Articles | Volume 14, issue 7
Atmos. Chem. Phys., 14, 3511–3532, 2014
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: Megapoli-Paris 2009/2010 campaign
Atmos. Chem. Phys., 14, 3511–3532, 2014
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 et al.
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Cited
18 citations as recorded by crossref.
- Comparison of IASI water vapor retrieval with H<sub>2</sub>O-Raman lidar in the framework of the Mediterranean HyMeX and ChArMEx programs P. Chazette et al. 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. 10.5194/acp-15-5325-2015
- Aerosol data assimilation and forecasting experiments using aircraft and surface observations during CalNex Z. Zang et al. 10.3402/tellusb.v68.29812
- Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts C. Ma et al. 10.1007/s00376-017-7179-y
- Analysis of a warehouse fire smoke plume over Paris with an N<sub>2</sub> Raman lidar and an optical thickness matching algorithm X. Shang et al. 10.5194/amt-11-6525-2018
- Springtime major pollution events by aerosol over Paris Area: From a case study to a multiannual analysis P. Chazette & P. Royer 10.1002/2017JD026713
- Optical properties of an industrial fire observed with a ground based N2-Raman lidar over the Paris area X. Shang et al. 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. 10.1029/2019JD031465
- Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. 10.5194/acp-14-12031-2014
- Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
- AEROCOM and AEROSAT AAOD and SSA study – Part 1: Evaluation and intercomparison of satellite measurements N. Schutgens et al. 10.5194/acp-21-6895-2021
- Simulation of particle diversity and mixing state over Greater Paris: a model–measurement inter-comparison S. Zhu et al. 10.1039/C5FD00175G
- 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 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 PM<sub>2.5</sub> forecasts across China Y. Liang et al. 10.5194/gmd-13-6285-2020
- How much information do extinction and backscattering measurements contain about the chemical composition of atmospheric aerosol? M. Kahnert & E. Andersson 10.5194/acp-17-3423-2017
- Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. 10.5194/amt-13-4645-2020
- Lidar data assimilation method based on CRTM and WRF-Chem models and its application in PM2.5 forecasts in Beijing X. Cheng et al. 10.1016/j.scitotenv.2019.05.186
- Three-dimensional modeling of the mixing state of particles over Greater Paris S. Zhu et al. 10.1002/2015JD024241
18 citations as recorded by crossref.
- Comparison of IASI water vapor retrieval with H<sub>2</sub>O-Raman lidar in the framework of the Mediterranean HyMeX and ChArMEx programs P. Chazette et al. 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. 10.5194/acp-15-5325-2015
- Aerosol data assimilation and forecasting experiments using aircraft and surface observations during CalNex Z. Zang et al. 10.3402/tellusb.v68.29812
- Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts C. Ma et al. 10.1007/s00376-017-7179-y
- Analysis of a warehouse fire smoke plume over Paris with an N<sub>2</sub> Raman lidar and an optical thickness matching algorithm X. Shang et al. 10.5194/amt-11-6525-2018
- Springtime major pollution events by aerosol over Paris Area: From a case study to a multiannual analysis P. Chazette & P. Royer 10.1002/2017JD026713
- Optical properties of an industrial fire observed with a ground based N2-Raman lidar over the Paris area X. Shang et al. 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. 10.1029/2019JD031465
- Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. 10.5194/acp-14-12031-2014
- Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
- AEROCOM and AEROSAT AAOD and SSA study – Part 1: Evaluation and intercomparison of satellite measurements N. Schutgens et al. 10.5194/acp-21-6895-2021
- Simulation of particle diversity and mixing state over Greater Paris: a model–measurement inter-comparison S. Zhu et al. 10.1039/C5FD00175G
- 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 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 PM<sub>2.5</sub> forecasts across China Y. Liang et al. 10.5194/gmd-13-6285-2020
- How much information do extinction and backscattering measurements contain about the chemical composition of atmospheric aerosol? M. Kahnert & E. Andersson 10.5194/acp-17-3423-2017
- Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. 10.5194/amt-13-4645-2020
- Lidar data assimilation method based on CRTM and WRF-Chem models and its application in PM2.5 forecasts in Beijing X. Cheng et al. 10.1016/j.scitotenv.2019.05.186
- Three-dimensional modeling of the mixing state of particles over Greater Paris S. Zhu et al. 10.1002/2015JD024241
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