Ensemble-based atmospheric reanalysis using a global coupled atmosphere-ocean GCM

Ensemble-based atmospheric data assimilation (DA) systems are sometimes afflicted with an underestimation of the ensemble spread near the surface caused by the use of identical boundary conditions for all ensemble members and the lack of atmosphere-ocean interaction. To overcome these problems, a newDAsystem has been developed by replacing an atmospheric GCM with a coupled atmosphere-ocean GCM, in which atmospheric observational data are assimilated every 6 h to update the atmospheric variables, whereas the oceanic variables are subject to no directDA. Although SST suffers from the common biases among many coupledGCMs, twomonths of a retrospective analysis-forecast cycle reveals that the ensemble spreads of air temperature and specific humidity in the surface boundary layer are slightly increased and the forecast skill in the midtroposphere is rather improved by using the coupledDAsystem in comparison with the atmosphericDAsystem. In addition, surface atmospheric variables over the tropical Pacific have the basinwide horizontal correlation in ensemble space in the coupled DA system but not in the atmospheric DA system. This suggests the potential benefit of using a coupled GCMrather than an atmospheric GCM even for atmospheric reanalysis with an ensemble-based DA system.