Climate model simulations of the 21st Century show global warming, sea ice melting, snow cover decreasing, and intensification of the hydrological cycle when forced with scenarios of increasing greenhouse gases and tropospheric aerosols. Here we apply a new statistical technique recently proposed by Vinnikov and Robock (GRL, No.2, 2002) to analyze how the variability of climate will change with global warming. Simulations from the Geophysical Fluid Dynamics Laboratory (using the R30 climate model) predict that the variability of the global mean surface air temperature will decrease. We will using our new statistical tools to investigate whether or not the data contains significant changes in variability. The same technique already found no significant trends of variability for many climatic indices during the 20th Century record. Results for all these studies and analyses, along with the utility of our statistical technique will be presented at the conference. We will demonstrate how this approach can have profound implications for understanding the impacts of future climate change.