Author(s)

R. Zapert, J.A. Filar & P.S. Gaertner

Abstract

This paper investigates the use of a stochastic dynamical system approach to assessing uncertainty of integrated global climate change models. It uses the formulation of controlled stochastic dynamical systems applied to integrated global change models: dX(t) = [F(X(t))+U(t)]dt + BdW(t), X(to) = C, (0) where X(t) is a state of the system, U(t) is anthropogenic forcing, BW(t) is white noise random excitation, and C a random initial state. The uncertainty is estimated from the distribution of process X(t). The application of this approach is illustrated with the implementation of an uncertainty analysis module of the IMAGE 1.0 (Integrated Model to Assess the Greenhouse

Keywords