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| Titel |
Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system |
| VerfasserIn |
J. J. Guerrette, D. K. Henze |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 6 ; Nr. 8, no. 6 (2015-06-23), S.1857-1876 |
| Datensatznummer |
250116414
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| Publikation (Nr.) |
 copernicus.org/gmd-8-1857-2015.pdf |
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| Zusammenfassung |
| Here we present the online meteorology and chemistry adjoint and
tangent linear model, WRFPLUS-Chem (Weather Research and Forecasting plus chemistry), which incorporates modules to
treat boundary layer mixing, emission, aging, dry deposition, and
advection of black carbon aerosol. We also develop land surface and
surface layer adjoints to account for coupling between radiation and
vertical mixing. Model performance is verified against finite
difference derivative approximations. A second-order checkpointing
scheme is created to reduce computational costs and enable simulations
longer than 6 h. The adjoint is coupled to WRFDA-Chem, in order
to conduct a sensitivity study of anthropogenic and biomass burning
sources throughout California during the 2008 Arctic Research of the
Composition of the Troposphere from Aircraft and Satellites (ARCTAS)
field campaign. A cost-function weighting scheme was devised to
reduce the impact of statistically insignificant residual errors in future
inverse modeling studies.
Results of the sensitivity study show that, for this domain
and time period, anthropogenic emissions are overpredicted, while
wildfire emission error signs vary spatially. We consider the diurnal
variation in emission sensitivities to determine at what time sources
should be scaled up or down. Also, adjoint sensitivities for two
choices of land surface model (LSM) indicate that emission inversion results
would be sensitive to forward model configuration. The tools
described here are the first step in conducting four-dimensional
variational data assimilation in a coupled meteorology–chemistry
model, which will potentially provide new constraints on aerosol
precursor emissions and their distributions. Such analyses will be
invaluable to assessments of particulate matter health and climate
impacts. |
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