J12.7
Spectral and morphing ensemble Kalman filters

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Tuesday, 25 January 2011: 5:00 PM
Spectral and morphing ensemble Kalman filters
2B (Washington State Convention Center)
Jan Mandel, University of Colorado, Denver, CO; and J. D. Beezley and L. Cobb
Manuscript (2.9 MB)

We present several EnKF-like methods for data assimilation. The new methods are based on the Fast Fourier Transform (FFT), and so they can assimilate observation into realistic NWP fields at a low computation cost. The covariance is localized automatically and no tapering is needed. FFT EnKF uses spectral estimation to achieve data assimilation with a very small ensemble. FFT EnKF OSI is optimal statistical interpolation with covariance fitted to a model in the frequency space. The FFT-based methods are combined with the morphing method, which can achieve position corrections, needed in the presence of coherent features, such as wildfires and fronts.

The performance of the methods will be demonstrated on applications, including WRF-Fire, a coupled atmosphere-wildland fire model.

Supplementary URL: http://ccm.ucdenver.edu/wiki/Osimorph