Could we guess the diet of different zooplankton species with data assimilation?

Ehouarn Simon
Seminar Date: 
29. March 2012 - 12:30 - 13:00
Lecture room, Ground Floor, NERSC

We consider the estimation of the grazing preferences parameters of zooplankton in ocean ecosystem models with ensemble-based Kalman filters. These parameters are introduced to model the relative diet composition of zooplankton that consists of phytoplankton, small size-classes of zooplankton and detritus. They are positive values and their sum is equal to one. However, the sum-to-one constraint cannot be guaranteed by ensemble-based Kalman filters when parameters are bounded. Therefore, a reformulation of the parameterization is proposed. We investigate two types of variables transformations for the estimation of positive sum-to-one constrained parameters that lead to the estimation of new set of parameters with normal or bounded distributions. These transformations are illustrated and discussed with twin experiments performed with the 1D coupled model GOTM-NORWECOM with Gaussian anamorphosis extensions of the deterministic ensemble Kalman filter (DEnKF).