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Variational assimilation: application to the control of the initial data in ICARE model

N Alaa, W. Bouarifi, G. Boullet, A. Chehbouni, R. Khiri, L. Hanich


Variational assimilation is a statistical technique to combine measurements of variables such as the atmospheric temperature, water content or precipitation, with models that describe the time evolution of these variables. The error statistics of both the measurements and the model is used to find the best guess of the actual field. In this paper we are interested in the application of variational assimilation with the SVAT model to assimilate the initial data of soil temperature. The initial conditions or parameters are usually inferred by minimizing the sum of the squared difference between the observed system and the one calculated by mathematical model. This approach is used to assimilate the initial data of the temperature of the soil in ICARE model in the model Agdal gardens near of Marrakech (Morocco).


data assimilation, optimal control, inverse modelling

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