This study identifies soil moisture spatial variability patterns using measurements across different extents (i.e., field, watershed, and basin) and depths (i.e., from surface to root zone profile) from 18 different soil moisture field experiments. The spatial variability patterns are well represented by negative exponential functions between the mean and the coefficient of variation of soil moisture. Principal component analysis demonstrates that rainfall and topography explain surface soil moisture variability changes as soils dry, while soil parameters control the maximum relative variability. Soil moisture's relative variability typically decreases as sampling extent increases, supporting the power law decay function proposed by Rodriquez-Iturbe et al. (1995). The finding that soil moisture relative variability increases as soil depth increases is consistent with an earlier study (Choi and Jacobs, 2006). These common soil moisture variability patterns can provide a feasible methodology to validate land surface models and to estimate variability across extents from mean soil moisture values.