The emergence of next generation GOES satellites, beginning with GOES-R, poses a serious challenge to data assimilation. Some of the most critical issues to be resolved include: (i) assimilation of satellite observations with high spatial and temporal resolution, (ii) employment of complex atmospheric models with highly non-linear microphysical and thermo-dynamical processes, (iii) calculation of flow dependent background error covariance matrix, involving microphysical variables, (iv) assigning appropriate observation errors, (v) estimation and correction of model errors, (vi) estimation of analysis uncertainty. These issues will be examined and discussed in the context of ensemble data assimilation in application to mesoscale atmospheric models. In special focus will be the impact of numerous observations and many degrees of freedom present in complex atmospheric models.