Generating Derivative Code by Automatic Differentiation for Assimilation and Error Estimation

Tuesday, April 30, 2002 - 3:00pm - 3:45pm
Keller 3-180
Ralf Giering (FastOpt)
Joint work with T. Kaminski, Wolfgang Knorr, Marko Scholze, and Peter Rayner.

We give a brief introduction to automatic differentiation (AD), i.e. the generation of derivative code from the code of a numerical model. We introduce the AD Tool Transformation of Algorithms in Fortran (TAF) and list a number of succesful applications to large codes in oceanography, meteorology, and biogeochemistry. We highlight two examples, in which second derivative code is used: A model of the general oceanic circulation (MIT model) and two models of the terrestrial biosphere (SDBM/BETHY). We discuss the information from Hessian times Vector products for the MIT model. We present a carbon cycle data assimilation/prediction system that has been built around SDBM/BETHY and is used to: (1) infer model parameters and the covariance of their uncertainties and (2) compute diagnostics and their uncertainties in the calibrated model.