An efficient time integration scheme for climate prediction models

Abstract

Developing climate prediction model integration schemes which can provide realistic scenarioson long time scales with limited computing resources is the challenge of this research. Onemethod to succeed in this task is to increase the integration timestep. We have tested severaltechniques which may prove useful. The most successful was applied to the shallow waterequations over a spherical surface in which the prediction model was represented in its normalmodes, the high-frequency modes were balanced while the low-frequency modes were predicted.Experiments which we will describe extend this procedure to a state-of-the-art model (the NCAR/CCM3). We have taken the predicted data from each timestep of the model integration, projected it onto Hough modes, separated the modes into fast and slow components, integratedthe slow components with a timestep 3 times longer than that used in the standard model runand balanced the fast modes. The modal data was then reconverted to model format andreturned for the next iteration. Seasonal model output using this procedure was compared tothe standard model run output and the results of 10 realizations showed that both calculationsgave identical results within model variability.