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Improved Bathymetric Prediction using Geological Information: SYNBATH
  • +6
  • David T. Sandwell,
  • John A Goff,
  • Julie Gevorgian,
  • Hugh Harper,
  • Seung-Sep Kim,
  • Yao Yu,
  • Brook Tozer,
  • Paul Wessel,
  • Walter H.F. Smith
David T. Sandwell
UCSD, UCSD

Corresponding Author:[email protected]

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John A Goff
University of Texas at Austin, University of Texas at Austin
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Julie Gevorgian
UCSD, UCSD
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Hugh Harper
UC San Diego, UC San Diego
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Seung-Sep Kim
Chungnam National University, Chungnam National University
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Yao Yu
UCSD, UCSD
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Brook Tozer
UCSD, UCSD
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Paul Wessel
SOEST, University of Hawaii at Manoa, SOEST, University of Hawaii at Manoa
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Walter H.F. Smith
National Oceanic and Atmospheric Administration (NOAA), National Oceanic and Atmospheric Administration (NOAA)
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Abstract

To date, approximately 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.
Feb 2022Published in Earth and Space Science volume 9 issue 2. 10.1029/2021EA002069