Toward a Pre-Operational Data Assimilation System for the E. Mediterranean using Kalman Filtering Techniques

This paper describes a sophisticated data assimilation system which has been developed for the estimation of the state of the Eastern Mediterranean ecosystem. The forecast model is based on the complex biochemical ERSEM model coupled with the physical general ocean circulation POM model. The assimilation scheme is a square-root based Kalman filter which makes also use of low rank error covariance matrices to reduce computational cost. The assimilation of only surface sea color data shows a clear improvement in the model’s behavior and a continuous decrease in the estimation error.