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Deep Green’s Function Tsunami Inversion

delete2025-01-01
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PRE
AI
A
Amr Morssy
P
Paul D. Teal
W
W. Bastiaan Kleijn
DOI:10.1109/LGRS.2025.3614237delete
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Abstract

Abstract

En 中文
An important source of uncertainty in tsunami forecasting arises from uncertainty in the event’s initial conditions. In this work, we propose a dictionary-based inversion method that uses offshore sensor data to recover the initial ocean condition, allowing inversion of any tsunami event, and leading to reduced uncertainty in forecasts. We show that deep learning models can be used to address the computational requirements that arise from dictionary-based inversion. We validate our method using simulations of historic events.
Keywords:
Deep learning
Green’s function
tsunami

Journal

I
IEEE Geoscience and Remote Sensing Letters
IF:
4.4
Papers:
570
Citations:
0

Organization

V
Victoria University of Wellington
Scholars:
503
Papers: 288
Citations: 6.2K