This presentation will focus on specific results from the OSSEs that are unique to the upscale growth scenario simulated herein. The analysis root mean squared error (RMSE), as measured by direct comparison to the truth simulation, increased during two periods of cell mergers. The increase in RMSE is partially mitigated by tuning the covariance localization parameter, especially in the vertical. Hypotheses why these analyses may be particularly sensitive to the localization, especially the vertical localization, during the cell merger phase will be presented. Further, producing accurate analyses of the developing surface cold pool is particularly important for convective systems that undergo upscale growth. The representation of the cold pool in the OSSEs was particularly sensitive to the additive noise (Dowell et al. 2009) parameters used to maintain ensemble spread. Reducing the amount of additive noise decreased the RMSE within the cold pool, but increased RMSE elsewhere within the convective system. Finally, findings from the OSSEs will be compared to preliminary results from a real-data case study (using a realistic mesoscale environment) of a developing MCS to gauge their robustness.