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| Titel |
A review of operational, regional-scale, chemical weather forecasting models in Europe |
| VerfasserIn |
J. Kukkonen, T. Olsson, D. M. Schultz, A. Baklanov, T. Klein, A. I. Miranda, A. Monteiro, M. Hirtl, V. Tarvainen, M. Boy, V.-H. Peuch, A. Poupkou, I. Kioutsioukis, S. Finardi, M. Sofiev, R. Sokhi, K. E. J. Lehtinen, K. Karatzas, R. San José, M. Astitha, G. Kallos, M. Schaap, E. Reimer, H. Jakobs, K. Eben |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 1 ; Nr. 12, no. 1 (2012-01-02), S.1-87 |
| Datensatznummer |
250010421
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| Publikation (Nr.) |
 copernicus.org/acp-12-1-2012.pdf |
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| Zusammenfassung |
| Numerical models that combine weather forecasting and atmospheric
chemistry are here referred to as chemical weather forecasting
models. Eighteen operational chemical weather forecasting models on
regional and continental scales in Europe are described and compared
in this article. Topics discussed in this article include how weather
forecasting and atmospheric chemistry models are integrated into
chemical weather forecasting systems, how physical processes are
incorporated into the models through parameterization schemes, how the
model architecture affects the predicted variables, and how air
chemistry and aerosol processes are formulated. In addition, we
discuss sensitivity analysis and evaluation of the models, user
operational requirements, such as model availability and
documentation, and output availability and dissemination. In this
manner, this article allows for the evaluation of the relative
strengths and weaknesses of the various modelling systems and
modelling approaches. Finally, this article highlights the most
prominent gaps of knowledge for chemical weather forecasting models
and suggests potential priorities for future research directions, for
the following selected focus areas: emission inventories, the
integration of numerical weather prediction and atmospheric chemical
transport models, boundary conditions and nesting of models, data
assimilation of the various chemical species, improved understanding
and parameterization of physical processes, better evaluation of
models against data and the construction of model ensembles. |
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