We used MODIS observations to retrieve number concentration of cloud droplets (N_d) at cloud lower boundary during spring 2018–2020 for the Moscow region. Looking through the similar synoptic situations of the northern clear air advection, we obtained N_d within the limits of 200–300 cm⁻³. During the lockdown period, with similar northern advection conditions, the reduction of N_d on 40–50 cm⁻³ (or 14–16%), with the increase in droplet effective radius by 8 ± 1% and cloud optical thickness reduction by 5 ± 2%, was observed in contrast to the values in typical conditions in 2018–2019. We used these values for setting up corresponding parameters in numerical simulations with the COSMO-Ru model. According to the numerical experiments, we showed that the observed reduction in cloud droplet concentration by 50 cm⁻³ provides a 5–9 W/m² (or 9–11%) increase in global irradiance at ground in overcast cloud conditions with LWP = 200–400 g/m².

The monograph is devoted to the study of atmospheric aerosol and its dynamics in the urban environment of Moscow megacity. Based on the AeroRadCity 2018-2019 complex experiment, composed of measurement campaign and numerical experiments using the COSMO-ART chemical transport model, a number of new results were obtained, which contributed to a deeper understanding of the gas-aerosol composition of the urban atmosphere, wet aerosol deposition with accounting of geochemical processes and aerosol radiative effects. Aerosol pollution in the Moscow region and its dynamics in the 21st century were estimated according to the aerosol retrievals using the MAIAC algorithm developed for the MODIS satellite instrument, and long-term AERONET measurements. The effects of aerosol on meteorological and radiative characteristics of the atmosphere were obtained from the numerical experiments with the COSMO model and long-term observations. The indirect aerosol effects on cloud characteristics and weather forecast were estimated.

We investigated the liquid water path and global solar irradiance (Q) at ground level according to the ICON model; CLOUDNET measurements in Lindenberg, Munich, and Jülich; and BSRN observations in Lindenberg. This research is focused on stratiform non-precipitating clouds. The liquid water path (LWP) is underestimated, while Q is overestimated. The lower LWP is due to liquid water content underestimation practically in all atmosphere layers and a lower frequency of liquid cloud occurrence compared to observations. This is partly associated with the structure of the cloud nucleation scheme of the ICON model and with the default cloud condensation nuclei (CCN) number concentration. An increase in CCNs from 250 cm⁻³ (typical background value for the region of interest) to 1700 cm⁻³ (characteristic of polluted continental clouds) leads to an increase in the grid-scale liquid water path by 40% and a decrease in Q by 12% in overcast conditions. However, we also showed that the liquid water path is not a key factor of Q overestimation. The main factor is an inaccurate description of the cloud spatial structure, where the correct prediction of the ratio of direct to global irradiance as a spatial characteristic of clouds plays a more important role than the standard cloud fraction.

We investigated the liquid water path and global solar irradiance at ground (Q) according to the ICON model, CLOUDNET measurements in Lindenberg, Munich, Jülich, and BSRN observations in Lindenberg. The liquid water path is underestimated, while global irradiance is overestimated. The lower liquid water path is due to liquid water content underestimation practically in all atmosphere layers and lower frequency of liquid clouds occurrence compare to observations. The latter is partly associated with a reduced model’ sensitivity to the cloud condensation nuclei (CCN). An increase in CCN from 250 cm-3 (typical background value for the region of interest) to 1700 cm-3 (characteristic of polluted continental clouds) leads to an increase in grid-scale liquid water path by 40% and a decrease in Q under overcast conditions by 12%. However, we also showed that liquid water path is not a key factor of Q overestimation. The main factor is an inaccurate description of the cloud spatial structure, where the correct prediction of the direct to global irradiance ratio as a spatial characteristic of clouds plays the most important role compared to standard cloud fraction.