UQ Summer School – Adrian Sandu

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.