ausblenden:
Schlagwörter:
GENERAL-CIRCULATION MODEL; DATA ASSIMILATION; TROPICAL PACIFIC; OCEAN MODEL; ICE MODEL; CLIMATE; PREDICTION; ENSO; VARIABILITY; SYSTEM
Zusammenfassung:
A simple method for initializing coupled general circulation models (CGCMs) using only sea surface temperature (SST) data is comprehensively tested in an extended set of ensemble hindcasts with the Max-Planck-Institute (MPI) climate model, MPI-OM/ECHAM5. In the scheme, initial conditions for both atmosphere and ocean are generated by running the coupled model with SST nudged strongly to observations. Air-sea interaction provides the mechanism through which SST influences the subsurface. Comparison with observations indicates that the scheme is performing well in the tropical Pacific.
Results from a 500-yr control run show that the model's El Nino Southern Oscillation (ENSO) variability is quite realistic, in terms of strength, structure and period. The hindcasts performed were six months long, initiated four times per year, consisted of nine ensemble members, and covered the period 1969-2001. The ensemble was generated by only varying atmospheric initial conditions, which were sampled from the initialization run to capture intraseasonal variability. At six-month lead, the model is able to capture all the major ENSO extremes of the period. However, because of poor sampling of ocean initial conditions and model deficiencies, the ensemble-mean anomaly correlation skill for Nino3 SST is only 0.6 at six-month lead. None the less, the results presented here demonstrate the potential of such a simple scheme, and provide a simple method by which SST information may be better used in more complex initialization schemes.
