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Seafloor Topography Estimation From Gravity Gradients Using Simulated Annealing
Author(s) -
Yang Junjun,
Jekeli Christopher,
Liu Lintao
Publication year - 2018
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1029/2018jb015883
Subject(s) - seafloor spreading , geology , gravity anomaly , geodesy , simulated annealing , altimeter , nonlinear system , inverse , geophysics , geometry , mathematics , algorithm , physics , paleontology , quantum mechanics , oil field
Inferring seafloor topography from gravity anomaly currently is the dominant method to obtain a global view of the oceans. Standard techniques rely on an approximate, linear relationship between topography and gravity, which is valid only if the local topography is smooth compared with the regional topography, so the estimation accuracy in the very rugged areas is low. Current methods can be improved by removing the linear approximation and estimating the topography through simulated annealing and by using gravity gradiometry that is more sensitive to topography at short wavelengths than the gravity anomaly. Simulated annealing is a global optimization technique that can process nonlinear inverse problems. It is developed to estimate the seafloor depths by minimizing the difference between the observed and forward‐computed vertical gravity gradients. The method is tested on altimetry‐derived gravity gradients in a 2 ∘ ×2 ∘ area of rugged seafloor topography in the West Pacific Ocean and results in estimates with a root‐mean‐square error of ±236 m. Compared to estimates from an existing model obtained by standard techniques this represents an accuracy improvement of 22%.