Aerosols have significant and complex impacts on regional climate in East Asia. Cloud‐aerosol‐precipitation interactions (CAPI) remain most challenging in climate studies. The quantitative understanding of CAPI requires good knowledge of aerosols, ranging from their formation, composition, transport, and their radiative, hygroscopic, and microphysical properties. A comprehensive review is presented here centered on the CAPI based chiefly, but not limited to, publications in the special section named EAST‐AIRcpc concerning (1) observations of aerosol loading and properties, (2) relationships between aerosols and meteorological variables affecting CAPI, (3) mechanisms behind CAPI, and (4) quantification of CAPI and their impact on climate. Heavy aerosol loading in East Asia has significant radiative effects by reducing surface radiation, increasing the air temperature, and lowering the boundary layer height. A key factor is aerosol absorption, which is particularly strong in central China. This absorption can have a wide range of impacts such as creating an imbalance of aerosol radiative forcing at the top and bottom of the atmosphere, leading to inconsistent retrievals of cloud variables from space‐borne and ground‐based instruments. Aerosol radiative forcing can delay or suppress the initiation and development of convective clouds whose microphysics can be further altered by the microphysical effect of aerosols. For the same cloud thickness, the likelihood of precipitation is influenced by aerosols: suppressing light rain and enhancing heavy rain, delaying but intensifying thunderstorms, and reducing the onset of isolated showers in most parts of China. Rainfall has become more inhomogeneous and more extreme in the heavily polluted urban regions.

The rapid warming and consequent retreat of glaciers across the Tibetan Plateau (TP) have given rise to the debate on the ability of the atmospheric water supply to alleviate the depletion of surface water storage. We investigate long‐term changes in atmospheric water vapor balance across the TP using 40‐year fifth generation European Centre for Medium‐Range Weather Forecasts (ECMWF) (ERA5) reanalysis. Precipitation, water vapor convergence, and evaporation generally maintain an equilibrium but with different long‐term variation trends: 0.68, −0.18, and 0.69 mm/a, respectively. Results suggest the inability of the water vapor arriving from outside the TP to effectively replenish the surface water storage. Despite of huge changes in atmospheric water vapor balance during summer, the risk of water storage depletion is brought by other three seasons, especially the autumn. The climatology and long‐term trends of water vapor balance exhibit strong variation across the regions of TP. The surrounding areas of Yarlung Zangbo Grand Canyon experience sharp decrease in water vapor convergence, thus reducing precipitation. Moreover, increasing evaporation is expected to severely loss of surface water storage. For the Three Rivers Source Region with no significant changes in total precipitations, decrease in water transported from outside of TP overlaps increase in evaporation results in the possible depletion of surface water storage. Brahmaputra basin, inner TP, and Qilian Mountain exhibit significant wetting trends due to increases in both convergence of water vapor flux and evaporation. Above regional and seasonal characteristics of water vapor, balances across the TP are attributed by inhomogeneous variation of atmospheric heat source and complex changes of atmospheric circulations.

Based on 8 years of (January 2008–December 2015) cloud phase information from the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP), aerosol products from CALIPSO and meteorological parameters from the ERA-Interim products, the present study investigates the effects of atmospheric dynamics on the supercooled liquid cloud fraction (SCF) during nighttime under different aerosol loadings at global scale to better understand the conditions of supercooled liquid water gradually transforming to ice phase. Statistical results indicate that aerosols' effect on nucleation cannot fully explain all SCF changes, especially in those regions where aerosols' effect on nucleation is not a first-order influence (e.g., due to low ice nuclei aerosol frequency). By performing the temporal and spatial correlations between SCFs and different meteorological factors, this study presents specifically the relationship between SCF and different meteorological parameters under different aerosol loadings on a global scale. We find that the SCFs almost decrease with increasing of aerosol loading, and the SCF variation is closely related to the meteorological parameters but their temporal relationship is not stable and varies with the different regions, seasons and isotherm levels. Obviously negative temporal correlations between SCFs versus vertical velocity and relative humidity indicate that the higher vertical velocity and relative humidity the smaller SCFs. However, the patterns of temporal correlation for lower-tropospheric static stability, skin temperature and horizontal wind are relatively more complex than those of vertical velocity and humidity. For example, their close correlations are predominantly located in middle and high latitudes and vary with latitude or surface type. Although these statistical correlations have not been used to establish a certain causal relationship, our results may provide a unique point of view on the phase change of mixed-phase cloud and have potential implications for further improving the parameterization of the cloud phase and determining the climate feedbacks.

Diurnal variations in cloud cover and cloud vertical distribution are of great importance to Earth–atmosphere system radiative budgets and climate change. However, thus far these topics have received insufficient attention, especially on the Tibetan Plateau (TP). This study focuses on the diurnal variations in total cloud cover, cloud vertical distribution, and cirrus clouds and their relationship to meteorological factors over the TP based on active and passive satellite observations, reanalysis data, and CMIP6 outputs. Our results are consistent with previous studies but provide new insights. The results show that total cloud cover peaks at 06:00–09:00 UTC, especially over the eastern TP, but the spatial and temporal distributions of clouds from different datasets are inconsistent. This could to some extent be attributed to subvisible clouds missed by passive satellites and models. Compared with satellite observations, the amplitudes of the diurnal variations in total cloud cover obtained by the reanalysis and CMIP6 models are obviously smaller. CATS can capture the varying pattern of the vertical distribution of clouds and corresponding height of peak cloud cover at middle and high atmosphere levels, although it underestimates the cloud cover of low-level clouds, especially over the southern TP. Compared with CATS, ERA5 cannot capture the complete diurnal variations in vertical distribution of clouds and MERRA-2 has a poorer performance. We further find that cirrus clouds, which are widespread over the TP, show significant diurnal variations with averaged peak cloud cover over 0.35 at 15:00 UTC. Unlike in the tropics, where thin cirrus (0.03< optical depth <0.3) dominate, opaque cirrus clouds (0.3< optical depth <3) are the dominant cirrus clouds over the TP. The seasonal and regional averaged cloud cover of opaque cirrus reaches a daily maximum of 0.18 at 11:00 UTC, and its diurnal cycle is strong positive correlation with that of 250 hPa relative humidity and 250 hPa vertical velocity. Although subvisible clouds (optical depth <0.03), which have a potential impact on the radiation budget, are the fewest among cirrus clouds over the TP, the seasonal and regional averaged peak cloud cover can reach 0.09 at 22:00 UTC, and their diurnal cycle correlates with that of the 250 hPa relative humidity, 2 m temperature, and 250 hPa vertical velocity. Our results will be helpful to improve the simulation and retrieval of total cloud cover and cloud vertical distribution and further provide an observational constraint for simulations of the diurnal cycle of surface radiation budget and precipitation over the TP region.

Using hourly observation data of precipitation and PM_2.5 at 12 sites in Beijing from 2015 to 2017, this study investigates the impacts of different types of precipitation on PM_2.5 mass concentration, along with the characteristics of precipitation and PM_2.5. There were totally 91–123 precipitation events annually, 69.7–79.4% of which has precipitation amount less than 5 mm. By investigating the differences of PM_2.5 mass concentration between 1 hr after and before the precipitation events, this study finds distinct impacts of different types of precipitation on PM_2.5 mass concentration. For precipitation events with amount of 0.1–0.5 mm, PM_2.5 mass concentration increased with precipitation amount with a rate of 0.85 μg/m³ per 0.1 mm. For precipitation events with amount of 0.5–10 mm, there was no clear relationship between precipitation amount and PM_2.5 mass concentration. For precipitation events with amount larger than 10 mm, PM_2.5 mass concentration decreased with precipitation amount with a rate of 0.17 μg/m³ per 1 mm. Further analysis shows that weak precipitation less than 10 mm increased PM₁₀, and heavy precipitation larger than 10 mm decreased PM₁₀. The aerosol amount also affects the response of PM_2.5 to precipitation, with weak pollution prone to increase with precipitation and heavy pollution prone to decrease with precipitation. Likely mechanisms are discussed, which include the aerosol hygroscopic growth and gas‐particle conversion that increase aerosol amount and precipitation scavenging that decreases aerosol amount. Shortly, the mechanisms that increase (decrease) aerosol amount more probably dominate when precipitation is light (heavy).