Articles | Volume 14, issue 7
https://doi.org/10.5194/acp-14-3511-2014
© Author(s) 2014. 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-14-3511-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
08 Apr 2014
Research article |
| 08 Apr 2014
Modelling and assimilation of lidar signals over Greater Paris during the MEGAPOLI summer campaign
Y. Wang
LSCE, Joint Laboratory CEA-CNRS – UMR8212, 91191 Gif-sur-Yvette, France
CEREA, Joint Laboratory École des Ponts ParisTech – EDF R & D, Université Paris-Est, 77455 Champs-sur-Marne, France
K. N. Sartelet
CEREA, Joint Laboratory École des Ponts ParisTech – EDF R & D, Université Paris-Est, 77455 Champs-sur-Marne, France
M. Bocquet
INRIA, Paris-Rocquencourt Research Centre, Le Chesnay, France
CEREA, Joint Laboratory École des Ponts ParisTech – EDF R & D, Université Paris-Est, 77455 Champs-sur-Marne, France
P. Chazette
LSCE, Joint Laboratory CEA-CNRS – UMR8212, 91191 Gif-sur-Yvette, France
Viewed
Total article views: 4,800 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 18 Oct 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,529 | 1,911 | 360 | 4,800 | 456 | 338 |
- HTML: 2,529
- PDF: 1,911
- XML: 360
- Total: 4,800
- BibTeX: 456
- EndNote: 338
Total article views: 3,904 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Apr 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,095 | 1,475 | 334 | 3,904 | 436 | 326 |
- HTML: 2,095
- PDF: 1,475
- XML: 334
- Total: 3,904
- BibTeX: 436
- EndNote: 326
Total article views: 896 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 18 Oct 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 434 | 436 | 26 | 896 | 20 | 12 |
- HTML: 434
- PDF: 436
- XML: 26
- Total: 896
- BibTeX: 20
- EndNote: 12
Cited
23 citations as recorded by crossref.
- Comparison of IASI water vapor retrieval with H2O-Raman lidar in the framework of the Mediterranean HyMeX and ChArMEx programs P. Chazette et al. https://doi.org/10.5194/acp-14-9583-2014
- Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models M. Bocquet et al. https://doi.org/10.5194/acp-15-5325-2015
- Aerosol data assimilation and forecasting experiments using aircraft and surface observations during CalNex Z. Zang et al. https://doi.org/10.3402/tellusb.v68.29812
- Optical properties of an industrial fire observed with a ground based N2-Raman lidar over the Paris area X. Shang et al. https://doi.org/10.1051/epjconf/201817604006
- Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. https://doi.org/10.1029/2019JD031465
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. https://doi.org/10.1016/j.jes.2022.04.012
- An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. https://doi.org/10.5194/gmd-15-3555-2022
- Information constraints in variational data assimilation M. Kahnert https://doi.org/10.1002/qj.3347
- Simulation of particle diversity and mixing state over Greater Paris: a model–measurement inter-comparison S. Zhu et al. https://doi.org/10.1039/C5FD00175G
- How much information do extinction and backscattering measurements contain about the chemical composition of atmospheric aerosol? M. Kahnert & E. Andersson https://doi.org/10.5194/acp-17-3423-2017
- A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations D. Wang et al. https://doi.org/10.5194/gmd-15-1821-2022
- Lidar data assimilation method based on CRTM and WRF-Chem models and its application in PM2.5 forecasts in Beijing X. Cheng et al. https://doi.org/10.1016/j.scitotenv.2019.05.186
- Three‐dimensional modeling of the mixing state of particles over Greater Paris S. Zhu et al. https://doi.org/10.1002/2015JD024241
- The December 2016 extreme weather and particulate matter pollution episode in the Paris region (France) G. Foret et al. https://doi.org/10.1016/j.atmosenv.2022.119386
- Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts C. Ma et al. https://doi.org/10.1007/s00376-017-7179-y
- Analysis of a warehouse fire smoke plume over Paris with an N2 Raman lidar and an optical thickness matching algorithm X. Shang et al. https://doi.org/10.5194/amt-11-6525-2018
- Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. https://doi.org/10.5194/acp-14-12031-2014
- Parametrization of Horizontal and Vertical Transfers for the Street-Network Model MUNICH Using the CFD Model Code_Saturne A. Maison et al. https://doi.org/10.3390/atmos13040527
- AEROCOM and AEROSAT AAOD and SSA study – Part 1: Evaluation and intercomparison of satellite measurements N. Schutgens et al. https://doi.org/10.5194/acp-21-6895-2021
- Raman lidar-derived aerosol optical properties and classification during the FENNEC experiment – coherence with CAMS data P. Chazette https://doi.org/10.5194/amt-19-4293-2026
- The Secondary Organic Aerosol Processor (SOAP v1.0) model: a unified model with different ranges of complexity based on the molecular surrogate approach F. Couvidat & K. Sartelet https://doi.org/10.5194/gmd-8-1111-2015
- Development of a three-dimensional variational assimilation system for lidar profile data based on a size-resolved aerosol model in WRF–Chem model v3.9.1 and its application in PM2.5 forecasts across China Y. Liang et al. https://doi.org/10.5194/gmd-13-6285-2020
- Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. https://doi.org/10.5194/amt-13-4645-2020
23 citations as recorded by crossref.
- Comparison of IASI water vapor retrieval with H2O-Raman lidar in the framework of the Mediterranean HyMeX and ChArMEx programs P. Chazette et al. https://doi.org/10.5194/acp-14-9583-2014
- Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models M. Bocquet et al. https://doi.org/10.5194/acp-15-5325-2015
- Aerosol data assimilation and forecasting experiments using aircraft and surface observations during CalNex Z. Zang et al. https://doi.org/10.3402/tellusb.v68.29812
- Optical properties of an industrial fire observed with a ground based N2-Raman lidar over the Paris area X. Shang et al. https://doi.org/10.1051/epjconf/201817604006
- Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. https://doi.org/10.1029/2019JD031465
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. https://doi.org/10.1016/j.jes.2022.04.012
- An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. https://doi.org/10.5194/gmd-15-3555-2022
- Information constraints in variational data assimilation M. Kahnert https://doi.org/10.1002/qj.3347
- Simulation of particle diversity and mixing state over Greater Paris: a model–measurement inter-comparison S. Zhu et al. https://doi.org/10.1039/C5FD00175G
- How much information do extinction and backscattering measurements contain about the chemical composition of atmospheric aerosol? M. Kahnert & E. Andersson https://doi.org/10.5194/acp-17-3423-2017
- A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations D. Wang et al. https://doi.org/10.5194/gmd-15-1821-2022
- Lidar data assimilation method based on CRTM and WRF-Chem models and its application in PM2.5 forecasts in Beijing X. Cheng et al. https://doi.org/10.1016/j.scitotenv.2019.05.186
- Three‐dimensional modeling of the mixing state of particles over Greater Paris S. Zhu et al. https://doi.org/10.1002/2015JD024241
- The December 2016 extreme weather and particulate matter pollution episode in the Paris region (France) G. Foret et al. https://doi.org/10.1016/j.atmosenv.2022.119386
- Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts C. Ma et al. https://doi.org/10.1007/s00376-017-7179-y
- Analysis of a warehouse fire smoke plume over Paris with an N2 Raman lidar and an optical thickness matching algorithm X. Shang et al. https://doi.org/10.5194/amt-11-6525-2018
- Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. https://doi.org/10.5194/acp-14-12031-2014
- Parametrization of Horizontal and Vertical Transfers for the Street-Network Model MUNICH Using the CFD Model Code_Saturne A. Maison et al. https://doi.org/10.3390/atmos13040527
- AEROCOM and AEROSAT AAOD and SSA study – Part 1: Evaluation and intercomparison of satellite measurements N. Schutgens et al. https://doi.org/10.5194/acp-21-6895-2021
- Raman lidar-derived aerosol optical properties and classification during the FENNEC experiment – coherence with CAMS data P. Chazette https://doi.org/10.5194/amt-19-4293-2026
- The Secondary Organic Aerosol Processor (SOAP v1.0) model: a unified model with different ranges of complexity based on the molecular surrogate approach F. Couvidat & K. Sartelet https://doi.org/10.5194/gmd-8-1111-2015
- Development of a three-dimensional variational assimilation system for lidar profile data based on a size-resolved aerosol model in WRF–Chem model v3.9.1 and its application in PM2.5 forecasts across China Y. Liang et al. https://doi.org/10.5194/gmd-13-6285-2020
- Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. https://doi.org/10.5194/amt-13-4645-2020
Saved (final revised paper)
Latest update: 21 Oct 2026
Special issue
Altmetrics
Final-revised paper
Preprint