To parameterize shallow convective clouds and precipitation induced by land surface processes in large-scale atmospheric models (e.g., global climate models and weather forecast models), it is primordial to identify the atmospheric variables and cloud microphysical parameters which have a predominant impact on the development and formation of this type of clouds. For this purpose a sensitivity analysis of the various parameters and processes involved in the development and formation of this type of clouds and precipitation was performed with the Fourier amplitude sensitivity test (FAST). This test determines the relative contribution of the distribution of individual input parameters, assuming that their exact value is unknown, to the variance of the model output. By simultaneously varying all parameters according to their individual probability density function (PDF), the number of computations needed is very much reduced. Assuming various PDFs of cloud microphysical characteristics under a broad range of atmospheric conditions, this analysis demonstrated that given an appropriate atmospheric water content, vertical velocity and air temperature are the dominant atmospheric factor in shallow convective precipitation. This emphasizes the need to correctly calculate the spatial distribution of land surface heat fluxes, which affect the development of microscale and mesoscale turbulence in the atmospheric planetary boundary layer. The uncertainty in estimating cloud droplet concentration, pristine ice concentration, mass coefficient, collision efficiency, terminal velocity, snow crystals diameter, and aggregates diameter can affect quite significantly, one way or the other, the mixing ratio of the various water particles simulated with the cloud microphysics scheme. The relative importance of some of these parameters is very much dependent upon temperature and vertical velocity.