Alex Kalmikov (Massachusetts Institute of Technology)
A Hessian-based method for Uncertainty Quantification in Global Ocean State Estimation
A Hessian-based method is developed for Uncertainty Quantification (UQ) in global ocean state estimation. Large error covariance matrices are evaluated by inverting the Hessian of a model-observation misfit functional. First and second derivative codes of the MIT general circulation model are generated by algorithmic differentiation and used to propagate the uncertainties between observation, control and target variable domains. The UQ framework is applied to quantify Drake Passage transport uncertainties in a global idealized barotropic configuration of the MITgcm.