Data assimilation in support of tropical ocean circulation studies

The assimilation of data into tropical ocean models is an active area of research for a variety of reasons. The deterministic nature of the tropical ocean circulation, the rapid time scale at low latitudes, the two-layer approximation, the non-local impact of assimilated data, the increased quantity of in situ data obtained as part of the TOGA Program, and the important role played by the tropics in short-term climate prediction have stimulated data assimilation in tropical oceanography. This paper describes the extent of the approaches in data assimilation supporting tropical ocean circulation studies. Data assimilation efforts in the tropics encompass initialization experiments, observing system simulation experiments, estimation of model parameters, and real-time analyses for the tropical Pacific Ocean. The data that are most frequently assimilated are observations of the vertical structure of temperature and sea level height. Observations of sea level and thermocline depth are normally assimilated into reduced-gravity models with the more advanced assimilation schemes such as the Kalman filter and the adjoint method. The effect of the data usually increases the amplitude of the variability in the model. Four-dimensional temperature observations are used to constrain primitive equation, general circulation models via optimal interpolation and successive correction methods. The principal influence of the assimilated data is to eliminate systematic biases in the model temperature fields.