IMIS | Flanders Marine Institute
 

Flanders Marine Institute

Platform for marine research

IMIS

Publications | Institutes | Persons | Datasets | Projects | Maps
[ report an error in this record ]basket (0): add | show Printer-friendly version

An Ensemble Kalman filter with a 1-D marine ecosystem model
Eknes, M.; Evensen, G. (2002). An Ensemble Kalman filter with a 1-D marine ecosystem model. J. Mar. Syst. 36(1-2): 75-100. dx.doi.org/10.1016/s0924-7963(02)00134-3
In: Journal of Marine Systems. Elsevier: Tokyo; Oxford; New York; Amsterdam. ISSN 0924-7963, more
Peer reviewed article  

Available in Authors 

Keywords
    Data processing; Ecosystems; Kalman filters; Methodology; Modelling; Marine

Authors  Top 
  • Eknes, M.
  • Evensen, G.

Abstract
    The Ensemble Kalman Filter (EnKF) has been examined in a data assimilation experiment with a one-dimensional three-component ecosystem model. The model is an extension of the zero-dimensional model developed by Evans and Parslow [Biol. Oceanogr. 3 (1985) 327.]. The purpose of this paper is to examine the possibilities of using a sequential data assimilation method for state estimation in a biological model, an approach which differs from the more traditional parameter estimation studies. The method chosen is the Ensemble Kalman Filer (EnKF), and it has been shown that this method captures the nonlinear error evolution in time and is capable of both tracking the reference solution and to provide realistic error estimates for the estimated state. This is an indication that the methodology might be suitable for future operational data assimilation systems using more complex three-dimensional models.

All data in IMIS is subject to the VLIZ privacy policy Top | Authors