A primary solar climate intervention (SCI) strategy is stratospheric aerosol injection (SAI). SAI would increase the number of small reflective particles (aerosols) in the upper atmosphere to reduce climate warming by reflecting more incoming solar radiation away from Earth. Research on SCI is growing quickly, but no studies to date have examined the impact of SCI on severe storms using a mesoscale weather model. In this study, we develop a novel framework using the convection-permitting (4-km resolution) Weather Research & Forecasting (WRF) model to assess the potential impact of SCI on future convective weather over the contiguous United States (CONUS). We conduct three types of simulations for the March–August 2011 period, during which widespread convective outbreaks occurred across the CONUS: (1) a control simulation driven by ERA-5 reanalysis; (2) a Pseudo-Global Warming (PGW) simulation representing a future with increasing greenhouse gas concentrations but without SCI; and (3) a novel Pseudo-SAI (PSAI) simulation representing a future with SCI. Future climate perturbations applied to the PGW and PSAI boundary conditions are derived from ensemble-mean differences between baseline and future scenarios in Community Earth System Model (CESM) experiments with and without SCI. These perturbations are taken from two CESM projects featuring different scenarios: the Geoengineering Large Ensemble (GLENS) and the Assessing Responses and Impacts of Solar Climate Intervention on the Earth System with Stratospheric Aerosol Injection (ARISE). The PSAI simulation includes an additional aerosol optical depth perturbation to represent the shortwave radiative impact of SAI. This paper presents the novel experimental design and modeling framework, and shares preliminary results that highlight the feasibility and scientific potential of this approach for assessing potential weather-scale impacts of SCI. In particular, we show that global warming leads to an increase in extreme precipitation and more frequent deep convection over the Eastern U.S., both of which can be mitigated by SAI deployment.