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标题：Improved Bathymetric Prediction Using Geological Information: SYNBATH
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作者：David T. Sandwell ; John A. Goff ; Julie Gevorgian 等
期刊名称：Earth and Space Science
电子版ISSN：2333-5084
出版年度：2022
卷号：9
期号：2
页码：n/a-n/a
DOI：10.1029/2021EA002069
语种：English
出版社：John Wiley & Sons, Ltd.
摘要：Abstract To date, ∼20% of the ocean floor has been surveyed by ships at a spatial resolution of 400 m or better. The remaining 80% has depth predicted from satellite altimeter‐derived gravity measurements at a relatively low resolution. There are many remote ocean areas in the southern hemisphere that will not be completely mapped at 400 m resolution during this decade. This study is focused on the development of synthetic bathymetry to fill the gaps. There are two types of seafloor features that are not typically well resolved by satellite gravity; abyssal hills and small seamounts (<2.5 km tall). We generate synthetic realizations of abyssal hills by combining the measured statistical properties of mapped abyssal hills with regional geology including fossil spreading rate/orientation, rms height from satellite gravity, and sediment thickness. With recent improvements in accuracy and resolution, it is now possible to detect all seamounts taller than about 800 m in satellite‐derived gravity and their location can be determined to an accuracy of better than 1 km. However, the width of the gravity anomaly is much greater than the actual width of the seamount so the seamount predicted from gravity will underestimate the true seamount height and overestimate its base dimension. In this study, we use the amplitude of the vertical gravity gradient (VGG) to estimate the mass of the seamount and then use their characteristic shape, based on well‐surveyed seamounts, to replace the smooth‐predicted seamount with a seamount having a more realistic shape.