Preliminary examination of a long model run of the NCAR CCM with idealized geography indicates that the surface temperature field can be interpreted as an system forced by noise in space- time. The linear system can be interpreted as an energy-balance climate model (EBM) with diffusive horizontal heat transport and linear radiation damping. The surface temperature field in both models has several interesting properties. For example, the spatial correlation statistics are essentially isotropic over distances of a few thousand km. The spatial correlations fall off with a characteristic length of about 1500 km which agrees with the EBM and with surface temperature data. Linear theory suggests that climatological (=time averaged) responses to point heat sources should exhibit a spatial pattern identical to the equal times spatial auto correlation function. This appears to be the case in the CCM surface data. These pieces of evidence help to explain why the EBM has been so successful in earlier studies of the seasonal cycle and even in various paleoclimate scenarios compared to data and GCMs. This research will study the underlying mechanisms of climate variability and change using simple models. The PI will systematically examine the fluxes and related meteorological fields in order to clarify the reasons for the apparant linearity of climate fluctuation and response phenomena. This research is important because it may give insight into how the climate system works - a pre-requisite for more credible predictions of future climates.
