reconstruction of ocean currents from sparse and noisy data
DESCRIPTION
Reconstruction of Ocean Currents From Sparse and Noisy Data. Peter C Chu and Leonid Ivanov Naval Postgraduate School T.P. Korzhova, T.M. Margolina, O.V. Melnichenko Marine Hydrophysical Institute Sevastopol, Crimea, Ukraine [email protected]. - PowerPoint PPT PresentationTRANSCRIPT
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Reconstruction of Ocean Currents From Sparse and Noisy
Data
Peter C Chu and Leonid IvanovNaval Postgraduate School
T.P. Korzhova, T.M. Margolina, O.V. Melnichenko
Marine Hydrophysical InstituteSevastopol, Crimea, Ukraine
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Can we get the velocity signal from sparse and noisy data?
• Black Sea
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• How can we assimilate sparse and noisy velocity data into numerical model?
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Flow Decomposition
• 2 D Flow (Helmholtz)
• 3D Flow (Toroidal & Poloidal): Very popular in astrophysics
•
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3D Incompressible Flow
• If Incompressible
• We have
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Flow Decomposition
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Boundary Conditions
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Basis Functions
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Determination of Basis Functions
• Poisson Equations• Γ - Rigid Boundary• Γ’ – Open Boundary
• {λk}, {μm} are Eigenvalues.
• Basis Functions are predetermined.
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Flow Reconstruction
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Reconstructed Circulation
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Conclusions
• Reconstruction is a useful tool for processing real-time velocity data with short duration and limited-area sampling.
• The scheme can handle highly noisy data.• The scheme is model independent.• The scheme can be used for assimilating
sparse velocity data