The impact of cloud condensation nuclei (CCN) concentration on microphysical processes within thunderstorms and the resulting surface precipitation is not fully understood yet. In this work, an analysis of the microphysical pathways occurring in these clouds is proposed to systematically investigate and understand these sensitivities. Thunderstorms were simulated using convection-permitting (1 km horizontal grid spacing) idealised simulations with the ICON model, which included a 2-moment microphysics parameterization. CCN concentrations were increased from 100 to 3200 CCN/cm3, in five different wind shear environments ranging from 18 to 50 m/s. Large and systematic decreases of surface precipitation (up to 35%) and hail (up to 90%) were found as CCN was increased. Wind shear changes the details, but not the sign, of the sensitivity to CCN. The microphysical process rates were tracked throughout each simulation, closing the mass budget for each hydrometeor class, and collected together into “microphysical pathways”, which quantify the different growth processes leading to surface precipitation. Almost all surface precipitation occurred through the mixed-phase pathway, where graupel and hail grow by riming and later melt as they fall to the surface. The mixed-phase pathway is sensitive to CCN concentration changes as a result of changes to the riming rate, which were systematically evaluated. Supercooled water content was almost insensitive to increasing CCN concentration, but decreased cloud drop size led to a large reduction in the riming efficiency (from 0.79 to 0.24) between supercooled cloud drops and graupel or hail, resulting in less surface precipitation.