Supermodeling: Synchronization of Alternative Dynamical Models of a Single Objective Process

Abstract

Imperfect models of the same objective process give an improved representation of that process, from which they assimilate data, if they are also coupled to one another. Inter-model coupling, through nudging, or more strongly through averaging of dynamical tendencies, typically gives synchronization or partial synchronization of models and hence formation of consensus. Previous studies of supermodels of interest for weather and climate prediction are here reviewed. The scheme has been applied to a hierarchy of models, ranging from simple systems of ordinary differential equations, to models based on the quasigeostrophic approximation to geophysical fluid dynamics, to primitive-equation fluid dynamical models, and finally to state-of-the-art climate models. Evidence is reviewed to test the claim that, in nonlinear systems, the synchronized-model scheme surpasses the usual procedure of averaging model outputs.