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European Geosciences Union, Geoscientific Model Development, 3(17), p. 1271-1295, 2024

DOI: 10.5194/gmd-17-1271-2024

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The implementation of dust mineralogy in COSMO5.05-MUSCAT

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Mineral dust aerosols are composed of a complex assemblage of various minerals depending on the region in which they originated. Given the different mineral composition of desert dust aerosols, different physicochemical properties and therefore varying climate effects are expected. Despite the known regional variations in mineral composition, chemical transport models typically assume that mineral dust aerosols have uniform composition. This study adds, for the first time, mineralogical information to the mineral dust emission scheme used in the chemical transport model COSMO–MUSCAT. We provide a detailed description of the implementation of the mineralogical database, GMINER (Nickovic et al., 2012), together with a specific set of physical parameterizations in the model's mineral dust emission module, which led to a general improvement of the model performance when comparing the simulated mineral dust aerosols with measurements over the Sahara region for January–February 2022. The simulated mineral dust aerosol vertical distribution is tested by a comparison with aerosol lidar measurements from the lidar system PollyXT, located at Cape Verde. For a lofted mineral dust aerosol layer on 2 February at 05:00 UTC the lidar retrievals yield a dust mass concentration peak of 156 µg m−3, while the model calculates the mineral dust peak at 136 µg m−3. The results highlight the possibility of using the model with resolved mineral dust composition for interpretation of the lidar measurements since a higher absorption in the UV–Vis wavelengths is correlated with particles having a higher hematite content. Additionally, the comparison with in situ mineralogical measurements of dust aerosol particles shows that more of them are needed for model evaluation.