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Climate models contain numerous parameters with uncertain values. In the context of climate prediction, it is relevant to obtain an e stimate of the range of outcomes given the parameter uncertainty. Taking an ensemble of simulations with randomly perturbed parameters would require an extremely large sample, because most random perturbations do not have much impact. In this study we select parameter perturbations that potentially change the climate effectively. We consider a dry, spectral quasi-geostrophic, three-level model on the sphere (T21QGL3). Two approaches are considered. First, using the theory of empirical orthogonal functions (EOFs), parameter perturbations are explored that directly act in the direction of a preferred flow regime. Next the changing sensitivity to perturbations along the chaotic attractor of a circulation model is analyzed. Frequently short intervals of high sensitivity are passed. Using the adjoint method we select the first singular vector denoting the direction of the parameter perturbation having the largest effect in such an interval. For the first 1000 intervals with the highest sensitivity, this vector is taken for the

Effect of parameter change upon the extra-tropical atmospheric variability