Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4287-2020
https://doi.org/10.5194/gmd-13-4287-2020
Model evaluation paper
 | 
16 Sep 2020
Model evaluation paper |  | 16 Sep 2020

Modelling mineral dust emissions and atmospheric dispersion with MADE3 in EMAC v2.54

Christof G. Beer, Johannes Hendricks, Mattia Righi, Bernd Heinold, Ina Tegen, Silke Groß, Daniel Sauer, Adrian Walser, and Bernadett Weinzierl

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Cited articles

Aquila, V., Hendricks, J., Lauer, A., Riemer, N., Vogel, H., Baumgardner, D., Minikin, A., Petzold, A., Schwarz, J. P., Spackman, J. R., Weinzierl, B., Righi, M., and Dall'Amico, M.: MADE-in: a new aerosol microphysics submodel for global simulation of insoluble particles and their mixing state, Geosci. Model Dev., 4, 325–355, https://doi.org/10.5194/gmd-4-325-2011, 2011. a, b, c, d
Astitha, M., Lelieveld, J., Abdel Kader, M., Pozzer, A., and de Meij, A.: Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties, Atmos. Chem. Phys., 12, 11057–11083, https://doi.org/10.5194/acp-12-11057-2012, 2012. a
Balkanski, Y., Schulz, M., Claquin, T., Moulin, C., and Ginoux, P.: Global emissions of mineral aerosol: formulation and validation using satellite imagery, in: Emissions of Atmospheric Trace Compounds, Springer, 18, 239–267, https://doi.org/10.1007/978-1-4020-2167-1_6, 2004. a
Banks, J. R., Brindley, H. E., Stenchikov, G., and Schepanski, K.: Satellite retrievals of dust aerosol over the Red Sea and the Persian Gulf (2005–2015), Atmos. Chem. Phys., 17, 3987–4003, https://doi.org/10.5194/acp-17-3987-2017, 2017. a
Baumgardner, D., Jonsson, H., Dawson, W., O'Connor, D., and Newton, R.: The cloud, aerosol and precipitation spectrometer: a new instrument for cloud investigations, Atmos. Res., 59–60, 251–264, https://doi.org/10.1016/s0169-8095(01)00119-3, 2001. a
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Short summary
Mineral dust aerosol plays an important role in the climate system. Previously, dust emissions have often been represented in global models by prescribed monthly-mean emission fields representative of a specific year. We now apply an online calculation of wind-driven dust emissions. This results in an improved agreement with observations, due to a better representation of the highly variable dust emissions. Increasing the model resolution led to an additional performance gain.