Artículos relacionados a Wavelet Approximation in Data Assimilation

Wavelet Approximation in Data Assimilation - Tapa blanda

Tangborn, Andrew

 
9781289289737: Wavelet Approximation in Data Assimilation
Tapa blanda
ISBN 10: 1289289735 ISBN 13: 9781289289737
Editorial: BiblioGov, 2013

Sinopsis


Estimation of the state of the atmosphere with the Kalman filter remains a distant goal because of high computational cost of evolving the error covariance for both linear and nonlinear systems. Wavelet approximation is presented here as a possible solution that efficiently compresses both global and local covariance information. We demonstrate the compression characteristics on the the error correlation field from a global two-dimensional chemical constituent assimilation, and implement an adaptive wavelet approximation scheme on the assimilation of the one-dimensional Burger's equation. In the former problem, we show that 99%, of the error correlation can be represented by just 3% of the wavelet coefficients, with good representation of localized features. In the Burger's equation assimilation, the discrete linearized equations (tangent linear model) and analysis covariance are projected onto a wavelet basis and truncated to just 6%, of the coefficients. A nearly optimal forecast is achieved and we show that errors due to truncation of the dynamics are no greater than the errors due to covariance truncation.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor


Estimation of the state of the atmosphere with the Kalman filter remains a distant goal because of high computational cost of evolving the error covariance for both linear and nonlinear systems. Wavelet approximation is presented here as a possible solution that efficiently compresses both global and local covariance information. We demonstrate the compression characteristics on the the error correlation field from a global two-dimensional chemical constituent assimilation, and implement an adaptive wavelet approximation scheme on the assimilation of the one-dimensional Burger's equation. In the former problem, we show that 99%, of the error correlation can be represented by just 3% of the wavelet coefficients, with good representation of localized features. In the Burger's equation assimilation, the discrete linearized equations (tangent linear model) and analysis covariance are projected onto a wavelet basis and truncated to just 6%, of the coefficients. A nearly optimal forecast is achieved and we show that errors due to truncation of the dynamics are no greater than the errors due to covariance truncation.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
BiblioGov
Año de publicación
2013
Idioma
Inglés
ISBN 10 
1289289735
ISBN 13 
9781289289737
Encuadernación
Tapa blanda
Número de páginas
38
Contacto del fabricante
no disponible
Persona responsable
no disponible