A methodology to test the pertinence of remote-sensing data assimilation into vegetation models for water and energy exchange at the land surface

Issue		Agron. Sustain. Dev. Volume 24, Number 4, May-June 2004


Page(s)		197 - 204
DOI		10.1051/agro:2004017

Agronomie 24 (2004) 197-204
DOI: 10.1051/agro:2004017

A methodology to test the pertinence of remote-sensing data assimilation into vegetation models for water and energy exchange at the land surface

Jennifer Pellenq and Gilles Boulet

CESBIO (UMR 5126 UPS-CNRS-CNES-IRD), 18 avenue Edouard Belin, bpi 2801, 31401 Toulouse Cedex 4, France

(Received 9 October 2002; accepted 10 June 2003)

Abstract - This paper presents a methodology to test the performance of assimilation of satellite data into models for the functioning of the continental surface. This methodology applies the Kalman Ensemble Filter to modelling of plant growth and senescence in conjunction with the water and energy exchanges at the land surface. It belongs to a family of methods known in meteorology and oceanography as the Observing System Simulation Experiment (OSSE) approach. By combining information from modelling and observation, the Kalman Ensemble Filter permits corrections in real time of the simulated state of the continental surface, as well as propagation in time of the associated uncertainties. The OSSE approach may present a first step in designing a decision support system, and also in predicting the usefulness of new types of satellite data.

Key words: surface functioning / data assimilation / remote sensing / OSSE / Kalman Ensemble Filter

Corresponding author: Gilles Boulet Gilles.Boulet@ird.fr

© INRA, EDP Sciences 2004

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