Open AccessThe new method of modeling horizontal error functions in variational assimilation with orthogonal wavelet
Author(s) -
Xiaoqun Cao,
Shucai Huang,
Haibo Du
Publication year - 2008
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.57.1984
Subject(s) - covariance , wavelet , data assimilation , orthogonal wavelet , anisotropy , computer science , grid , mathematics , covariance function , algorithm , wavelet transform , mathematical analysis , geometry , discrete wavelet transform , physics , statistics , artificial intelligence , meteorology , optics
Background error covariance is an important part of variational data assimilation systemwhich is used to spread the observation information to other grid points and vertical levels of the model. In order to model the inhomogeneity and anisotropy in horizontal error functions of raw background error covariancea new method is proposed to model horizontal error functions based on orthogonal wavelet transforms. The results of experiments show that the new method successfully modeled the heterogeneity and anisotropy included in the local correlation functions and depicted the structure and feature of raw covariance correctly.