The Effect of Time Averaging on the Noise Level of Climatological Statistics Generated by Atmospheric General Circulation Models

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Abstract
We have tested the response of certain versions of atmospheric general circulation models (GCM's) to random perturbations in initial conditions while leaving external and boundary conditions unaltered. By means of time averaging and global space averaging, we have investigated the reduction of the level of noise inherent in the models. In this way, comparisons of the magnitude of the models' response to random perturbations with their response to advertent changes can be used to determine the significance of prescribed (non-random) perturbation experiments. This paper is intended to present preliminary results from two GCM's (NCAR and Rand) and may be useful for those contemplating using GCM's for climate or perturbation experiments. Abstract We have tested the response of certain versions of atmospheric general circulation models (GCM's) to random perturbations in initial conditions while leaving external and boundary conditions unaltered. By means of time averaging and global space averaging, we have investigated the reduction of the level of noise inherent in the models. In this way, comparisons of the magnitude of the models' response to random perturbations with their response to advertent changes can be used to determine the significance of prescribed (non-random) perturbation experiments. This paper is intended to present preliminary results from two GCM's (NCAR and Rand) and may be useful for those contemplating using GCM's for climate or perturbation experiments.

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