Many recent paleoclimatic studies, both observational and modeling, have pointed to the influence of high latitudes on the tropical precipitation distribution. In this study, we use both idealized and comprehensive atmospheric GCMs to develop a better understanding of what controls this tropical response. The idealized moist GCM is that described by Frierson et al (2006), which has no cloud or water vapor feedbacks and includes a simplified Betts-Miller convection scheme. One of the convection scheme parameters can be varied to alter the ITCZ response. The results from the idealized model are compared with those from AM2, an atmospheric general circulation model developed at the Geophysical Fluid Dynamics Laboratory (GFDL). Heating is imposed poleward of 40°N with equal and opposite cooling added poleward of 40°S, equivalent to an imposed cross-equatorial heat flux in the ocean.
As an intermediate step in understanding the tropical response, we focus on the degree of compensation between the imposed oceanic flux and the resulting response in the atmospheric energy transport. The idealized model produces a low level of compensation of about 25%. An energy balance model is constructed to support the claim that this low level of compensation is expected if the primarily communication between the extratropics and the Hadley cell is through eddy fluxes of moist static energy. A simple theory is developed that predicts the precipitation response, given this degree of compensation and a measure of the gross moist stability of the model tropics. The gross moist stability can be modified by altering the convection scheme, providing a test of this theory.
In AM2, all cases show a much greater shift of the ITCZ than in the idealized model, related to the fact that in AM2 the compensation of the implied oceanic transport by the atmospheric energy transport is much larger (~65% rather than ~25%). We argue that this enhancement of the response is due to changes in cloud and water vapor feedbacks. The dependence of the ITCZ response on cloud feedbacks suggests an important way in which uncertainties in cloud modeling can create uncertainties in regional responses to climatic perturbations.