Reference : Constraining model biases in a global general circulation model with ensemble data as...
Dissertations and theses : Doctoral thesis
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
Constraining model biases in a global general circulation model with ensemble data assimilation methods
Canter, Martin mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Université de Liège, ​Liège, ​​Belgique
Docteur en Sciences
Barth, Alexander mailto
Donnay, Jean-Paul mailto
Beckers, Jean-Marie mailto
Counillon, François
Goosse, Hugues
Brasseur, Pierre
Testut, Charles-Emmanuel
[en] Data assimilation ; Ensemble Transform Kalman Filter ; Bias correction
[en] A new method of bias correction using an ensemble transform Kalman filter as data assimilation scheme is developed. The objective is to create a stochastic forcing term which will partially remove the bias from numerical models. The forcing term is considered as a parameter to be estimated through state vector augmentation and the assimilation of observations.

The theoretical formulation of this method is introduced in the general context of numerical modelling. A specially designed and modified Lorenz '96 model is studied, and provides a testing environment for this new bias correction method. Several different aspects are considered through both single and iterative assimilation in a twin experiment.

The method is then implemented on the global general circulation model of the ocean NEMO-LIM2. The forcing term generation is detailed to respect particular physical constraints. Again, a twin experiment allows to assess the efficiency of the method on a realistic model. The assimilation of sea surface height observations is performed, with sea surface salinity and temperature as control variable. Subsequently, a multivariate assimilation shows further improvement of the bias correction.

Finally, the method is confronted to real sea surface height observations from the CNES-CLS09 global mean dynamic topography. A thorough study of the NEMO-LIM2 model response to the bias correction forcing term is proposed, and specific results are highlighted. An iterative assimilation concludes the method investigation. Possible ideas and future developments are suggested.
GeoHydrodynamics and Environment Research
Researchers ; Professionals

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