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A Wavelet Approach to Representing Background Error Covariances in a Limited-Area Model

机译:小波方法表示有限区域模型中的背景误差协方差

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The use of orthogonal wavelets for the representation of background error covariances over a limited area is studied. Each wavelet function contains both information on position and information on scale: using a diagonal correlation matrix in wavelet space thus gives the possibility of representing the local variations of correlation scale. To this end, a generalized family of orthogonal Meyer wavelets that are not restricted to dyadic domains (i.e., powers of 2) is introduced. A three-bases approach is used, which allows one to take advantage of the respective properties of the spectral, wavelet, and gridpoint spaces. While the implied local anisotropies are relatively small, the local changes in the two-dimensional length scale are rather well represented.
机译:研究了正交小波在有限区域内表示背景误差协方差的方法。每个小波函数都包含位置信息和尺度信息:在小波空间中使用对角相关矩阵可以表示相关尺度的局部变化。为此,引入了不限于二进域(即2的幂)的正交Meyer小波的广义族。使用了三基方法,该方法允许利用频谱,小波和网格点空间的各自属性。尽管隐含的局部各向异性相对较小,但二维长度尺度中的局部变化却可以很好地表示出来。

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