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Numerical simulation for cutoff draft of sea ice ridge keels based on a novel optimal modeling with nonlinear-statistical constraints

Authors :
Bing Tan
Peng Lu
Bin Cheng
Ting Wang
Chunchun Gao
Zhijun Li
Source :
Electronic Research Archive, Vol 30, Iss 5, Pp 1708-1722 (2022)
Publication Year :
2022
Publisher :
AIMS Press, 2022.

Abstract

Optimal identification and numerical models are powerful tools that have been widely used in geoscience research for many years. In this study, we proposed a novel optimal method to simulate a key parameter (cutoff draft) of the ridge keels due to dynamic deformation of sea ice at bottom. The sea ice ridges were measured in the Northwestern Weddell Sea of Antarctic, by a helicopter-borne electromagnetic-induction (EM) system. An optimal model with nonlinear-statistical constraints was developed, by taking deviations between the theoretical and measured keel draft (spacing) distributions as the performance criterion, and cutoff draft as the identified parameter. The properties of the optimal model and the existence of the optimal parameter were demonstrated. We identified that the optimal cutoff draft was 3.78 m via an optimal numerical algorithm, this value was then employed to separate the ridge keels from the ice bottom. Finally, the relationship between the mean keel draft and frequency (number of keels per km) was analyzed, and the result showed that this relationship was modeled well by a logarithmic function with a correlation coefficient of 0.7. The present optimal modeling method will provide a new theoretical reference for separating accurately the ridge keels from undeformed sea ice bottom, and analyzing the relationship between the morphologies of sea ice surface and bottom and the inversions of sea ice bottom draft and ice thickness by the surface height.

Details

Language :
English
ISSN :
26881594
Volume :
30
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Electronic Research Archive
Publication Type :
Academic Journal
Accession number :
edsdoj.f58b37b85fc747cb83e5e20a4ff7c8ef
Document Type :
article
Full Text :
https://doi.org/10.3934/era.2022086?viewType=HTML