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Seafloor Magnetization image data, Reykjanes Ridge, Langseth cruise MGL1309 (2013, investigators Fernando Martinez and Richard Hey)

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DataONE2019-03-04 更新2024-06-08 收录
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This three-dimensonal seafloor magnetization data was derived from the magnetic anomaly data. To carry out the inversion for seafloor magnetization the MGL1309 magnetic anomaly grid was extended within a rectangular area using regional gridded values from Macnab et al. (1995) and ship data from Searle et al. (1998) regridded in ~1 km cells. The multibeam bathymetry grid was extended within the same rectangular area using satellite-predicted bathymetry (Sandwell et al., 2014) to fill areas outside the multibeam coverage and regridded in ~1 km cells. The grids were mirrored to minimize edge effects and a three-dimensional Fourier inversion for seafloor magnetization (Parker, 1972) was carried out using Mirone Software (Luis, 2007) assuming a 500 m source layer with magnetization direction given by the axial geocentric dipole. Five terms in the Fourier series were used in the inversion. The resulting values were masked to the extent of the MGL1309 multibeam grid. As the polarity transitions agreed well with two-dimensional reversal modeling of profile values no annihilator was added. The data file is in PDF format. It is cited in Martinez and Hey, 2017, and was generated as part of the project called Test Between Thermal and Tectonic Hypotheses for North Atlantic Seafloor Spreading Geometry Reorganization. Funding was provided by NSF award OCE11-54071.

本三维海底磁化强度数据源自磁异常数据。为开展海底磁化强度反演,研究人员借助Macnab等人(1995)的区域网格化数据,以及经重网格化至约1 km格网单元的Searle等人(1998)船舶实测数据,将MGL1309磁异常网格扩展至矩形研究区域内。针对同一矩形区域的多波束测深网格,研究人员采用卫星预测水深数据(Sandwell等人,2014)进行扩展,以填补多波束覆盖范围之外的空白区域,并将该网格重网格化至约1 km格网单元。为最小化边缘效应,对上述两类网格实施镜像处理;随后基于Parker(1972)提出的三维傅里叶反演方法,借助Mirone软件(Luis,2007)开展海底磁化强度反演,假设源层厚度为500 m,磁化方向由轴向地心偶极子确定。本次反演共使用傅里叶级数的5项展开项。最终得到的磁化强度数值被掩码至MGL1309多波束网格的覆盖范围。由于地磁极性转换结果与剖面数据的二维反转模型拟合度极佳,未添加消去因子。本数据集文件采用PDF格式,被Martinez与Hey(2017)引用,其生成服务于名为“北大西洋海底扩张几何重组的热学与构造学假说检验”的研究项目。本研究由美国国家科学基金会(National Science Foundation, NSF)资助项目OCE11-54071提供经费支持。
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2019-03-04
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