Fast spin up of Ocean biogeochemical models using matrix-free Newton–Krylov

Abstract

A novel computational approach is introduced for the efficient computation of equilibrium solutions of seasonally forced ocean biogeochemical models. The essential idea is to formulate the problem as a large system of nonlinear algebraic equations to be solved with a class of methods known as matrix-free Newton–Krylov (MFNK). MFNK is a combination of Newton-type methods for superlinearly convergent solution of nonlinear equations, and Krylov subspace methods for solving the Newton correction equations. The basic link between the two methods is the Jacobian-vector product, which may be probed approximately without forming and storing the elements of the true Jacobian. To render this approach practical for global models with O(10 6) degrees of freedom, a flexible preconditioning strategy is developed. The result is an essentially “black-box” numerical scheme than can be applied to most existing biogeochemical models. The method is illustrated by applying it to find the equilibrium solutions of two realistic biogeochemical problems. Compared with the conventional approach of direct time integration, the preconditioned-MFNK scheme is shown to be roughly two orders of magnitude more efficient. Several potential refinements of the basic algorithm that may yield further performance gains are discussed. The numerical scheme described here addresses a fundamental challenge to using ocean biogeochemical models more effectively.