The variability of overcast low stratiform clouds observed over the ARM Climate Research Facility Southern Great Plains (ACRF SGP) site is analyzed, and an approach to characterizing subgrid variability based on assumed statistical distributions is evaluated. The analysis is based on a vast (>1000 hours) radar reflectivity database collected by the Millimeter-Wave Cloud Radar at ACRF SGP site. The radar data are classified into two low cloud categories and stratified by scale and the presence of precipitation. Cloud variability is analyzed by studying statistical distributions for the first two moments of the probability distribution functions (PDF) of radar reflectivity. Results indicate that variability for a broadly defined low-altitude stratiform cloud type exhibits on average 40% greater standard deviation than canonical boundary layer clouds topped by an inversion. Cloud variability also dramatically depends on microphysical processes (as manifested in radar reflectivity) and increases by 2--5 times within a typical reflectivity range. Finally, variability is a strong function of scale and almost doubles in the 20--100 min temporal scale range. Formulations of subgrid variability, based on PDFs of reflectivity, are evaluated for the two cloud types and two scales of 10 and 30 km, taken to be representative of mesoscale and NWP model grid sizes. The results show that for these cloud types and scales the PDF of reflectivity can be reasonably well approximated by a truncated Gaussian function, specified by mean and standard deviation with the latter parameterized as a linear function of the mean.