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Identification for the Thermodynamic Parameters of Sea Ice and Study on the Characteristics of Pressure Ridge Sails
Author: TanBing
Tutor: LiZhiJun; FengEnMin
School: Dalian University of Technology
Course: Operational Research and Cybernetics
Keywords: Distributed Parameter System Parameter Identification Sea Ice Ridge sailmorphology Drag coefficient
CLC: P731.15
Type: PhD thesis
Year: 2012
Downloads: 21
Quote: 0
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Abstract
As the most important characteristics of the underlying surface in Polar Regions, sea ice has a significantly effect on the global atmosphere, ocean circulations, and climate change. Meanwhile, as one of the important characteristics of the sea ice surface, pressure ridges are the main factor for the estimations of the momentum and thermal transfer between the atmosphere and sea ice, as well as between the ocean and sea ice, ice mass and thickness. On the background of the thermodynamic process of sea ice, and characteristics of morphology and dynamics of pressure ridges, based on the measured sea ice temperature during the Second China Arctic Research Expedition and elevations of sea ice surface in the Weddell Sea measured during the Winter Weddell Outflow Study2006by the Germany Alfred Wegener Institute for Polar and Marine Research, the optimization methods, numerical computation for partial differential equations, and probability theory and mathematical statistics are used to identify the thermodynamic parameters and analyze the parameters of morphology and dynamics of pressure ridges. The main content and contributions are as follows.1. For the thermodynamic process of the sea ice in the Arctic, a parabolic distributed parameter system is established to describe the thermodynamic process of sea ice. L2theory for partial equations is used to prove the existence and uniqueness of the weak solution of the system and the continuous dependence of this solution on the identified parameters. A nonoverlapped domain decomposition method is applied to decompose the timedependent domain to three subdomains of snow, ice and sea water, and the continuous condition is introduced at all interfaces to make each subdomain smooth. Some important properties of the system and its weak solution are analyzed by optimization theory and methods. An optimal model with state constraints is presented with the thicknesses of snow and sea ice as identified parameters, and the deviation between the calculated and the measured sea ice temperature as the performance criterion. The existence of the optimal parameter is proved and the optimal conditions are derived. Numerical simulation is carried out based on the temperature of snow, ice and water measured during the Second China Arctic Research Expedition, and the results not only reflect the variability of sea ice temperature in time and space domains, but also agree well with the observed temperatures.2. Ice surface elevation profiles measured during Winter Weddell Outflow Study are used to investigate the morphology and distribution of pressure ridges in the northwestern Weddell Sea. To search effective methods for the determination of the cutoff height and the clustering of pressure ridges, an statistical optimal model with nonlinear constraint is presented with the cutoff height as identified parameter, and the deviation between the theoretical and the measured ridge height/spacing distributions as the performance criterion. The obtained optimal cutoff height is then used to separate pressure ridges from other sea ice surface undulations. Next, for the defects of the traditional k means clustering algorithm, an improved k means clustering algorithm is presented to cluster the measured profiles with the ridging intensity (the ratio of mean ridge height to mean spacing), and which are clustered into three regimes. These three ice regimes coincided closely with distinct sea ice regions identified in a satellite radar image. The statistical characteristics of each regime are analyzed and the influences of the ridging intensity on the ridge height and spacing distributions are also discussed. The correlations between the morphology parameters are also discussed.3. Wind drag is parted into two components according to the drag partition theory:form drag on pressure ridges and the skin drag over rough sea ice surface. The parameterization of form drag on pressure ridges and its contribution to the total drag and airice drag coefficient at a reference height of10m under a neutral stability condition are improved by the morphology parameters and distributions of pressure ridges, and the variations of them with increasing ridging intensity and roughness length are discussed. The results revealed that, for the compacted ice field, form drag on ridges and its contribution to total drag both increase with ridging intensity, while decrease with increasing roughness length. There is an increasing trend of the airice drag coefficient Cdn(10) with increasing ridging intensity. Meanwhile, Cdn(10) increases for the smaller ridging intensities, whereas decreases for the larger ridging intensity, with increasing roughness length, which is mainly attributed to the change of dominance of form drag on pressure ridges and skin drag over rough ice surface:the form drag on pressure ridges becomes dominant only when ridging intensity is extremely large, while the skin drag over rough ice surface is the dominant component for the profiles with the relative lower ridging intensity. This work will push the study of the sea ice thermodynamic and dynamic models.

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CLC: > Astronomy,Earth Sciences > Oceanography > Marine basic science > Marine hydrology > Marine hydrological factors > Sea ice
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