melting Arctic sea ice is the distinctive ponds that form on its surface. The geometrical patterns describing how melt water is distributed over the surface largely determine the solar reflectance and transmittance of the sea ice cover, which are key parameters in climate modeling and upper ocean ecology. In order to help develop a predictive theoretical approach to studying melting sea ice, and the resulting patterns of light and dark regions on its surface in particular, we look to the statistical mechanics of phase transitions and introduce a two-dimensional random field Ising model which accounts for only the most basic physics in the system. The ponds are identified as metastable states in the model, where the binary spin variable corresponds to the presence of melt water or ice on the sea ice surface. With the lattice spacing determined by snow topography data as the only measured parameter input into the model, energy minimization drives the system toward realistic pond configurations from an initially random state. The model captures the essential mechanism of pattern formation of Arctic melt ponds, with predictions that agree very closely with observed scaling of pond sizes and transition in pond fractal dimension. |
format |
Article in Journal/Newspaper |
author |
Yi-Ping Ma Ivan Sudakov Courtenay Strong Kenneth M Golden |
author_facet |
Yi-Ping Ma Ivan Sudakov Courtenay Strong Kenneth M Golden |
author_sort |
Yi-Ping Ma |
title |
Ising model for melt ponds on Arctic sea ice |
title_short |
Ising model for melt ponds on Arctic sea ice |
title_full |
Ising model for melt ponds on Arctic sea ice |
title_fullStr |
Ising model for melt ponds on Arctic sea ice |
title_full_unstemmed |
Ising model for melt ponds on Arctic sea ice |
title_sort |
ising model for melt ponds on arctic sea ice |
publisher |
IOP Publishing |
publishDate |
2019 |
url |
https://doi.org/10.1088/1367-2630/ab26db https://doaj.org/article/a35e34e39d574a6bba491b209e33c2d7 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
New Journal of Physics, Vol 21, Iss 6, p 063029 (2019) |
op_relation |
https://doi.org/10.1088/1367-2630/ab26db https://doaj.org/toc/1367-2630 doi:10.1088/1367-2630/ab26db 1367-2630 https://doaj.org/article/a35e34e39d574a6bba491b209e33c2d7 |
op_doi |
https://doi.org/10.1088/1367-2630/ab26db |
container_title |
New Journal of Physics |
container_volume |
21 |
container_issue |
6 |
container_start_page |
063029 |
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1776198222835875840 |