Modeling Uncertainties of Bathymetry Predicted With Satellite Altimetry Data and Application to Tsunami Hazard Assessments
Modeling Uncertainties of Bathymetry Predicted With Satellite Altimetry Data and Application to Tsunami Hazard Assessments
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DOI：
10.1029/2020jb019735
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发表时间：
2020-09
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通讯作者：
Ignacio Sepúlveda;B. Tozer;J. Haase;P. Liu;M. Grigoriu
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作者：
Ignacio Sepúlveda;B. Tozer;J. Haase;P. Liu;M. Grigoriu
由卫星雷达测高得到的测深模型对于模拟许多海洋过程是必不可少的。它们受到需要量化的不确定性的影响。我们提出了一个不确定性模型，该模型假设误差是由高程数据中缺乏高波数含量引起的。然后将该模型应用于海啸危害评估。我们建立了智利北部的测深不确定性模型。利用多波束数据获得了测高预测测深误差的统计特性。我们发现Von Karman相关函数和拉普拉斯边际分布可以用来定义一个基于随机场的不确定性模型。我们还提出了一种生成符合船载测量条件的合成测深样品的方法。当测深数据分辨率小于~ 10 km时，该方法进一步扩展到考虑插值不确定性。我们通过量化测深引起的海啸危害估计的不确定性来说明该方法的实用性。我们证明了智利中/近场潮汐计和浮标的海啸引导波预测对水深不确定性不敏感。这一结果表明海啸预警方法可以在数值模拟中充分利用测高预报的测深数据。最后，通过对全球分布的15个区域的测深误差统计，评估了在没有多波束数据的区域建模不确定性的可行性。我们发现一般的Von Karman相关和拉普拉斯边际分布可以作为一阶近似。不确定性随机场模型的标准偏差是有区域差异的，并根据所提出的标度定律进行估计。
Models of bathymetry derived from satellite radar altimetry are essential for modeling many marine processes. They are affected by uncertainties which require quantification. We propose an uncertainty model that assumes errors are caused by the lack of high‐wavenumber content within the altimetry data. The model is then applied to a tsunami hazard assessment. We build a bathymetry uncertainty model for northern Chile. Statistical properties of the altimetry‐predicted bathymetry error are obtained using multibeam data. We find that a Von Karman correlation function and a Laplacian marginal distribution can be used to define an uncertainty model based on a random field. We also propose a method for generating synthetic bathymetry samples conditional to shipboard measurements. The method is further extended to account for interpolation uncertainties, when bathymetry data resolution is finer than ∼10 km. We illustrate the usefulness of the method by quantifying the bathymetry‐induced uncertainty of a tsunami hazard estimate. We demonstrate that tsunami leading wave predictions at middle/near field tide gauges and buoys are insensitive to bathymetry uncertainties in Chile. This result implies that tsunami early warning approaches can take full advantage of altimetry‐predicted bathymetry in numerical simulations. Finally, we evaluate the feasibility of modeling uncertainties in regions without multibeam data by assessing the bathymetry error statistics of 15 globally distributed regions. We find that a general Von Karman correlation and a Laplacian marginal distribution can serve as a first‐order approximation. The standard deviation of the uncertainty random field model varies regionally and is estimated from a proposed scaling law.