On the Simulation of Climate and Climate Change with General Circulation Models

Abstract

Increasing concern over possible anthropogenic impact on climate has led to an awareness that straightforward diagnostic procedures are necessary to measure climate and climate change in computer model experiments. Since the best documented (and most predictable) climate change is the extreme seasonal change from January to July, an obvious first application of any such set of procedures would be to determine if an atmospheric general circulation model (GCM) is capable of producing measurably different climates from a prescribed seasonal change in external forcing. Toward this end, objective statistical tests are applied to various measures of the climate to determine the extent to which sampled climate ensembles produced by January and July versions of a 5° horizontal resolution GCM developed several years ago at the National Center for Atmospheric Research differ. It is shown that while ensemble averages and standard deviations of globally averaged, time-averaged precipitation are not significantly different, significant regional differences in both first- and second-moment statistics do result from the imposed seasonal changes in surface and radiative forcing. Of course, these same objective statistical tests can and should be applied to determine the extent to which observed and simulated climate ensembles agree or differ.