Rank histograms constructed from the unmodified ensemble imply either severe bias problems in the ensemble or a significantly underdispersed ensemble, depending on the variable examined, forecast time, pressure level, and location. Because forecasts between the different locations are poorly correlated, the assumption of independence is acceptable and rank histograms for each location are merged into combined rank histograms for all cities for a given variable, forecast time, pressure level, and location to produce adequate sample sizes. Combined rank histograms constructed from the bias corrected ensemble are U-shaped, which may be caused either by an under-dispersed ensemble, a non-homogeneous bias structures, or observational errors. However, including observational errors with the bias correction often results in uniform or, occasionally over-dispersed, rank histograms. Analysis of other factors, including non-homogeneous biases of the ensemble, is shown to help understand the combined rank histograms. Without the bias correction, this ensemble if of limited utility, but the lagged bias correction greatly enhances the ensemble performance.