Articles | Volume 15, issue 14
Atmos. Chem. Phys., 15, 7897–7911, 2015
https://doi.org/10.5194/acp-15-7897-2015

Special issue: CHemistry and AeRosols Mediterranean EXperiments (ChArMEx)...

Atmos. Chem. Phys., 15, 7897–7911, 2015
https://doi.org/10.5194/acp-15-7897-2015

Research article 17 Jul 2015

Research article | 17 Jul 2015

Aerosol forecast over the Mediterranean area during July 2013 (ADRIMED/CHARMEX)

L. Menut et al.

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Cited articles

Bessagnet, B., Hodzic, A., Vautard, R., Beekmann, M., Cheinet, S., Honoré, C., Liousse, C., and Rouil, L.: Aerosol modeling with CHIMERE: preliminary evaluation at the continental scale, Atmos. Environ., 38, 2803–2817, 2004.
Borrego, C., Monteiro, A., Pay, M., Ribeiro, I., Miranda, A., Basart, S., and Baldasano, J.: How bias-correction can improve air quality forecasts over Portugal, Atmos. Environ., 45, 6629–6641, https://doi.org/10.1016/j.atmosenv.2011.09.006, 2011.
Carslaw, K. S., Boucher, O., Spracklen, D. V., Mann, G. W., Rae, J. G. L., Woodward, S., and Kulmala, M.: A review of natural aerosol interactions and feedbacks within the Earth system, Atmos. Chem. Phys., 10, 1701–1737, https://doi.org/10.5194/acp-10-1701-2010, 2010.
Chen, F. and Dudhia, J.: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system, Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569–585, 2001.
Curier, R., Timmermans, R., Calabretta-Jongen, S., Eskes, H., Segers, A., Swart, D., and Schaap, M.: Improving ozone forecasts over Europe by synergistic use of the LOTOS-EUROS chemical transport model and in-situ measurements, Atmos. Environ., 60, 217–226, https://doi.org/10.1016/j.atmosenv.2012.06.017, 2012.
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The atmospheric composition was extensively studied in the European Mediterranean region and during summer 2013 within the framework of the ADRIMED project. During the campaign experiment, the WRF and CHIMERE models were used in forecast mode in order to help scientists to decide whether intensive observation periods should be triggered or not. This study quantifies the origin of the forecast error by comparing several forecast leads to the corresponding measurements.
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