A reduced order approach for 4D-Var data assimilation is presented in the context of a tropical Pacific ocean model. The control space is defined as the span of a few vectors representing a significant part of the system variability. It is shown that such an approach can lead to significant improvements, both in terms of the quality of the solution and of the computational efficiency. A first step toward an hybrid variational-sequential algorithm is also discussed.