Dr. Adrian Sandu: Variational Data Assimilation - Part 1,2,3 and 4

Topics include: - three dimensional variational (3D-var) data assimilation: formulation of the problem, construction of covariance matrices, observation operators, numerical optimization, and analysis of error impact; - four dimensional variational (4D-var) data assimilation: formulation of the problem; - adjoint sensitivity analysis for systems governed by ODEs and PDEs; - discrete versus continuous adjoint models: properties and implementation; automatic differentiation; - adjoint operators and uncertainty quantification; - computational issues and efficient implementation aspects; - applications and examples.