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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/11721

Title: 南海海洋動力過程實驗---衛星水色影像估算南海內波振幅
Estimation of Internal Wave Amplitudes in the South China Sea from Satellite Ocean Color Imagery
Authors: 何宗儒
Contributors: NTOU:Department of Marine Environmental Informatics
國立臺灣海洋大學:海洋環境資訊系
Date: 2008-08
Issue Date: 2011-06-28T08:44:00Z
Publisher: 行政院國家科學委員會
Abstract: 摘要:本計畫將利用海洋水色衛星影像觀測南海內波的動態,並利用內波發生時海水葉綠素濃度的變 化,估算內波的振幅。目前衛星遙測內波主要是利用合成口徑雷達(SAR)或中解析度影像分光輻射 儀(MODIS),從SAR 或MODIS 影像顯示南海區域內波發生頻繁,現場觀測結果亦顯示此海域內 波的振幅相當大,最大振幅可超過100 公尺。此巨大振幅足以舉升或沈降海水中的最大葉綠素濃度 層(Deep Chlorophyll Maximum),造成衛星觀測有光層葉綠素濃度的變化,並顯示在水色衛星的葉 綠素濃度影像中,如此可從葉綠素濃度的變化量反推出內波的振幅。由於利用衛星遙測海水葉綠素 濃度的精確度,會影響估算的內波振幅的準確度,因此需要提高衛星遙測資料估算葉綠素濃度的精 確度。因此此三年計畫,第一年的重點為蒐集海洋水色影像,進行南海內波的時空分佈及特徵尺度 的統計,以供後續使用。並應用類神經網路模式計算葉綠素濃度影像,取代目前使用的生光模式演 算法,以獲得較精確的衛星遙測葉綠素濃度。第二年為開發海洋葉綠素影像估算有光層內波振幅模 式。第三年則應用衛星高度計資料推導斜溫層深度,再應用理論模式將有光層深度的內波振幅推導 至斜溫層深度的內波原使振幅。本研究所估算的南海內波振幅,結果並將與其他現場量測子計畫的 結果相互驗證。
abstract:The aim of this proposal is to estimate the amplitude of internal waves in the northern South China Sea (SCS) by using satellite ocean color imagery. Previous studies using satellite images such as synthetic aperture radar (SAR) or Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the northern SCS is the area that internal waves frequently occur. In-situ measurements also show that the amplitudes of internal waves can be more than 100 m. This large amplitude can modulate the deep chlorophyll maximum (DCM) layer which is generally shallower than the thermocline layer. This modulation may cause the chlorophyll variation in the satellite ocean imagery. Therefore, from the variation of chlorophyll in the satellite ocean imagery, the amplitudes of internal waves in the optical layer can be estimated. However, to have accurate estimation of the amplitudes of internal waves, the accurate chlorophyll estimation in the ocean color imagery is necessary. In this three-year proposal, the first year, we will focus on collection of ocean color imagery to do statistical analysis of spatial and temporal distribution as well as the characteristics of internal waves in the SCS. The accurate estimation of chlorophyll concentration in the ocean color images will also applied by a bipartite artificial neural network model. The second-year work will focus on the development of the model of chlorophyll variation to the amplitudes of internal waves. The third year, we will apply the satellite altimeter data to estimate the depth of thermocline and develop a physical model to derive the amplitudes of internal waves in the depth of thermoclie from the optical layer. All results from this study will compare with the in-situ measurements which are from other sub-proposals.
Relation: NSC95-2611-M019-008-MY3
URI: http://ntour.ntou.edu.tw/ir/handle/987654321/11721
Appears in Collections:[海洋環境資訊系] 研究計畫

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