Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.509 IF 5.509
  • IF 5-year value: 5.689 IF 5-year 5.689
  • CiteScore value: 5.44 CiteScore 5.44
  • SNIP value: 1.519 SNIP 1.519
  • SJR value: 3.032 SJR 3.032
  • IPP value: 5.37 IPP 5.37
  • h5-index value: 86 h5-index 86
  • Scimago H index value: 161 Scimago H index 161
Volume 15, issue 10
Atmos. Chem. Phys., 15, 5325-5358, 2015
https://doi.org/10.5194/acp-15-5325-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Coupled chemistry–meteorology modelling: status and...

Atmos. Chem. Phys., 15, 5325-5358, 2015
https://doi.org/10.5194/acp-15-5325-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Review article 18 May 2015

Review article | 18 May 2015

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

M. Bocquet et al.
Related authors  
Calibration of a multi-physics ensemble for greenhouse gas atmospheric transport model uncertainty estimation
Liza I. Díaz-Isaac, Thomas Lauvaux, Marc Bocquet, and Kenneth J. Davis
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1117,https://doi.org/10.5194/acp-2018-1117, 2018
Manuscript under review for ACP
Short summary
Review article: Comparison of local particle filters and new implementations
Alban Farchi and Marc Bocquet
Nonlin. Processes Geophys., 25, 765-807, https://doi.org/10.5194/npg-25-765-2018,https://doi.org/10.5194/npg-25-765-2018, 2018
Short summary
Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error
Colin Grudzien, Alberto Carrassi, and Marc Bocquet
Nonlin. Processes Geophys., 25, 633-648, https://doi.org/10.5194/npg-25-633-2018,https://doi.org/10.5194/npg-25-633-2018, 2018
Short summary
Parametric covariance dynamics for the nonlinear diffusive Burgers equation
Olivier Pannekoucke, Marc Bocquet, and Richard Ménard
Nonlin. Processes Geophys., 25, 481-495, https://doi.org/10.5194/npg-25-481-2018,https://doi.org/10.5194/npg-25-481-2018, 2018
Short summary
Quasi-static ensemble variational data assimilation: a theoretical and numerical study with the iterative ensemble Kalman smoother
Anthony Fillion, Marc Bocquet, and Serge Gratton
Nonlin. Processes Geophys., 25, 315-334, https://doi.org/10.5194/npg-25-315-2018,https://doi.org/10.5194/npg-25-315-2018, 2018
Short summary
Related subject area  
Subject: Gases | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Organic peroxy radical chemistry in oxidation flow reactors and environmental chambers and their atmospheric relevance
Zhe Peng, Julia Lee-Taylor, John J. Orlando, Geoffrey S. Tyndall, and Jose L. Jimenez
Atmos. Chem. Phys., 19, 813-834, https://doi.org/10.5194/acp-19-813-2019,https://doi.org/10.5194/acp-19-813-2019, 2019
Short summary
Comparison of surface ozone simulation among selected regional models in MICS-Asia III – effects of chemistry and vertical transport for the causes of difference
Hajime Akimoto, Tatsuya Nagashima, Jie Li, Joshua S. Fu, Dongsheng Ji, Jiani Tan, and Zifa Wang
Atmos. Chem. Phys., 19, 603-615, https://doi.org/10.5194/acp-19-603-2019,https://doi.org/10.5194/acp-19-603-2019, 2019
Short summary
Diurnal cycle of coastal anthropogenic pollutant transport over southern West Africa during the DACCIWA campaign
Adrien Deroubaix, Laurent Menut, Cyrille Flamant, Joel Brito, Cyrielle Denjean, Volker Dreiling, Andreas Fink, Corinne Jambert, Norbert Kalthoff, Peter Knippertz, Russ Ladkin, Sylvain Mailler, Marlon Maranan, Federica Pacifico, Bruno Piguet, Guillaume Siour, and Solène Turquety
Atmos. Chem. Phys., 19, 473-497, https://doi.org/10.5194/acp-19-473-2019,https://doi.org/10.5194/acp-19-473-2019, 2019
Short summary
Constraints and biases in a tropospheric two-box model of OH
Stijn Naus, Stephen A. Montzka, Sudhanshu Pandey, Sourish Basu, Ed J. Dlugokencky, and Maarten Krol
Atmos. Chem. Phys., 19, 407-424, https://doi.org/10.5194/acp-19-407-2019,https://doi.org/10.5194/acp-19-407-2019, 2019
Short summary
Quantification and evaluation of atmospheric pollutant emissions from open biomass burning with multiple methods: a case study for the Yangtze River Delta region, China
Yang Yang and Yu Zhao
Atmos. Chem. Phys., 19, 327-348, https://doi.org/10.5194/acp-19-327-2019,https://doi.org/10.5194/acp-19-327-2019, 2019
Short summary
Cited articles  
Abida, R. and Bocquet, M.: Targeting of observations for accidental atmospheric release monitoring, Atmos. Environ., 43, 6312–6327, 2009.
Adhikary, B., Kulkarni, S., Dallura, A., Tang, Y., Chai, T., Leung, L. R., Qian, Y., Chung, C. E., Ramanathan, V., and Carmichael, G. R.: A regional scale chemical transport modeling of Asian aerosols with data assimilation of AOD observations using optimal interpolation technique, Atmos. Environ., 42, 8600–8615, https://doi.org/10.1016/j.atmosenv.2008.08.031, 2008.
Anderson, J. L. and Anderson, S. L.: A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts, Mon. Weather Rev., 127, 2741–2758, 1999.
Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems, IEEE Trans. Geosci. Remote Sens., 41, 253–264, 2003.
Publications Copernicus
Special issue
Download
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.
Data assimilation is used in atmospheric chemistry models to improve air quality forecasts,...
Citation
Share