Adaptive Tuning , 4 D - Var and Representers In
نویسنده
چکیده
Four dimensional variational data assimilation, called 4D-Var in the atmospheric sciences literature, is a method for combining forecast, dynamical systems equations, prior information about properties of the atmosphere, and heterogeneous observations, to get an estimate of the evolving state of the atmosphere. Summary: We (abstractly) generalize thètoy' weak 4D-Var model in Gong, Wahba, Johnson & Tribbia (1998) to include adaptive tuning of a variety of parameters throughout the 4D-Var varia-tional problem, and note issues of sensitivity and identiiability. We discuss`models' for model errors which include systematic, short memory and long memory errors. Finally we remark on the role of the theory of representers in reproducing kernel Hilbert spaces in the weak 4D-Var setting.
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