Publication: Automatic Differentiation as a Tool for Sensitivity Analysis of a Convective Storm in a 3-D Cloud Model
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Automatic Differentiation as a Tool for Sensitivity Analysis of a Convective Storm in a 3-D Cloud Model

- incollection -
 

Author(s)
Seon Ki Park , Kelvin K. Droegemeier , Christian H. Bischof

Published in
Computational Differentiation: Techniques, Applications, and Tools

Editor(s)
Martin Berz, Christian H. Bischof, George F. Corliss, Andreas Griewank

Year
1996

Publisher
SIAM

Abstract
The ADIFOR automatic differentiation tool is applied to a 3-D storm-scale meteorological model to generate a sensitivity-enhanced code capable of providing derivatives of all model output variables and related diagnostic (derived) parameters as a function of specified control parameters. The tangent linear approximation, applied to a deep convective storm by the first of its kind using a full-physics compressible model, is valid up to 50 min for a 1 % water vapor perturbation. The result is very encouraging considering the highly nonlinear and discontinuous properties of solutions. The ADIFOR-generated code has provided valuable sensitivity information on storm dynamics. Especially, it is very efficient and useful for investigating how a perturbation inserted at earlier time propagates through the model variables at later times. However, it is computationally very expensive to apply to the variational data assimilation, especially for 3-D meteorological models, which potentially have a large number of input variables.

Cross-References
Berz1996CDT

BibTeX
@INCOLLECTION{
         Park1996ADa,
       author = "Seon Ki Park and Kelvin K. Droegemeier and Christian H. Bischof",
       editor = "Martin Berz and Christian H. Bischof and George F. Corliss and Andreas Griewank",
       title = "Automatic Differentiation as a Tool for Sensitivity Analysis of a Convective Storm in
         a 3-{D} Cloud Model",
       booktitle = "Computational Differentiation: Techniques, Applications, and Tools",
       pages = "205--214",
       publisher = "SIAM",
       address = "Philadelphia, PA",
       key = "Park1996ADa",
       crossref = "Berz1996CDT",
       abstract = "The ADIFOR automatic differentiation tool is applied to a 3-D storm-scale
         meteorological model to generate a sensitivity-enhanced code capable of providing derivatives of all
         model output variables and related diagnostic (derived) parameters as a function of specified
         control parameters. The tangent linear approximation, applied to a deep convective storm by the
         first of its kind using a full-physics compressible model, is valid up to 50 min for a 1 \%
         water vapor perturbation. The result is very encouraging considering the highly nonlinear and
         discontinuous properties of solutions. The ADIFOR-generated code has provided valuable sensitivity
         information on storm dynamics. Especially, it is very efficient and useful for investigating how a
         perturbation inserted at earlier time propagates through the model variables at later times.
         However, it is computationally very expensive to apply to the variational data assimilation,
         especially for 3-D meteorological models, which potentially have a large number of input
         variables.",
       keywords = "Tangent linear approximation, forward sensitivity, adjoint sensitivity, variational
         data assimilation, convective storm, 3-D cloud model, moist convection, supercell storm.",
       year = "1996"
}


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