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- W1992685094 abstract "All variational data assimilation schemes use some form of mass–wind coupling in their definitions of the control variables used in the minimization of the cost function. At the European Centre for Medium-Range Weather Forecasts, the statistical coupling developed by Parrish and Derber (1992) is used. This is simple and robust. The robustness is obtained by calculating the mass–wind correlations from a dataset representing short-range forecast errors. A potential disadvantage of this method is that, if the calibration dataset is not well balanced, there will be little mass–wind coupling in the analysis procedure. An alternative procedure is to assume that the balanced part of the errors, represented in this case by potential-vorticity errors, is uncorrelated with the unbalanced part of the error. This would be natural for a linear model. A simple potential-vorticity based method is developed and tested. It is shown that the strong scale dependence of the gravity-wave speed introduces significant numerical difficulties. However, with care, good results can be obtained. Copyright © 2003 Royal Meteorological Society" @default.
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- W1992685094 date "2003-07-01" @default.
- W1992685094 modified "2023-10-09" @default.
- W1992685094 title "Four-dimensional variational data assimilation: A new formulation of the background-error covariance matrix based on a potential-vorticity representation" @default.
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- W1992685094 doi "https://doi.org/10.1256/qj.02.10" @default.
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