Variational Data Assimilation with a Semi-Lagrangian Semi-implicit Global Shallow-Water Equation Model and Its Adjoint
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- handle: 10670/1.9u0s31
- Li, Y.; Navon, I. M.; Courtier, P. et Gauthier, P. (1993). « Variational Data Assimilation with a Semi-Lagrangian Semi-implicit Global Shallow-Water Equation Model and Its Adjoint ». Monthly Weather Review, 121(6), pp. 1759-1769.
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http://dx.doi.org/10.1175/1520-0493(1993)1212.0.CO [...]
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doi:10.1175/1520-0493(1993)1212.0.CO;2
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Adjoint model global model semi-Lagrangian model shallow water equation variational data assimilationCiter ce document
Y. Li et al., « Variational Data Assimilation with a Semi-Lagrangian Semi-implicit Global Shallow-Water Equation Model and Its Adjoint », UQAM Archipel : articles scientifiques, ID : 10670/1.9u0s31
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Résumé
An adjoint model is developed for variational data assimilation using the 2D semi-Lagrangian semi-implicit (SLSI) shallow-water equation global model of Bates et al. with special attention being paid to the linearization of the interpolation routines. It is demonstrated that with larger time steps the limit of the validity of the tangent linear model will be curtailed due to the interpolations, especially in regions where sharp gradients in the interpolated variables coupled with strong advective wind occur, a synoptic situation common in the high latitudes. This effect is particularly evident near the pole in the Northern Hemisphere during the winter season. Variational data assimilation experiments of “identical twin” type with observations available only at the end of the assimilation period perform well with this adjoint model. It is confirmed that the computational efficiency of the semi-Lagrangian scheme is preserved during the minimization process, related to the variational data assimilation procedure.