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Dusty cirrus clouds are extended optically thick cirrocumulus decks that occur during strong mineral dust events. So far they have mostly been documented over Europe associated with dust-infused baroclinic storms. Since today's global numerical weather prediction models neither predict mineral dust distributions nor consider the interaction of dust with cloud microphysics, they cannot simulate this phenomenon. We postulate that the dusty cirrus forms through a mixing instability of moist clean air with drier dusty air. A corresponding sub-grid parameterization is suggested and tested in the ICOsahedral Nonhydrostatic model with Aerosol and Reactive Trace gases (ICON-ART). Only with the help of this parameterization is ICON-ART able to simulate the formation of the dusty cirrus, which leads to substantial improvements in cloud cover and radiative fluxes compared to simulations without this parameterization. A statistical evaluation over six Saharan dust events with and without observed dusty cirrus shows robust improvements in cloud and radiation scores. The ability to simulate dusty cirrus formation removes the linear dependency on mineral dust aerosol optical depth from the bias of the radiative fluxes. For the six Saharan dust episodes investigated in this study, the formation of dusty cirrus clouds is the dominant aerosol–cloud–radiation effect of mineral dust over Europe.

In June 2019, the Raikoke volcano, Kuril Islands, emitted 0.4–1.8×109 kg of very fine ash and 1–2×109 kg of SO2 up to 14 km into the atmosphere. The eruption was characterized by several eruption phases of different duration and height summing up to a total eruption length of about 5.5 h. Resolving such complex eruption dynamics is required for precise volcanic plume dispersion forecasts. To address this issue, we coupled the atmospheric model system ICON-ART (ICOsahedral Nonhydrostatic with the Aerosols and Reactive Trace gases module) with the 1D plume model FPlume to calculate the eruption source parameters (ESPs) online. The main inputs are the plume heights for the different eruption phases that are geometrically derived from satellite data. An empirical relationship is used to derive the amount of very fine ash (particles µm), which is relevant for long-range transport in the atmosphere. On the first day after the onset of the eruption, the modeled ash loading agrees very well with the ash loading estimated from AHI (Advanced Himawari Imager) observations due to the resolution of the eruption phases and the online treatment of the ESPs. In later hours, aerosol dynamical processes (nucleation, condensation, and coagulation) explain the loss of ash in the atmosphere in agreement with the observations. However, a direct comparison is partly hampered by water and ice clouds overlapping the ash cloud in the observations. We compared 6-hourly means of model and AHI data with respect to the structure, amplitude, and location (SAL method) to further validate the simulated dispersion of SO2 and ash. In the beginning, the structure and amplitude values for SO2 differed largely because the dense ash cloud leads to an underestimation of the SO2 amount in the satellite data. On the second and third day, the SAL values are close to zero for all parameters (except for the structure value of ash), indicating a very good agreement of the model and observations. Furthermore, we found a separation of the ash and SO2 plume after 1 d due to particle sedimentation, chemistry, and aerosol–radiation interaction. The results confirm that coupling the atmospheric model system and plume model enables detailed treatment of the plume dynamics (phases and ESPs) and leads to significant improvement of the ash and SO2 dispersion forecast. This approach can benefit the operational forecast of ash and SO2 especially in the case of complex and noncontinuous volcanic eruptions like that of Raikoke in 2019.

Urban aerosol pollution was analyzed over the Moscow megacity region using the COSMO-ART (COSMO – COnsortium for Small-scale MOdelling, ART – Aerosols and Reactive Trace gases) online coupled mesoscale model system and intensive measurement campaigns at the Moscow State University Meteorological Observatory (MSU MO, 55.707∘ N, 37.522∘ E) during the April–May period in 2018 and 2019. We analyzed mass concentrations of particulate matter with diameters smaller than 10 µm (PM10), black carbon (BC) and aerosol gas precursors (NOx, SO2, CHx) as well as columnar aerosol parameters for fine and coarse modes together with different meteorological parameters, including an index characterizing the intensity of particle dispersion (IPD). Both model and experimental datasets have shown a statistically significant linear correlation of BC with NO2 and PM10 mass concentrations, which indicates mostly common sources of emissions of these substances. There was a pronounced increase in the BC/PM10 ratio from 0.7 % to 5.9 %, with the decrease in the IPD index related to the amplification of the atmospheric stratification. We also found an inverse dependence between the BC/PM10 ratio and columnar single-scattering albedo (SSA) for the intense air mixing conditions. This dependence together with the obtained negative correlation between wind speed and BC/PM10 may serve as an indicator of changes in the absorbing properties of the atmosphere due to meteorological factors. On average, the relatively low BC / PM10 ratio (for urban regions) of 4.7 % is the cause of the observed relatively high SSA = 0.94 in Moscow. Using long-term parallel aerosol optical depth (AOD) measurements over the 2006–2020 period at the MSU MO and under upwind clean background conditions at Zvenigorod Scientific Station (ZSS) of the IAP RAS (55.7∘ N, 36.8∘ E), we estimated the urban component of AOD (AODurb) and some other parameters as the differences at these sites. The annual mean AODurb at 550 nm was about 0.021 with more than 85 % of the fine aerosol mode. The comparisons between AODurb obtained from the model and measurements during this experiment have revealed a similar level of aerosol pollution of about AODurb=0.015–0.019, which comprised 15 %–19 % of the total AOD at 550 nm. The urban component of PM10 (PM10urb) was about 16 µg m−3 according to the measurements and 6 µg m−3 according to the COSMO-ART simulations. We obtained a pronounced diurnal cycle of PM10urb and urban BC (BCurb) as well as their strong correlation with the IPDs. With the IPD index change from 3 to 1 at night, there was about a 4 times increase in PM10urb (up to 30–40 µg m−3) and a 3 times increase in BCurb (up to 3–3.5 µg m−3). At the same time, no pronounced daily cycle was found for the columnar urban aerosol component (AODurb), although there was a slight increase in model AODurb at night.

Between June and September large amounts of biomass burning aerosol are released into the atmosphere from agricultural fires in central and southern Africa. Recent studies have suggested that this plume is carried westward over the Atlantic Ocean at altitudes between 2 and 4 km and then northward with the monsoon flow at low levels to increase the atmospheric aerosol load over coastal cities in southern West Africa (SWA), thereby exacerbating air pollution problems. However, the processes by which these fire emissions are transported into the planetary boundary layer (PBL) are still unclear. One potential factor is the large-scale subsidence related to the southern branch of the monsoon Hadley cell over the tropical Atlantic. Here we use convection-permitting model simulations with COSMO-ART to investigate for the first time the contribution of downward mixing induced by clouds, a process we refer to as downward cloud venting in contrast to the more common process of upward transport from a polluted PBL. Based on a monthly climatology, model simulations compare satisfactory with wind fields from reanalysis data, cloud observations, and satellite-retrieved carbon monoxide (CO) mixing ratio. For a case study on 2 July 2016, modelled clouds and rainfall show overall good agreement with Spinning Enhanced Visible and InfraRed Imager (SEVIRI) cloud products and Global Precipitation Measurement Integrated Multi-satellitE Retrievals (GPM-IMERG) rainfall estimates. However, there is a tendency for the model to produce too much clouds and rainfall over the Gulf of Guinea. Using the CO dispersion as an indicator for the biomass burning plume, we identify individual mixing events south of the coast of Côte d'Ivoire due to midlevel convective clouds injecting parts of the biomass burning plume into the PBL. Idealized tracer experiments suggest that around 15 % of the CO mass from the 2–4 km layer is mixed below 1 km within 2 d over the Gulf of Guinea and that the magnitude of the cloud venting is modulated by the underlying sea surface temperatures. There is even stronger vertical mixing when the biomass burning plume reaches land due to daytime heating and a deeper PBL. In that case, the long-range-transported biomass burning plume is mixed with local anthropogenic emissions. Future work should provide more robust statistics on the downward cloud venting effect over the Gulf of Guinea and include aspects of aerosol deposition.

This document describes the conclusions of theEU-funded project Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA)directlyrelevant to operational meteorological services.DACCIWAproducedthe most comprehensive observational dataset of the atmosphere overdensely populatedsouthern West Africa to date and used this dataset to fosterour understanding of atmosphericprocesses, and to evaluate dynamicalmodels and satellite data. With this document DACCIWA aims to help improve atmospheric predictions across time-scales, which are important for thedevelopment of greaterresilience of the West African population tohazardous weather and climate change.&nbsp