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Optimal control theory of partial differential equations [1], [2] has emerged as a new way to attack problem of 4-D atmospheric/oceanic data assimilation problems. These variational techniques attempt to achieve a best fit between data (observations) and forecast model subject to some ‘a priori’ criteria. This review paper presents new trends for utilizing model adjoint equations for variational data assimilation, parameter fitting and sensitivity analysis in general, as applicable to many areas of meteorological, oceanographic and environmental research.

Variational Data Assimilation, Optimal Parameter Estimation and Sensitivity Analysis for Environmental Problems