Articles | Volume 7, issue 1
https://doi.org/10.5194/gmd-7-283-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-283-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
13 Feb 2014
Model evaluation paper |
| 13 Feb 2014
Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model
B. Gaubert
LISA, CNRS/INSU UMR7583, Université Paris-Est Créteil et Université Paris Diderot, Institut Pierre Simon Laplace, 94010 Créteil, France
A. Coman
LISA, CNRS/INSU UMR7583, Université Paris-Est Créteil et Université Paris Diderot, Institut Pierre Simon Laplace, 94010 Créteil, France
G. Foret
LISA, CNRS/INSU UMR7583, Université Paris-Est Créteil et Université Paris Diderot, Institut Pierre Simon Laplace, 94010 Créteil, France
F. Meleux
Institut National de l'Environnement Industriel et des Risques, INERIS, Parc Technologique ALATA-B.P. No. 2, 60550 Verneuil en Halatte, France
A. Ung
Institut National de l'Environnement Industriel et des Risques, INERIS, Parc Technologique ALATA-B.P. No. 2, 60550 Verneuil en Halatte, France
L. Rouil
Institut National de l'Environnement Industriel et des Risques, INERIS, Parc Technologique ALATA-B.P. No. 2, 60550 Verneuil en Halatte, France
A. Ionescu
Centre d'Études et de Recherche en Thermique, Environnement et Systèmes EA 3481, Université Paris-Est Créteil, 94010 Créteil, France
Y. Candau
Centre d'Études et de Recherche en Thermique, Environnement et Systèmes EA 3481, Université Paris-Est Créteil, 94010 Créteil, France
M. Beekmann
LISA, CNRS/INSU UMR7583, Université Paris-Est Créteil et Université Paris Diderot, Institut Pierre Simon Laplace, 94010 Créteil, France
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Short summary
Short summary
A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, and Helen Worden
Atmos. Meas. Tech., 17, 1941–1963, https://doi.org/10.5194/amt-17-1941-2024, https://doi.org/10.5194/amt-17-1941-2024, 2024
Short summary
Short summary
We assimilate different MOPITT CO products to understand the impact of (1) assimilating multispectral and joint retrievals versus single spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral and joint retrievals versus assimilating individual products separately.
Adrien Deroubaix, Marco Vountas, Benjamin Gaubert, Maria Dolores Andrés Hernández, Stephan Borrmann, Guy Brasseur, Bruna Holanda, Yugo Kanaya, Katharina Kaiser, Flora Kluge, Ovid Oktavian Krüger, Inga Labuhn, Michael Lichtenstern, Klaus Pfeilsticker, Mira Pöhlker, Hans Schlager, Johannes Schneider, Guillaume Siour, Basudev Swain, Paolo Tuccella, Kameswara S. Vinjamuri, Mihalis Vrekoussis, Benjamin Weyland, and John P. Burrows
EGUsphere, https://doi.org/10.5194/egusphere-2024-516, https://doi.org/10.5194/egusphere-2024-516, 2024
Preprint archived
Short summary
Short summary
This study assesses atmospheric composition using air quality models during aircraft campaigns in Europe and Asia, focusing on carbonaceous aerosols and trace gases. While carbon monoxide is well modeled, other pollutants have moderate to weak agreement with observations. Wind speed modeling is reliable for identifying pollution plumes, where models tend to overestimate concentrations. This highlights challenges in accurately modeling aerosol and trace gas composition, particularly in cities.
Adrien Deroubaix, Marco Vountas, Benjamin Gaubert, Maria Dolores Andrés Hernández, Stephan Borrmann, Guy Brasseur, Bruna Holanda, Yugo Kanaya, Katharina Kaiser, Flora Kluge, Ovid Oktavian Krüger, Inga Labuhn, Michael Lichtenstern, Klaus Pfeilsticker, Mira Pöhlker, Hans Schlager, Johannes Schneider, Guillaume Siour, Basudev Swain, Paolo Tuccella, Kameswara S. Vinjamuri, Mihalis Vrekoussis, Benjamin Weyland, and John P. Burrows
EGUsphere, https://doi.org/10.5194/egusphere-2024-521, https://doi.org/10.5194/egusphere-2024-521, 2024
Preprint archived
Short summary
Short summary
This study explores the proportional relationships between carbonaceous aerosols (black and organic carbon) and trace gases using airborne measurements from two campaigns in Europe and East Asia. Differences between regions were found, but air quality models struggled to reproduce them accurately. We show that these proportional relationships can help to constrain models and can be used to infer aerosol concentrations from satellite observations of trace gases, especially in urban areas.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
Short summary
Short summary
The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Jean-Maxime Bertrand, Frédérik Meleux, Anthony Ung, Gaël Descombes, and Augustin Colette
Atmos. Chem. Phys., 23, 5317–5333, https://doi.org/10.5194/acp-23-5317-2023, https://doi.org/10.5194/acp-23-5317-2023, 2023
Short summary
Short summary
Post-processing methods based on machine learning algorithms were applied to refine the forecasts of four key pollutants at monitoring sites across Europe. Performances show significant improvements compared to those of the deterministic model raw outputs. Taking advantage of the large modelling domain extension, an innovative
globalapproach is proposed to drastically reduce the period necessary to train the models and thus facilitate the implementation in an operational context.
Elsa Real, Florian Couvidat, Anthony Ung, Laure Malherbe, Blandine Raux, Alicia Gressent, and Augustin Colette
Earth Syst. Sci. Data, 14, 2419–2443, https://doi.org/10.5194/essd-14-2419-2022, https://doi.org/10.5194/essd-14-2419-2022, 2022
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This paper describes a 16-year (2000–2015) dataset of air pollution concentrations and air quality indicators over France combining background measurements and modeling. Hourly concentrations and regulatory indicators of NO2, O3, PM10 and PM2.5 are produced with 4 km spatial resolution. The overall dataset has been cross-validated and showed overall very good results. We hope that this open-access publication will facilitate further studies on the impacts of air pollution.
Augustin Colette, Laurence Rouïl, Frédérik Meleux, Vincent Lemaire, and Blandine Raux
Geosci. Model Dev., 15, 1441–1465, https://doi.org/10.5194/gmd-15-1441-2022, https://doi.org/10.5194/gmd-15-1441-2022, 2022
Short summary
Short summary
We introduce the first toolbox that allows exploration of the benefits of air pollution mitigation scenarios in the every-day air quality forecasts through a web interface. The toolbox relies on the joint use of chemistry-transport models (CTMs) and surrogate modelling techniques.
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