TY - JOUR

T1 - Amundsen sea bathymetry

T2 - The benefits of using gravity data for bathymetric prediction

AU - McMillan, Malcolm

AU - Shepherd, Andrew

AU - Vaughan, David G.

AU - Laxon, Seymour

AU - McAdoo, David

PY - 2009/12/1

Y1 - 2009/12/1

N2 - Bathymetric charts are essential for modeling oceanic processes, yet, in remote areas, direct measurements of seafloor depth are often scarce. It is possible to augment sparse depth soundings with dense satellite-derived gravity data to provide additional bathymetric detail in regions devoid of sounding data. We demonstrate this method by using marine gravity derived from the European Remote Sensing (ERS-1) satellite altimeter, combined with depth soundings, to form a bathymetric prediction of the Amundsen Sea, West Antarctica. We estimate the root mean square error of depth estimates at unsurveyed locations in our solution to be ∼ 120 m. We use a Monte Carlo method to assess the value of gravity as a bathymetric predictor in sparsely surveyed regions by comparing our solution to predictions formed from depth soundings alone. When less than ∼11% of 10-km grid cells contain depth soundings, inclusion of gravity data improves the depth accuracy of the solution by up to 17%, as compared to a minimum curvature surface interpolation of the depth soundings alone. When depth data are sparse, our gravity-derived prediction reveals additional short-wavelength bathymetric features, such as troughs on the continental shelf, which are not resolved by interpolations of the depth soundings alone.

AB - Bathymetric charts are essential for modeling oceanic processes, yet, in remote areas, direct measurements of seafloor depth are often scarce. It is possible to augment sparse depth soundings with dense satellite-derived gravity data to provide additional bathymetric detail in regions devoid of sounding data. We demonstrate this method by using marine gravity derived from the European Remote Sensing (ERS-1) satellite altimeter, combined with depth soundings, to form a bathymetric prediction of the Amundsen Sea, West Antarctica. We estimate the root mean square error of depth estimates at unsurveyed locations in our solution to be ∼ 120 m. We use a Monte Carlo method to assess the value of gravity as a bathymetric predictor in sparsely surveyed regions by comparing our solution to predictions formed from depth soundings alone. When less than ∼11% of 10-km grid cells contain depth soundings, inclusion of gravity data improves the depth accuracy of the solution by up to 17%, as compared to a minimum curvature surface interpolation of the depth soundings alone. When depth data are sparse, our gravity-derived prediction reveals additional short-wavelength bathymetric features, such as troughs on the continental shelf, which are not resolved by interpolations of the depth soundings alone.

KW - Altimetry

KW - Arctic regions

KW - Gravity measurement

KW - Satellites

KW - Sea floor

KW - Terrain mapping

U2 - 10.1109/TGRS.2009.2023665

DO - 10.1109/TGRS.2009.2023665

M3 - Journal article

AN - SCOPUS:70549100090

VL - 47

SP - 4223

EP - 4228

JO - IEEE Transactions on Geoscience and Remote Sensing

JF - IEEE Transactions on Geoscience and Remote Sensing

SN - 0196-2892

IS - 12

M1 - 5196715

ER -