Wavelet Approximation in Data Assimilation (Paperback) (ISBN-13: 9781289289737)

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.


Author: Nasa Technical Reports Server (Ntrs),Andrew Tangborn
ISBN-10: 1289289735
ISBN-13: 9781289289737
Publisher: Bibliogov
Language: English
Published: 08/07/2013
Pages: 38
Format: Paperback
Weight: 0.19lbs
Size: 9.69h x 7.44w x 0.08d