| Marchuk, G.I., 1975: Formulation of theory of perturbations for complicated models. Appl. Math. Optimization, 2, 1--33. |
.... oceanography, as well as of operational numerical prediction for atmospheric and oceanic flows (Panel, 1991) Its major sources of theoretical and practical ideas include by now the engineering (Bucy and Joseph, 1987; Gelb, 1974; Jazwinski, 1970) mathematical (Gill et al. 1982; Lions, 1971; Marchuk, 1975) and geophysical (Bennett, 1992; Daley, 1991; Ghil and Malanotte Rizzoli, 1991) literatures. The Second WMO International Symposium on Assimilation of Observations in Meteorology and Oceanography, held in Tokyo in March 1995, has shown substantial progress in the practical implementation of ....
....theorem (e.g. Lo eve, 1978) The objective function J [x(t 0 ) in Section 4.1 becomes a functional J [u(r; t 0 ) and its J. Met. Soc. Japan, 1997) K. Ide, P. Courtier, M. Ghil and A.C. Lorenc 18 minimization involves the adjoint PDE for a given linearization of M(u;x; t) Lions, 1971; Marchuk, 1975). The combined complexities of nonlinearity and stochastic perturbations are challenging but the motivation for addressing them in the PDE setting is strongly enhanced by the promises of increased resolution in both models and observations. ....
Marchuk, G.I., 1975: Formulation of theory of perturbations for complicated models. Appl. Math. Optimization, 2, 1--33.
....and the estimation theoretical methodology. The latter relies on the state vector approach of Kalman (1960) to sequential estimation and was formally introduced into geophysical flow problems by Ghil et al. 1981) The former relies on the work of the French (Lions, 1971) and Russian (Marchuk, 1975) mathematical schools; the full power of this approach was introduced into meteorological problems by Lewis and Derber (1985) and Le Dimet and Talagrand (1986) The two types of methods, sequential and variational, are essentially equivalent for simple linear systems (Gelb, 1974; Ghil and ....
Marchuk, G. I., 1975: Formulation of theory of perturbations for complicated models. Appl. Math. Optimization, 2, 1--33.
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