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Article Dans Une Revue Nonlinear Processes in Geophysics Année : 2024

Prognostic Assumed-PDF (DDF) Approach: Further Generalization and Demonstrations

Jun-Ichi Yano
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Résumé

A general formulation for the distribution problem is presented, which is applicable to frequency distributions of subgrid-scale variables, hydrometeor size distributions, as well as to probability distributions characterizing data uncertainties. The general formulation is presented based upon two well-known basic principles: the maximum-entropy principle and Liouville equation. The maximum-entropy principle defines the most likely general distribution form, if necessary constraints are specified. This paper proposes to specify these constraints as the output variables to be used in a host model. Once a general distribution form is defined, the problem of temporal evolution of the distribution reduces to that of predicting a small number of parameters characterizing it. This paper derives prognostic equations for these parameters from the Liouville equation. The developed formulation, which is applicable to a wide range of atmospheric modelling problems, is specifically applied to condensation growth of cloud droplets as a demonstration.
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hal-04449741 , version 1 (09-02-2024)

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Jun-Ichi Yano. Prognostic Assumed-PDF (DDF) Approach: Further Generalization and Demonstrations. Nonlinear Processes in Geophysics, 2024, pp.2024-287. ⟨10.5194/egusphere-2024-287⟩. ⟨hal-04449741⟩
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