Articles | Volume 15, issue 10
https://doi.org/10.5194/acp-15-5325-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/acp-15-5325-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models
M. Bocquet
CEREA, Joint Laboratory École des Ponts ParisTech/EDF R&D, Université Paris-Est, Marne-la-Vallée, France
INRIA, Paris Rocquencourt Research Center, Rocquencourt, France
H. Elbern
Institute for Physics and Meteorology, University of Cologne, Cologne, Germany
H. Eskes
KNMI, De Bilt, The Netherlands
M. Hirtl
Central Institute for Meteorology and Geodynamics, Vienna, Austria
R. Žabkar
Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
G. R. Carmichael
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, USA
J. Flemming
European Centre for Medium-range Weather Forecasts, Reading, UK
A. Inness
European Centre for Medium-range Weather Forecasts, Reading, UK
M. Pagowski
NOAA/ESRL, Boulder, Colorado, USA
J. L. Pérez Camaño
Technical University of Madrid (UPM), Madrid, Spain
P. E. Saide
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, USA
R. San Jose
Technical University of Madrid (UPM), Madrid, Spain
M. Sofiev
Finnish Meteorological Institute, Helsinki, Finland
Finnish Meteorological Institute, Helsinki, Finland
A. Baklanov
World Meteorological Organization (WMO), Geneva, Switzerland and Danish Meteorological Institute (DMI), Copenhagen, Denmark
C. Carnevale
Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy
G. Grell
NOAA/ESRL, Boulder, Colorado, USA
C. Seigneur
CORRESPONDING AUTHOR
CEREA, Joint Laboratory École des Ponts ParisTech/EDF R&D, Université Paris-Est, Marne-la-Vallée, France
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126 citations as recorded by crossref.
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- Development of Three‐Dimensional Variational Data Assimilation Method of Aerosol for the CMAQ Model: An Application for PM 2.5 and PM 10 Forecasts in the Sichuan Basin Z. Zhang et al. 10.1029/2020EA001614
- Introducing the MISR level 2 near real-time aerosol product M. Witek et al. 10.5194/amt-14-5577-2021
- Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis K. Miyazaki & K. Bowman 10.5194/acp-17-8285-2017
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Short summary
Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of concentrations, and perform inverse modeling. Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. We review here the current status of data assimilation in atmospheric chemistry models, with a particular focus on future prospects for data assimilation in CCMM.
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