Articles | Volume 8, issue 2
https://doi.org/10.5194/gmd-8-381-2015
https://doi.org/10.5194/gmd-8-381-2015
Development and technical paper
 | 
23 Feb 2015
Development and technical paper |  | 23 Feb 2015

Modelling of primary aerosols in the chemical transport model MOCAGE: development and evaluation of aerosol physical parameterizations

B. Sič, L. El Amraoui, V. Marécal, B. Josse, J. Arteta, J. Guth, M. Joly, and P. D. Hamer

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Cited articles

Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–-1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003.
Alfaro, S. C., Gaudichet, A., Gomes, L., and Maillé, M.: Mineral aerosol production by wind erosion: Aerosol particle sizes and binding energies, Geophys. Res. Lett., 25, 991–994, 1998.
Andronache, C.: Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions, Atmos. Chem. Phys., 3, 131–143, https://doi.org/10.5194/acp-3-131-2003, 2003.
Andronache, C.: Diffusion and electric charge contributions to below-cloud wet removal of atmospheric ultra-fine aerosol particles, J. Aerosol Sci., 35, 1467–1482, 2004.
Andronache, C., Grönholm, T., Laakso, L., Phillips, V., and Venäläinen, A.: Scavenging of ultrafine particles by rainfall at a boreal site: observations and model estimations, Atmos. Chem. Phys., 6, 4739–4754, https://doi.org/10.5194/acp-6-4739-2006, 2006.
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