Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
doi:10.5194/acp-2016-1125
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
13 Jan 2017
Review status
A revision of this discussion paper was accepted for the journal Atmospheric Chemistry and Physics (ACP) and is expected to appear here in due course.
Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data
Nikolaos Siomos1, Dimitrios S. Balis1, Anastasia Poupkou1, Natalia Liora1, Spyridon Dimopoulos1, Dimitrios Melas1, Eleni Giannakaki2,5, Maria Filioglou1,2, Sara Basart3, and Anatoly Chaikovsky4 1Laboratory of atmospheric physics, Physics Department, Aristotle University of Thessaloniki, Greece
2Finnish Meteorological Institute, Atmospheric Research Centre of Eastern Finland, Kuopio, Finland
3Earth Sciences Department, Barcelona Supercomputing Center, BSC-CNS, Barcelona, Spain
4Institute of Physics, National Academy of Science, Minsk, Belarus
5Department of Environmental Physics and Meteorology, Faculty of Physics, University of Athens, Greece
Abstract. In this study we present an evaluation of the Comprehensive Air quality Model with extensions CAMx for Thessaloniki using radiometric and lidar data. The aerosol mass concentration profiles of CAMx are compared against the fine and coarse mode aerosol concentration profiles retrieved by the Lidar-Radiometer Inversion Code LIRIC. The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration in the boundary layer and the free troposphere The mean mass concentration comparison resulted in profiles within the same order of magnitude and similar vertical structure for the fine particles. The mean center of mass values are also close with a fractional bias of 24.8 %. On the opposite side, the coarse mode appears to be underestimated by the model below 4 km and overestimated above. In order to grasp the reasons behind the discrepancies, we investigate the effect of aerosol components that are not properly included in the model's emission inventory and boundary conditions such as the wildfires and the desert dust component. The identification of the cases that are affected by wildfires is performed using wind backward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory Model HYSPLIT in conjunction with satellite fire pixel data from the MODIS Terra and Aqua Global Monthly Fire Location Product MCD14ML. By removing those cases the correlation coefficient improves from 0.44 to 0.86 for the fine mode integrated mass in the boundary layer. The fine mode center of mass fractional bias also decreases to 16.9 %. Concerning the analysis on the desert dust component, the simulations from the updated version of the former Dust Regional Atmospheric Model called BSC-DREAM8b were deployed. When only the desert dust cases are taken into account, BSC-DREAM8b generally outperforms CAMx when compared with LIRIC, achieving a correlation of 0.91 and a fractional bias of −18.9 % for the integrated mass in the free troposphere and a correlation of 0.44 for the center of mass. CAMx, on the other hand, both underestimates and anti-correlates the integrated mass in the free troposphere. Consequently, the accuracy of CAMx is limited concerning the transported dust cases. We conclude that the performance of CAMx appears to be best for the fine particles, especially in the boundary layer. At the same time it systematically fails to successfully predict the coarse mode. Sources of particles not properly taken into account by the model are confirmed to negatively affect its performance.

Citation: Siomos, N., Balis, D. S., Poupkou, A., Liora, N., Dimopoulos, S., Melas, D., Giannakaki, E., Filioglou, M., Basart, S., and Chaikovsky, A.: Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-1125, in review, 2017.
Nikolaos Siomos et al.
Nikolaos Siomos et al.

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This study presents an evaluation of an air quality model using aerosol measurements from radiometric and lidar data at Thessaloniki, Greece. The aerosol mass concentration profiles of CAMx are compared against the fine and coarse mode aerosol concentration profiles retrieved by the Lidar-Radiometer Inversion Code LIRIC. The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration.
This study presents an evaluation of an air quality model using aerosol measurements from...
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