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Aeolian dust, the most dominant atmospheric aerosol by mass, influences the weather and climate directly through absorbing and scattering the radiation. Particle size distribution (PSD) controls the magnitude of these impacts through modulating the dust residence time in the atmosphere and optical properties. Although the dust PSD varies during the atmospheric transport, current models usually neglect the effect of these variations on dust optical properties. This study investigates the impact of variable PSD on dust optical properties and radiative impacts using the next-generation atmospheric modeling system ICON-ART (ICOsahedral Nonhydrostatic with Aerosols and Reactive Trace gases). Two sets of numerical experiments are conducted assuming fixed and variable PSD. A parameterization is developed to account for the effect of variable PSD on dust optical properties in the model. This parameterization is then implemented in ICON-ART to simulate a period of 1 month on a global grid with 80 km horizontal resolution. Results show that the consideration of a variable PSD increases the dust AOD. However, the magnitude of the changes depends on the dominant size modes. Although the optical properties of the fine mode show the highest sensitivity to the variable PSD, the median diameter of this mode hardly changes during transport. Thus, the new parametrization does not have a significant impact on AOD where fine mode is dominant. In contrast, when coarse mode is prevailing, the increase of AOD is more pronounced. This makes the surface slightly warmer (+0.2 K) in the source regions. [ABSTRACT FROM AUTHOR]

Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operational numerical weather prediction models account for aerosol direct effects by using climatological mean concentrations and neglect indirect effects. This simplification may lead to shortcomings in model forecasts during outbreaks of Saharan dust towards Europe, when climatological mean dust concentrations deviate strongly from actual concentrations. This study investigates errors in model analyses and short‐range forecasts during such events. We investigate a pronounced dust event in March 2021 using the pre‐operational ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON‐ART) with prognostic calculation of dust and the operational European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) model, which deploys a dust climatology. We compare model analysis and forecast with measurements from satellite and in situ instruments. We find that inclusion of prognostic aerosol and direct radiative effects from dust improves forecasts of surface radiation during clear‐sky conditions. However, dust‐induced cirrus clouds are strongly underestimated, highlighting the importance of representing indirect effects adequately. These findings are corroborated by systematic quantification of forecast errors against satellite measurements. For this we construct an event catalogue with 49 dust days over Central Europe between January 2018 and March 2022. We classify model cells by simulated and observed cloudiness and simulated dustiness in the total atmospheric column. We find significant overestimations of brightness temperature for cases with dust compared with cases without dust. For surface shortwave radiation, we find median overestimations of 6.2% during cloudy conditions with dust optical depth greater than 0.1, however these are not significant compared with cloudy conditions without dust. Our findings show that the pre‐operational ICON‐ART and the operational IFS model still do not reproduce cloudiness adequately during events with Saharan dust over Central Europe. Missing implementations of prognostic dust, particularly of indirect effects on cloud formation, lead to significant underestimations of cloudiness and potentially overestimations of surface radiation. [ABSTRACT FROM AUTHOR]

The evolution and the properties of a Saharan dust plume were studied near the city of Karlsruhe in south-west Germany (8.4298 °E, 49.0953 °N) from April 7 to 9, 2018 combining a scanning lidar (90°, 30°), a vertically pointing lidar (90°), a sun photometer, and the transport model ICOsahedral Nonhydrostatic model - Aerosols and Reactive Trace gases (ICON-ART). The lidar measurements show that the dust particles had backscatter coefficients of 0.86 ± 0.14 Mm-1 sr -1, an extinction coefficient of 40 ± 0.8 Mm-1, a lidar ratio of 46 ± 5 sr, and a particle depolarization ratio of 0.33 ± 0.07. These values are in good agreement with those obtained in previous studies of Saharan dust plumes in Western Europe. Compared to the remote sensing measurements, the model simulation predicts the plume arrival time, its layer height, and structure very well but overestimates the backscatter coefficient. In this manuscript, we discuss the complementarity and advantages of the different measurement methods as well as model simulations to predict Saharan dust plumes. Main conclusions are that the ICON-ART model can predict the structure of Saharan dust plumes very well but overestimates the backscatter coefficients by a factor of 2.2 ± 0.16 at 355 nm and underestimates the aerosol optical depth (AOD) by a factor of 1.5 ± 0.11 at 340 nm for this Saharan dust plume event. Employing a scanning aerosol lidar allows determining backscatter coefficient, particle depolarization ratio and especially lidar ratio of Saharan dust both for daytime and nighttime independently. Combining lidar with sun photometer data allows constraining aerosol optical depth in different ways and determining column integrated lidar ratios. These comprehensive datasets allow for a better understanding of Saharan dust plumes in Western Europe. [ABSTRACT FROM AUTHOR]