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Predictability of atmospheric flow at synoptic scales :influence of moisture and non-linear processes

Abstract : This work aims at explaining the importance of moisture and nonlinear processes for the predictability of baroclinic systems. In order to study nonlinear growth of errors, the Nonlinear Singular Vectors technique (NLSV) is introduced: these are the most rapidly amplifying perturbations on the lead time of the forecast. The first part of this work studies the physical properties of NLSV s in atmospheric models with different levels of realism. The importance of nonlinear interactions between the mean flow and the perturbation is highlighted. Then the impact of precipitation on the structure and amplification of optimal perturbations is studied in a GCM. ln the last section, a novel nonlinear method for investigating the sensitivity of error growth to the moisture of the basic state is introduced and shows a negative impact of moisture on predictability .
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Contributor : Ecole Des Ponts Paristech <>
Submitted on : Friday, January 30, 2009 - 8:00:00 AM
Last modification on : Friday, January 30, 2009 - 8:00:00 AM
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Olivier Rivière. Predictability of atmospheric flow at synoptic scales :influence of moisture and non-linear processes. Sciences of the Universe [physics]. Ecole des Ponts ParisTech, 2007. English. ⟨pastel-00004043⟩

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