Abstract
An atmosphere-land coupled simple climate model is constructed and its climatic properties are analyzed by introducing a global analysis method, cell mapping. The simple model is a nonlinear six order simplified climate model featured with chaotic dynamics, dissipation, and forcing source, which are the main features of the real climate system. The cell mapping method is applied with this coupled system. Numerical experiments are carried out for investigating the interactions between the fast-changing atmospheric variables and slow-changing underlying surface variables. The predictability of the system is also investigated via the global analysis, with which the evolution of the system is translated to the evolution of probability transition on a Markov Chain. An effective scheme is proposed for computing the probability transition matrix for the coupled system. Predictions can be made based on the combination of dynamics and statistics. The importance of constructing the coupled model is shown by globally analyzing the predictability of the coupled system. The coupling mechanism prolongs the memorization of initial information, and then the predictability as well.
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