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Ocean Turbulent Dynamics at Superresolution From Optimal Multiresolution Analysis and Multiplicative Cascade

Joël Sudre 1, 2 Hussein Yahia 3 Oriol Pont 3 Véronique Garçon 1
1 LEGOS - Laboratoire d'études en Géophysique et océanographie spatiales
2 DYNBIO LEGOS
LEGOS - Laboratoire d'études en Géophysique et océanographie spatiales
3 GeoStat - Geometry and Statistics in acquisition data
Inria Bordeaux - Sud-Ouest
Abstract : The synoptic determination of ocean circulation using the data acquired from space, with a coherent depiction of its turbulent characteristics, remains a fundamental challenge in oceanography. This determination has the potential of revealing all aspects of the ocean dynamic variability on a wide range of spatiotemporal scales and will enhance our understanding of ocean–atmosphere exchanges at superresolution, as required in the present context of climate change. Here, we show a four-year time series of spatial superresolution (4 km) turbulent ocean dynamics generated from satellite data using emerging ideas in signal processing coming from nonlinear physics, low-resolution dynamics, and superresolution oceanic sea surface temperature data acquired from optical sensors. The method at its core consists in propagating across the scales the low-resolution dynamics in a multiresolution analysis computed on adimensional critical transition information.
Keywords : wavelet transforms oceans nonlinear dynamical systems image motion analysis motion measurement Altimetry chaos fluid dynamics fractals geophysical signal processing
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Journal articles
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https://hal.inria.fr/hal-01166170
Contributor : H. Yahia <>
Submitted on : Monday, June 22, 2015 - 11:56:34 AM
Last modification on : Saturday, January 9, 2021 - 3:31:16 AM

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CNRS | DYNBIO | SYSCO2 | INRIA | OMP | OMP-LEGOS | TDS-MACS | UNIV-TLSE3 | METEO | INSU

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Joël Sudre, Hussein Yahia, Oriol Pont, Véronique Garçon. Ocean Turbulent Dynamics at Superresolution From Optimal Multiresolution Analysis and Multiplicative Cascade. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2015, 53 (11), pp.12. ⟨10.1109/TGRS.2015.2436431⟩. ⟨hal-01166170⟩

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