Towards a data assimilation system for the Cretan Sea ecosystem using a simplified Kalman filter

With the aim of using data assimilation techniques for state estimation in marine ecosystem models, a singular evolutive extended Kalman (SEEK) filter was used to assimilate real in situ data in a water column marine coupled physical-biogeochemical model describing the Cretan sea ecosystem. The biogeochemistry of the ecosystem is described by the European Regional Sea Ecosystem Model (ERSEM), while the Princeton Ocean Model (POM) describes the physical forcing. In the SEEK filter, the error statistics are parameterised by means of a suitable set of empirical orthogonal functions (EOFs). Numerical experiments were conducted to evaluate the performance of this assimilation system. In this context, sensitivity studies to the observations are also presented and discussed.