Simulation and prediction of El Nino and interactions with the seasonal cycle in a hybrid coupled model

A hybrid coupled model (HCM) for the tropical Pacific ocean-atmosphere system is employed for ENSO simulation and prediction. The ocean component is the fully nonlinear Geophysical Fluid Dynamics Laboratory ocean general circulation model. The atmospheric component is an empirical model that specifies wind stress from ocean model sea surface temperatures (SST), derived from singular value decomposition of the covariance between observed surface wind stress and SST fluctuations.; A coupled seasonal cycle approach is used to model the coupled feedbacks, mainly the momentum feedbacks, in the seasonal cycle on the same basis as the interannual variability. The result indicates that the momentum feedbacks in coupled processes have significant effects in the ocean-atmosphere system in producing the seasonal cycle in the equatorial Pacific.; With a more conventional coupling approach, the impacts of ocean vertical mixing schemes and atmospheric spin-up time on ENSO period are investigated. With a surface-layer parameterization that gives stronger vertical mixing, a longer inherent ENSO period is obtained. Longer atmospheric spin-up time scale further lengthens the inherent ENSO period. The standard version of the HCM exhibits 3- and 4-year frequency-locking behavior and spatial and temporal evolution that compare well to observations.; The interactions between the inherent ENSO variability and the seasonal cycle can lead to frequency-locking and transition to chaos, which has been suggested to be the source of ENSO irregularity. A considerable parameter range is explored and only mild chaotic behavior is found. Error growth due to sensitive dependence on initial conditions is found to be small on a time scale of several years. This suggests that chaotic behavior is not a serious limitation to ENSO prediction, compared to other factors, such as weather noise.; Our model results exhibit a scattered phase-locking behavior, due to the alternation between different integer-year intervals attempting to match the preferred season. This behavior is also found in observations, which suggests that the ENSO phase locking takes into account the integrated effects from past events and how much the preferred period can be stretched.; In HCM hindcast experiments, a correlation skill competitive to other prediction models is obtained, using results of the Climate Prediction Center data assimilation product from a related ocean model. The hindcast results confirm the importance of ocean subsurface structure and show the crucial wind components are those associated with the slow ENSO mode.