Interpolation of the European velocity field using least squares ...
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Interpolation of the European velocity field using least squares collocation
method
Legrand Juliette, Altamimi Zuheir, and Jamet OlivierLAREG/IGN, France
EUREF Symposium 2006
RIGA, LATVIA, 14 - 17 JUNE 2006
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Outline
• Stacking of EPN combined time series of station positions
• Euler Pole Estimation
• Interpolation: Least squares collocation method
• Conclusion
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European Velocity Field Estimation
• EPN weekly solution from 1996 to 2006 • Stacked with CATREF Software [Altamimi]
• before december 2004 : Remove original constraints and apply minimum constraints
• after december 2004 : Use as they are minimally constrained solutions
• Reject outliers and properly handle discontinuities• Combination ==> Global solution (Pos&Vel)
• Datum definition : MC over a reference set of 16 EPN stations (ITRF2005P)
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Euler pole estimation- 2.5 years of observation- located at rigid part of the tectonic plate- velocity formal error less than 3 mm/yr- residuals less than 1.5 mm/yr
Velocities
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- 2.5 years of observation- located at rigid part of the tectonic plate- velocity formal error less than 3 mm/yr- residuals less than 1.5 mm/yr
Euler pole estimationResidual velocities
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- 2.5 years of observation- velocity formal error less than 3 mm/yr- Estimated rigid body rotation removed from velocity
Interpolation: Residual velocity Field
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Least-squares collocation method
We have the horizontal velocities of p stations
We want to estimate the horizontal velocities at q points
The “measurement” is decomposed into – a signal – and a noise
At each point, the signal can be linearly expressed as a function of the angular velocity.
with
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The best (unbiased minimum variance) linear estimate of the signal vector ---- in terms of the “measurement” vector ---- is given by [Moritz, 1989] :
Least-squares collocation method
The covariance matrix of the interpolated velocity field is :
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Least-squares collocation method
The covariance matrices
Noise covariance matrixCovariance Model
No correlation between2 different components
Spherical symmetry
Covariance function
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Signal covariance for d =0
Correlation length
Least-squares collocation methodCovariance function determination
Isotropic covariance function with zero derivative at the origin [Kahle et al., 2000]
Spherical distance
is estimated as the weighted mean of the
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Interpolated EPN velocity field
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Interpolated EPN velocity field
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Interpolated EPN velocity field
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Interpolated EPN velocity field
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Conclusion
• A new method to interpolate a horizontal velocity field
• Contribution to the DEVF • Applied to the EPN horizontal velocity field
• First test model to predict velocities over Western Eurasia
• More refinement and validation still to be done• Confrontation with geophysical models still to be
done• Extension to vertical velocities