As operational support to define the Clouds-Atmospheric Dynamics-Dust Interactions in West Africa (CADDIWA) field campaign which took place in the Cape Verde area, the coupled regional model WRF-CHIMERE is deployed in forecast mode during the summer 2021. The simulation domain covers West Africa and the eastern Atlantic and allows the modeling of dust emissions and their transport to the Atlantic. On this route, we find Cape Verde, which was used as a base for measurements during the CADDIWA campaign. Meteorological variables and mineral dust concentrations are forecasted on a horizontal grid with a 30 km resolution and from the surface to 200 hPa. For a given day D, simulations are initialized from D-1 analyses and run for 4 d until D+4, yielding up to six available simulations on a given day. For each day, we thus have six different calculations, with better precision expected the closer we get to the analysis (lead D-1). In this study, a quantification of the forecast variability of wind, temperature, precipitation and mineral dust concentrations according to the modeled lead is presented. It is shown that the forecast quality does not decrease with time, and the high variability observed on some days for some variables (wind, temperature) does not explain the behavior of other dependent and downwind variables (mineral dust concentrations). A new method is also tested to create an ensemble without perturbing input data, but considering six forecast leads available for each date as members of an ensemble forecast. It has been shown that this new forecast based on this ensemble is able to give better results for two AErosol RObotic NETwork (AERONET) stations than the four available for aerosol optical depth observations. This could open the door to further testing with more complex operational systems.

Mineral dust emissions mainly depend on soil erodibility and near-surface wind speeds. During biomass burning episodes, pyroconvection locally generates high surface wind speed and non-desert surfaces (such as forest and shrubs) are partially replaced by barren soil. These effects may induce additional mineral dust emission. However, they are generally not taken into account in chemistry-transport models since the biomass burning and mineral dust emissions are usually considered as independent processes. This may lead to an underestimation of the mineral dust emissions and therefore of the transported concentrations. In this study, this link is added in the CHIMERE chemistry-transport model. The summer of 2021 is modeled over Europe using the coupled WRF-CHIMERE system. Simulations with and without the link between emission processes are performed. Results are compared to observations such as surface measurements of ozone and particulate matter by EEA and aerosol optical depth by AERONET. With more emitted mineral dust, an effect is found on the whole meteorological and chemical system: wind, temperature, cloud, gas (such as ozone with a few ppb changes) and aerosol concentrations are changed. The effect does not appear to be very important but significant enough to have to be taken into account in future modeling.

Modelling of mineral dust is often done using one single mean species. But for biogeochemical studies, it could be useful to access to a more detailed information on differentiated mineral species and the associated chemical composition. Differentiating between mineral species would also induce different optical properties and densities and then different radiative impact, transport and deposition. In this study, the mineralogical differentiation is implemented in the CHIMERE regional chemistry-transport model, by using global databases. The results show that this implementation does not change the results much in terms of aerosol optical depth, surface concentrations and deposition fluxes. But the information on mineralogy, with a high spatial (a few kilometres) and temporal (1 h) resolution, is now available and is ready to be used for future biogeochemical studies.

The modeling of mineral dust emissons requires a fine 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 ecompassing the northern part of Africa and Europe and for the period of 1st January to 1st May 2012. The simulations’s results are compared to PM10 surface concentations and AERONET Aerosol Optical Depth and Aerosol Size Distribution. We show that with the orography variance, the simulations results are closr to the ones without, showing this additional variability is not the main driver of possible errors in mineral dust modeling.

Dust production models (DPM) used to estimate vertical fluxes of mineral dust aerosols over arid regions need accurate data on soil and surface properties. The Laboratoire Inter-Universitaire des Systemes Atmospheriques (LISA) data set was developed for Northern Africa, the Middle East, and East Asia. This regional data set was built through dedicated field campaigns and include, among others, the aerodynamic roughness length, the smooth roughness length of the erodible fraction of the surface, and the dry (undisturbed) soil size distribution. Recently, satellite-derived roughness length and high-resolution soil texture data sets at the global scale have emerged and provide the opportunity for the use of advanced schemes in global models. This paper analyzes the behavior of the ERS satellite-derived global roughness length and the State Soil Geographic data base-Food and Agriculture Organization of the United Nations (STATSGO-FAO) soil texture data set (based on wet techniques) using an advanced DPM in comparison to the LISA data set over Northern Africa and the Middle East. We explore the sensitivity of the drag partition scheme (a critical component of the DPM) and of the dust vertical fluxes (intensity and spatial patterns) to the roughness length and soil texture data sets. We also compare the use of the drag partition scheme to a widely used preferential source approach in global models. Idealized experiments with prescribed wind speeds show that the ERS and STATSGO-FAO data sets provide realistic spatial patterns of dust emission and friction velocity thresholds in the region. Finally, we evaluate a dust transport model for the period of March to July 2011 with observed aerosol optical depths from Aerosol Robotic Network sites. Results show that ERS and STATSGO-FAO provide realistic simulations in the region.

In February 2004, a spectacular dust event was observed in the south of France. Associated with huge particulate matter deposition, unusual 137Cs concentrations were found in samples. Using the transport model CHIMERE-DUST, we first show that these dust aerosols came from North Africa. More precisely, the question is whether this sudden increase of measured 137Cs concentrations was due to a huge amount of dust over a large region (with an usual radionuclide content) or due to an import of more concentrated air masses over a limited area. This question is connected to the open debate about the contribution of 137Cs concentrations in Europe from ‘‘Gerboise’’ sites, where former French nuclear tests in the 1960s were performed. With the model in scenario mode, this study attempts to track down 137Cs concentrations recorded in the south of France. To quantify the origin and percentage of dust originating from North Africa to the south of France, three simulations are performed: (1) with the complete dust emissions inventory of Africa, (2) with only emissions in the eastern Maghreb, and (3) only considering the Gerboise sites. It is showed that the majority (80%) of the dust was coming from eastern Maghreb, but only 0.7% of the African emissions were from Gerboise, leading to 1–5% of the concentrations recorded in the south of France for the day of the peak.

The predictability of northern Africa dust events is assessed using daily numerical forecast simulations for the next 3 days. The dust concentration fields, modeled with the CHIMERE-DUST model, were first evaluated by comparison with both Aerosol Robotic Network (AERONET) surface data and Ozone Monitoring Instrument (OMI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite measurements. The accuracy and spread between measurements and simulations are discussed for the first short observation period of the African Monsoon Multidisciplinary Analysis (AMMA) experiment in western Africa, between January and March 2006. The predictability of dust events was then estimated by comparing model results for different leads in a forecast mode. The model performance was evaluated with respect to its capability to forecast the surface wind speed, which is the key process for dust emission, and the transport of mineral dust near source regions and toward remote areas. It is shown that forecast emissions can vary up to 80% (close to the sources) but that the variability on forecasted dust concentrations and optical thicknesses do not exceed 40% and 20%.

The impact of atmospheric aerosol concentrations on climate remains uncertain. This is due to the lack of understanding of the physical processes involved and also to uncertainties on the data used to model them. In the case of modeled dust emissions, the key parameters are the surface wind speed and the soil characteristics. Dust emissions are issued from inhomogeneous land surfaces and depend on local changes in wind speed. Nevertheless, their representation in models is crude since the local variability of the emission is not taken into account due to the model resolution. This simplified physical representation is problematic since the first emission process, saltation, is triggered by a threshold on the wind speed value. For most model studies, the global meteorological fields used are issued either from NCEP or ECMWF models, but the impact of the forcing was never quantified. In this study, we examine the emission fluxes variability based on the selected meteorological data set. The difference between the two emission fluxes can reach a factor of 3. This bias is not systematic and is highly variable on the timescale of an hour within different areas over western Africa. The impact of the sandblasting scheme is also studied; the variation arising by using two different schemes do not exceed 20%.

Evaluating the impacts of atmospheric dust on marine ecosystems and climate requires the use of three-dimensional transport models including a size-resolved bins scheme to describe the evolution of the particle size distribution. Recently, Foreˆt et al. (2006) proposed an alternative size bins scheme to better account for the physical size-dependent processes such as dry deposition. This paper evaluates the benefit of using this new bin scheme in three-dimensional transport models. This is achieved by performing a one-and-a-half month simulation with the CHIMERE-DUST model forced by the Mesoscale Model, Version 5 (MM5)/National Center for Environmental Prediction (NCEP) analysis fields, for an area covering the northern Atlantic Sea and the western Africa. Compared to a reference run performed using a large number of size bins (40), our results show that the size bins scheme proposed by Foreˆt et al. (2006) reduces at least by a factor of 2 the numerical errors on the simulated concentrations compared to the classical isolog bins scheme for the same number of size bins. However, with this new bins scheme requiring to define the bins according to a dry deposition velocity corresponding to a given friction velocity, we examine the errors associated to this constraint.

Atmospheric dust concentrations are very sensitive to the dust surface emissions that are mainly controlled by saltation and sandblasting processes. Thus, a correct modeling of concentrations directly depends on mass flux parameterization accuracy. In 2001, Alfaro and Gomes proposed a whole set of parameterizations linking the dust flux to surface wind speed and soil characteristics. Their formulation is based on the integration of elementary fluxes, discretized along a soil size distribution. But, because the sandblasting is a threshold process, this discretization must be as fine as possible when the threshold acts. And because this threshold depends on dynamic parameters, it is necessary to always integrate fluxes with a high resolution. This leads to large numerical simulations. In this paper it is shown that it is possible to estimate fluxes with a good accuracy by adding equations that are dedicated to better describing the sensitive parts of the emission scheme.