EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

High-resolution mineral dust modeling

Martina Klose1, Tabea Unser1, Sara Basart2, Oriol Jorba2, Francesco Benincasa2, Florian Pantillon3, Peter Knippertz1, and Carlos Pérez García-Pando2,4
Martina Klose et al.
  • 1Institute of Meteorology and Climate Research – Department Troposphere Research (IMK-TRO), Karlsruhe Institute of Technology (KIT), Germany
  • 2Barcelona Supercomputing Center (BSC), Spain
  • 3Laboratoire d’Aérologie, Université de Toulouse/CNRS/UPS, France
  • 4ICREA, Barcelona, Spain

Dust emissions are linked with wind forces through a non-linear relationship. As a result, small errors in modelled wind speed lead to large errors in modelled dust emission. Dust models usually show satisfactory behaviour when dust outbreaks are caused by synoptic-scale weather systems. In contrast, smaller-scale dust events, e.g. haboobs or dust devils, are often unresolved at typical model resolutions and are hence unrepresented, in particular in coarse-grid global models. Haboobs are among the most important meteorological dust injection processes in the Sahara and Sahel in summer, both in terms of cumulative duration and intensity. The lack of haboobs or other unrepresented dust events likely leads to biases in the amount, spatial distribution, and seasonal variability of global dust emission and loading.

Here we present results of a high-resolution (~ 3 km), convection-permitting simulation for the year 2012 over northern Africa and the Middle East with the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH). In contrast to previous studies, our simulations do not only contain meteorological variables at high resolution, but also include a full representation of the dust cycle. We assess the impact of resolution on the spatiotemporal dust patterns compared to observations and model simulations at coarser resolution. We also identify haboobs in the high-resolution simulation and assess their properties, such as occurrence frequency, duration, size/intensity, to investigate how realistically they are represented. 

How to cite: Klose, M., Unser, T., Basart, S., Jorba, O., Benincasa, F., Pantillon, F., Knippertz, P., and Pérez García-Pando, C.: High-resolution mineral dust modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9121,, 2022.


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