Understanding of the possible response of severe convective precipitating storms to elevated greenhouse gas concentrations remains elusive. To address this problem, telescoping, multimodel approaches are proposed, which allow representation of a broad range of processes that could regulate convective storm behavior. In the global-cloud approach (G-C), the NCEP-NCAR Reanalysis Project (NNRP) global data set provides initial and boundary conditions for short-term integrations of a mesoscale model and nested convective-cloud-permitting domain. In the global-regional-cloud approach (G-R-C), the NNRP data set provides initial and boundary conditions for long-term integrations of a regional climate model, which in turn forces short-term integrations of a mesoscale model and nested convective-cloud-permitting domain. Upon applying these approaches to historical extreme convective storm events, it was found that the global-scale data could be dynamically downscaled to produce realistic convective-scale solutions. In particular, tornado proxies computed from the model-simulated winds were shown to compare well in relative numbers to those of tornado observations on many of the days considered. This supports the telescoping modeling concept as a viable means to address effects of elevated greenhouse gas concentrations on convective-scale phenomena. In an evaluation of the two approaches, it was also found that simulations of the historical events by the G-C were superior to those by the G-R-C. Sensitivity of the convective-scale processes to details in the downscaled synoptic-scale flow, and to the placement of the mesoscale model domain within the regional climate model, reduced the effectiveness of the G-R-C.