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Estimation of Positive Sum-to-one Constrained Zooplankton Grazing Preferences with the Denkf: a Twin Experiment : Volume 9, Issue 2 (19/03/2012)

By Simon, E.

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Book Id: WPLBN0003978896
Format Type: PDF Article :
File Size: Pages 37
Reproduction Date: 2015

Title: Estimation of Positive Sum-to-one Constrained Zooplankton Grazing Preferences with the Denkf: a Twin Experiment : Volume 9, Issue 2 (19/03/2012)  
Author: Simon, E.
Volume: Vol. 9, Issue 2
Language: English
Subject: Science, Ocean, Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Dumont, D., Samuelsen, A., Bertino, L., & Simon, E. (2012). Estimation of Positive Sum-to-one Constrained Zooplankton Grazing Preferences with the Denkf: a Twin Experiment : Volume 9, Issue 2 (19/03/2012). Retrieved from

Description: Nansen Environmental and Remote Sensing Center, Norway. 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 1-D coupled model GOTM-NORWECOM with Gaussian anamorphosis extensions of the deterministic ensemble Kalman filter (DEnKF).

Estimation of positive sum-to-one constrained zooplankton grazing preferences with the DEnKF: a twin experiment

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