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| Titel |
Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis |
| VerfasserIn |
M. Bocquet |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 1 ; Nr. 15, no. 1 (2008-02-18), S.127-143 |
| Datensatznummer |
250012560
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| Publikation (Nr.) |
 copernicus.org/npg-15-127-2008.pdf |
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| Zusammenfassung |
| For a start, recent techniques devoted to the reconstruction of
sources of an atmospheric tracer at continental scale are introduced.
A first method is based on the principle of maximum entropy on the
mean and is briefly reviewed here. A second approach, which has not
been applied in this field yet, is based on an exact Bayesian
approach, through a maximum a posteriori estimator.
The methods share common grounds, and both perform equally well in practice.
When specific prior hypotheses on the sources are
taken into account such as positivity, or boundedness, both methods lead to purposefully
devised cost-functions. These cost-functions are not necessarily
quadratic because the underlying assumptions are not Gaussian.
As a consequence, several mathematical tools developed in data assimilation
on the basis of quadratic cost-functions in order to establish a
posteriori analysis, need to be extended to this non-Gaussian framework.
Concomitantly, the second-order sensitivity analysis needs to be adapted,
as well as the computations of the averaging kernels of the source and
the errors obtained in the reconstruction.
All of these developments are applied to a real case of tracer
dispersion: the European Tracer Experiment [ETEX].
Comparisons are made between a least squares cost function (similar to
the so-called 4D-Var) approach and a cost-function which is not based on Gaussian hypotheses.
Besides, the information content of the observations which is used in
the reconstruction is computed and studied on the application case.
A connection with the degrees of freedom for signal is also
established.
As a by-product of these methodological developments,
conclusions are drawn on the information content of the ETEX
dataset as seen from the inverse modelling point of view. |
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