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Titlebook: Data Assimilation; Making Sense of Obse William Lahoz,Boris Khattatov,Richard Menard Book 2010 Springer-Verlag Berlin Heidelberg 2010 Atmos

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樓主: Disperse
21#
發(fā)表于 2025-3-25 05:44:11 | 只看該作者
Ensemble Kalman Filter: Current Status and Potential 4D-Var (four-dimensional variational assimilation) can be adapted to the LETKF without requiring an adjoint model. Although the Ensemble Kalman filter is less mature than 4D-Var (Kalnay 2003), its simplicity and its competitive performance with respect to 4D-Var suggest that it may become the method of choice.
22#
發(fā)表于 2025-3-25 07:56:16 | 只看該作者
Error Statistics in Data Assimilation: Estimation and Modellingcterized by covariance matrices for the error in the background state and the observations. These covariance matrices determine the level of influence each observation has on the analysis and how this influence is distributed spatially, temporally and among the different types of analysis variables.
23#
發(fā)表于 2025-3-25 14:44:00 | 只看該作者
Initialization features than those of direct concern. For many purposes these higher frequency components can be regarded as . contaminating the motions of meteorological interest. The elimination of this noise is achieved by adjustment of the initial fields, a process called ..
24#
發(fā)表于 2025-3-25 16:13:57 | 只看該作者
Cleaner Combustion and Sustainable Worldn lead to significant differences between the predicted states and the actual states of the system. In this case, observations of the system over time can be incorporated into the model equations to derive “improved” estimates of the states and also to provide information about the “uncertainty” in the estimates.
25#
發(fā)表于 2025-3-25 20:10:44 | 只看該作者
26#
發(fā)表于 2025-3-26 03:48:17 | 只看該作者
27#
發(fā)表于 2025-3-26 06:39:26 | 只看該作者
28#
發(fā)表于 2025-3-26 08:59:31 | 只看該作者
29#
發(fā)表于 2025-3-26 13:58:30 | 只看該作者
Beyond Japan: Cleaning, American-Stylecterized by covariance matrices for the error in the background state and the observations. These covariance matrices determine the level of influence each observation has on the analysis and how this influence is distributed spatially, temporally and among the different types of analysis variables.
30#
發(fā)表于 2025-3-26 18:06:18 | 只看該作者
Blogging from the New Front Lines features than those of direct concern. For many purposes these higher frequency components can be regarded as . contaminating the motions of meteorological interest. The elimination of this noise is achieved by adjustment of the initial fields, a process called ..
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