A stochastic dynamical model of Arctic sea ice

The noise forcing underlying the variability in the Arctic ice cover has a wide range of principally unknown origins. For this reason, the analytical and numerical solutions of a stochastic Arctic sea ice model are analyzed with both additive and multiplicative noise over a wide range of external he...

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Published in:Journal of Climate
Main Authors: Moon, Woosok, Wettlaufer, J. S.
Format: Article in Journal/Newspaper
Language:English
Published: American Meteorological Society 2017
Subjects:
Online Access:http://nora.nerc.ac.uk/id/eprint/517296/
https://nora.nerc.ac.uk/id/eprint/517296/1/jcli-d-16-0223.1.pdf
https://doi.org/10.1175/JCLI-D-16-0223.1
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spelling ftnerc:oai:nora.nerc.ac.uk:517296 2023-05-15T13:11:07+02:00 A stochastic dynamical model of Arctic sea ice Moon, Woosok Wettlaufer, J. S. 2017-07 text http://nora.nerc.ac.uk/id/eprint/517296/ https://nora.nerc.ac.uk/id/eprint/517296/1/jcli-d-16-0223.1.pdf https://doi.org/10.1175/JCLI-D-16-0223.1 en eng American Meteorological Society https://nora.nerc.ac.uk/id/eprint/517296/1/jcli-d-16-0223.1.pdf Moon, Woosok; Wettlaufer, J. S. 2017 A stochastic dynamical model of Arctic sea ice. Journal of Climate, 30 (13). 5119-5140. https://doi.org/10.1175/JCLI-D-16-0223.1 <https://doi.org/10.1175/JCLI-D-16-0223.1> Publication - Article PeerReviewed 2017 ftnerc https://doi.org/10.1175/JCLI-D-16-0223.1 2023-02-04T19:45:02Z The noise forcing underlying the variability in the Arctic ice cover has a wide range of principally unknown origins. For this reason, the analytical and numerical solutions of a stochastic Arctic sea ice model are analyzed with both additive and multiplicative noise over a wide range of external heat fluxes ΔF0, corresponding to greenhouse gas forcing. The stochastic variability fundamentally influences the nature of the deterministic steady-state solutions corresponding to perennial and seasonal ice and ice-free states. Thus, the results are particularly relevant for the interpretation of the state of the system as the ice cover thins with ΔF0, allowing a thorough examination of the differing effects of additive versus multiplicative noise. In the perennial ice regime, the principal stochastic moments are calculated and compared to those determined from a stochastic perturbation theory described previously. As ΔF0 increases, the competing contributions to the variability of the destabilizing sea ice–albedo feedback and the stabilizing longwave radiative loss are examined in detail. At the end of summer the variability of the stochastic paths shows a clear maximum, which is due to the combination of the increasing influence of the albedo feedback and an associated “memory effect,” in which fluctuations accumulate from early spring to late summer. This is counterbalanced by the stabilization of the ice cover resulting from the longwave loss of energy from the ice surface, which is enhanced during winter, thereby focusing the stochastic paths and decreasing the variability. Finally, common examples in stochastic dynamics with multiplicative noise are discussed wherein the choice of the stochastic calculus (Itô or Stratonovich) is not necessarily determinable a priori from observations alone, which is why both calculi are treated on equal footing herein. Article in Journal/Newspaper albedo Arctic Arctic Sea ice Natural Environment Research Council: NERC Open Research Archive Arctic Journal of Climate 30 13 5119 5140
institution Open Polar
collection Natural Environment Research Council: NERC Open Research Archive
op_collection_id ftnerc
language English
description The noise forcing underlying the variability in the Arctic ice cover has a wide range of principally unknown origins. For this reason, the analytical and numerical solutions of a stochastic Arctic sea ice model are analyzed with both additive and multiplicative noise over a wide range of external heat fluxes ΔF0, corresponding to greenhouse gas forcing. The stochastic variability fundamentally influences the nature of the deterministic steady-state solutions corresponding to perennial and seasonal ice and ice-free states. Thus, the results are particularly relevant for the interpretation of the state of the system as the ice cover thins with ΔF0, allowing a thorough examination of the differing effects of additive versus multiplicative noise. In the perennial ice regime, the principal stochastic moments are calculated and compared to those determined from a stochastic perturbation theory described previously. As ΔF0 increases, the competing contributions to the variability of the destabilizing sea ice–albedo feedback and the stabilizing longwave radiative loss are examined in detail. At the end of summer the variability of the stochastic paths shows a clear maximum, which is due to the combination of the increasing influence of the albedo feedback and an associated “memory effect,” in which fluctuations accumulate from early spring to late summer. This is counterbalanced by the stabilization of the ice cover resulting from the longwave loss of energy from the ice surface, which is enhanced during winter, thereby focusing the stochastic paths and decreasing the variability. Finally, common examples in stochastic dynamics with multiplicative noise are discussed wherein the choice of the stochastic calculus (Itô or Stratonovich) is not necessarily determinable a priori from observations alone, which is why both calculi are treated on equal footing herein.
format Article in Journal/Newspaper
author Moon, Woosok
Wettlaufer, J. S.
spellingShingle Moon, Woosok
Wettlaufer, J. S.
A stochastic dynamical model of Arctic sea ice
author_facet Moon, Woosok
Wettlaufer, J. S.
author_sort Moon, Woosok
title A stochastic dynamical model of Arctic sea ice
title_short A stochastic dynamical model of Arctic sea ice
title_full A stochastic dynamical model of Arctic sea ice
title_fullStr A stochastic dynamical model of Arctic sea ice
title_full_unstemmed A stochastic dynamical model of Arctic sea ice
title_sort stochastic dynamical model of arctic sea ice
publisher American Meteorological Society
publishDate 2017
url http://nora.nerc.ac.uk/id/eprint/517296/
https://nora.nerc.ac.uk/id/eprint/517296/1/jcli-d-16-0223.1.pdf
https://doi.org/10.1175/JCLI-D-16-0223.1
geographic Arctic
geographic_facet Arctic
genre albedo
Arctic
Arctic
Sea ice
genre_facet albedo
Arctic
Arctic
Sea ice
op_relation https://nora.nerc.ac.uk/id/eprint/517296/1/jcli-d-16-0223.1.pdf
Moon, Woosok; Wettlaufer, J. S. 2017 A stochastic dynamical model of Arctic sea ice. Journal of Climate, 30 (13). 5119-5140. https://doi.org/10.1175/JCLI-D-16-0223.1 <https://doi.org/10.1175/JCLI-D-16-0223.1>
op_doi https://doi.org/10.1175/JCLI-D-16-0223.1
container_title Journal of Climate
container_volume 30
container_issue 13
container_start_page 5119
op_container_end_page 5140
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