Geoengineering for climate control is gaining attention in the quest to combat climate change. Under this context, our study utilizes a general circulation model (GCM) of intermediate complexity known as Planet Simulator (PLASIM), to assess the potential for manipulating top-of-atmosphere shortwave radiative forcing. Our approach is based on a series of Green’s function experiments, which allow for constructing a forcing-response relationship ensemble adequate for machine learning. The critical relationship enables the estimation of the radiative perturbation necessary to induce a specific climate response, such as those associated with the changing of atmospheric CO2 levels. Our findings demonstrate that both temperature and precipitation can be effectively controlled in this intermediate complexity model. More specifically, we provide evidence that the typical climate responses to significant increase in CO2 concentrations can be mitigated through strategic adjustments to radiative forcing.