Dust evolution: Going beyond the empirical

A key element when modeling dust in any astrophysical environment is a self-consistent treatment of the evolution of the dust material properties (size distribution, chemical composition and structure) as they react to and adjust to the local radiation field intensity and hardness and to the gas density and dynamics. The best way to achieve this goal is to anchore as many model parameters as possible to laboratory data. In this paper, I present two examples to illustrate how outstanding questions in dust modeling have been/are being moved forward by recent advances in laboratory astrophysics and what laboratory data are still needed to further advance dust evolution models.

Intercomparisons of some dust models over West Asia

Evaluation and assessment of dust model results is of primary importance to get a better understanding of the models' performance, and therefore, enhancing the models' set up and structure. Besides some SDS-WAS dust models, two other high resolution WRF-Chem runs have been carried out for two dust episodes over the West Asia with alterations in the soil erodibility fields as one of the primary criteria of dust sources. The main aim of this article was to investigate the high resolution WRF-Chem modeling with the default and altered soil erosion, against the WMO SDS-WAS models. In this paper we investigated the application of WRF-Chem dust modeling for the region of interest (Iran), which cannot be seen entirely by the SDS-WAS models' domains. Comparisons of modelled dust surface concentrations with ground based measurements on 8 air quality stations show that the high resolution WRF-Chem could more or less lead to better predictions. For some cases, the results of the high resolution WRF-Chem unexpectedly presented a declined performance, which indicate that the improvements in the horizontal resolution and soil erodibility could not always lead to improved dust predictions, and more factors such as the model set-up and structure should be considered.

Modeling of Mineral Dust Emissions with a Weibull Wind Speed Distribution Including Subgrid-Scale Orography Variance

The modeling of mineral dust emissions requires an extensive knowledge of the wind speed close to the surface. In regional and global models, Weibull distributions are often used to better represent the subgrid-scale variability of the wind speed. This distribution mainly depends on a k parameter, itself currently parameterized as a function of the wind speed value. In this study we propose to add the potential impact of the orography variance in the wind speed distribution by changing the k parameter value. Academic test cases are designed to estimate the parameters of the scheme. A realistic test case is performed over a large domain encompassing the northern part of Africa and Europe and for the period 1 January–1 May 2012. The results of the simulations are compared to particulate matter (PM10) surface concentrations and Aerosol Robotic Network (AERONET) aerosol optical depth and aerosol size distribution. We show that with the orography variance, the simulation results are closer to the ones without variance, showing that this additional variability is not the main driver of possible errors in mineral dust modeling.