To date, neither observational studies nor direct climate model simulations have been able to document trends in the frequency or severity of deep moist convection associated with global climate change. The lack of such evidence is not unexpected as the observational record is insufficiently long and computational limitations prevent modeling at the scales necessary to simulate explicitly such phenomena. Nonetheless, severe deep moist convection represents an important aspect of regional climate, particularly in the central United States, where damage, injuries, and fatalities are a frequent result of such phenomena. Accordingly, any comprehensive assessment of the regional effects of climate change must account for these effects.In this work, the authors present a ''perfect prog'' approach to estimating the potential for surface-based convective initiation and severity based upon the large-scale variables well resolved by climate model simulations. This approach allows for the development of a stable estimation scheme that can be applied to any climate model simulation, presently and into the future. The scheme is applied for the contiguous United States using the output from the Parallel Climate Model, with the Intergovernmental Panel on Climate Change third assessment A2 (business as usual) as input. For this run, relative to interannual variability, the potential frequency of deep moist convection does not change, but the potential for severe convection is found to increase east of the Rocky Mountains and most notably in the ''tornado alley'' region of the U.S. Midwest. This increase in severe potential is mostly tied to increases in thermodynamic instability as a result of ongoing warm season surface warming and moistening. Finally, approaches toward improving such estimation methods are briefly discussed.
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