Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth
-
Published:2016-11-22
Issue:11
Volume:9
Page:5535-5554
-
ISSN:1867-8548
-
Container-title:Atmospheric Measurement Techniques
-
language:en
-
Short-container-title:Atmos. Meas. Tech.
Author:
Sič Bojan, El Amraoui Laaziz, Piacentini Andrea, Marécal VirginieORCID, Emili Emanuele, Cariolle Daniel, Prather MichaelORCID, Attié Jean-Luc
Abstract
Abstract. In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the spatially averaged 2-D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and to estimate improvements in a 3-D CTM assimilation run compared to a direct model run. Our assimilation system uses 3-D-FGAT (first guess at appropriate time) as an assimilation method and the total 3-D aerosol concentration as a control variable. In order to have an extensive validation dataset, we carried out our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l'Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2-D and 3-D) measured by in situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation increased the correlation (from 0.74 to 0.88), and reduced the bias (from 0.050 to 0.006) and the root mean square error in the AOD (from 0.12 to 0.07). When compared to the 3-D concentration data obtained by the in situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We also examine how the assimilation can influence the modelled aerosol vertical distribution. The results show that a 2-D continuous AOD assimilation can improve the 3-D vertical profile, as a result of differential horizontal transport of aerosols in the model.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference84 articles.
1. Andersson, E., Haseler, J., Undén, P., Courtier, P., Kelly, G., Vasiljevic, D., Brankovic, C., Gaffard, C., Hollingsworth, A., Jakob, C., Janssen, P., Klinker, E., Lanzinger, A., Miller, M., Rabier, F., Simmons, A., Strauss, B., Viterbo, P., Cardinali, C., and Thépaut, J.-N.: The ECMWF implementation of three-dimensional variational assimilation (3D-Var). III: Experimental results, Q. J. Roy. Meteor. Soc., 124, 1831–1860, https://doi.org/10.1002/qj.49712455004, 1998. 2. Attié, J.-L. et al.: Transport of Pollution and Air Quality experiment over the Mediterranean basin (TRAQA/ChArMEx campaign), in preparation, 2016. 3. Bechtold, P., Bazile, E., Guichard, F., Mascart, P., and Richard, E.: A mass-flux convection scheme for regional and global models, Q. J. Roy. Meteor. Soc., 127, 869–886, 2001. 4. Benedetti, A., Morcrette, J.-J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., and Suttie, M.: Aerosol analysis and forecast in the European centre for medium-range weather forecasts integrated forecast system: 2. Data assimilation, J. Geophys. Res.-Atmos., 114, D13205, https://doi.org/10.1029/2008JD011115, 2009. 5. Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and aerosols, in: Climate change 2013: The physical science basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge and New York, 571–657, 2013.
Cited by
27 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|