A Tailored Computation of the Mean Dynamic Topography for a Consistent Integration into Ocean Circulation Models
A Tailored Computation of the Mean Dynamic Topography for a Consistent Integration into Ocean Circulation Models
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DOI：
10.1007/s10712-013-9272-9
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发表时间：
2014-11
影响因子：
4.6
通讯作者：
S. Becker;M. Losch;J. Brockmann;G. Freiwald-;W. Schuh
中科院分区：
文献类型：
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作者：
S. Becker;M. Losch;J. Brockmann;G. Freiwald-;W. Schuh
地转地表速度可以由平均动态地形的梯度——平均海面和大地水准面之间的差——推导出来。因此，独立观测的平均动力地形数据是海洋环流模式有价值的输入参数和约束条件。为了成功地拟合观测动力地形数据，不仅需要特定海洋模式网格上的平均动力地形，还需要其逆协方差矩阵的信息。然而，利用卫星重力场模型和测高海面高度计算平均动力地形并不简单。为此，我们之前开发了一种综合方法，以一致的方式结合这两个不同的观察组，而不使用常见的过滤方法(Becker等人在J Geodyn 59(60):99 - 110,2012；Becker， in Konsistente组合von schwerfeld， Altimetrie and hydrographisen Daten zur Modellierung der dynamischen ozeopgraphy, 2012)。在这种组合方法中，考虑了观测的全光谱范围。此外，它允许在任意网格上直接确定平均动态地形的正态方程（即误差协方差矩阵的逆），这是海洋资料同化的要求之一。在本文中，我们报告了在高程数据集的选择和改进处理方面的进展。我们重点研究了Jason-1和Envisat的沿轨测高数据的预处理步骤，以获得平均海面剖面。在此过程中，完成了严格的方差传播，从而首次获得了平均海面的完整协方差矩阵。将平均剖面和GRACE/GOCE组合重力场模型相结合，得到北大西洋平均动力地形模型，该模型的特征是一组确定的假设。我们表明，在三维平稳逆海洋模型中包含具有完整误差结构的大地测量导出的平均动态地形，比以前的估计改善了模拟的海洋特征。
Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography—the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99–110, 2012; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie 2012). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.