Cloud droplet spectral relative dispersion is critical to parameterizations of cloud radiative properties, warm‐rain initiation, and aerosol‐cloud interactions in models; however, there is no consistent relationship between relative dispersion and volume‐mean radius in literature, which hinders improving relative dispersion parameterization and calls for physical explanation. Here we show, by analyzing aircraft observations of cumulus clouds during Routine AAF [Atmospheric Radiation Measurement (ARM) Aerial Facility] Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations, that the correlation between relative dispersion and volume‐mean radius changes from positive to negative as volume‐mean radius increases. With the new observation, we postulate that the sign of the correlation is determined by whether or not condensation (evaporation) occurs simultaneously with significant new activation (deactivation). The hypothesis is validated by simulations of both an adiabatic cloud parcel model and a parcel model accounting for entrainment‐mixing. A new quantity, first bin strength, is introduced to quantify this new observation. Theoretical analysis of truncated gamma and modified gamma size distributions further supports the hypothesis and reconciles the contrasting relationships between relative dispersion and volume‐mean radius, including the results in polluted fog observations. The results could shed new light on the so‐called “twilight zone” between cloudy and cloud‐free air, which in turn affects evaluation of aerosol‐cloud interactions and retrieval of aerosol optical depth.

An ongoing challenge for cloud condensation nuclei (CCN) measurements is the inclusion of unactivated particles, which affects droplet activation parameterizations and aerosol indirect effects in models. For the first time, a reciprocal relationship between the critical diameter and critical supersaturation of activated droplets from the κ‐Köhler theory is derived to accurately count unactivated particles in CCN measurements. We conducted 4‐day continuous observations to simultaneously measure the number concentration of CCN (N_CCN) and aerosol. The results show that as supersaturation (SS) decreases from 0.186% at 25 °C, the proportion of the unactivated particles in the CCN measurements increases, reaching 88% at SS of 0.07%. Owing to the N_CCN overestimation caused by N_CCN‐SS parameterizations with uncorrected N_CCN, there is significant overestimation of aerosol indirect effects, especially under low SS conditions. After removing unactivated particles, N_CCN‐SS parameterizations are adjusted accordingly, which can improve simulations of aerosol‐cloud‐radiation interactions in models.

Numerical simulations often overpredict precipitation over the Tibetan Plateau (TP). To examine the factors causing precipitation overprediction, different parameterizations of liquid‐phase microphysical processes (accretion, autoconversion, and entrainment mixing) are implemented into the Morrison microphysics scheme to simulate a TP precipitation event in summer with the Weather Research and Forecasting (WRF) model. The general spatial distribution and temporal trend of precipitation are captured by all simulations, but the precipitation rate is overpredicted. The results from sensitivity experiments suggest that compared to other examined liquid‐phase processes, the accretion process is more important in precipitation simulation over the TP region. Further investigation with the Heidke skill scores reveals that accretion parameterization that takes into account the raindrop size produces the most accurate results in terms of the total surface precipitation. This parameterization suppresses spurious accretion and does not produce liquid‐phase precipitation until cloud droplets are big enough. It is also confirmed that increasing the model resolution can reduce precipitation overprediction. Results from the case study are confirmed by the use of a 1‐month simulation.

Understanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements of aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation. However, they are still scarce. In this study, more than 4 years of comprehensive aerosol measurements were utilized at the central European research station of Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving the prediction of number concentration of cloud condensation nuclei (CCN, N_CCN). (1) The overall CCN activation characteristics at Melpitz are provided. As supersaturation (SS) increases from 0.1 % to 0.7 %, the median N_CCN increases from 399 to 2144 cm⁻³, which represents 10 % to 48 % of the total particle number concentration with a diameter range of 10–800 nm, while the median hygroscopicity factor (κ) and critical diameter (D_c) decrease from 0.27 to 0.19 and from 176 to 54 nm, respectively. (2) Aerosol particle activation is highly variable across seasons, especially at low-SS conditions. At SS=0.1 %, the median N_CCN and activation ratio (AR) in winter are 1.6 and 2.3 times higher than the summer values, respectively. (3) Both κ and the mixing state are size-dependent. As the particle diameter (D_p) increases, κ increases at D_p of ∼40 to 100 nm and almost stays constant at D_p of 100 to 200 nm, whereas the degree of the external mixture keeps decreasing at D_p of ∼40 to 200 nm. The relationships of κ vs. D_p and degree of mixing vs. D_p were both fitted well by a power-law function. (4) Size-resolved κ improves the N_CCN prediction. We recommend applying the κ–D_p power-law fit for N_CCN prediction at Melpitz, which performs better than using the constant κ of 0.3 and the κ derived from particle chemical compositions and much better than using the N_CCN (AR) vs. SS relationships. The κ–D_p power-law fit measured at Melpitz could be applied to predict N_CCN for other rural regions. For the purpose of improving the prediction of N_CCN, long-term monodisperse CCN measurements are still needed to obtain the κ–D_p relationships for different regions and their seasonal variations.

As a precursor process to cloud formation, aerosol activation over the Tibetan Plateau (TP) plays a pivotal role in regional cloud-precipitation and global climate. However, its characteristics remain unclear due to the absence of targeted observations in the TP. We conducted a ground in-situ aerosol-cloud-precipitation experiment in the southern TP (GACPE-STP), thereby unveiling the aerosol activation characteristics in this crucial region. Our findings reveal a weak aerosol activation capacity with low hygroscopicity (κ) values of less than 0.1 through multi-method κ measurements, contrasting starkly with the widely recommended κ value of 0.3 for continental regions. A κ parameterization is developed for predicting aerosol activation in this region, which can significantly reduce the overestimations of cloud droplet number concentration and hence aerosol indirect effects caused by using the recommended κ of 0.3. These findings address the unclear characteristics of aerosol activation in the TP region, contributing to the enhancement of regional cloud precipitation and global climate simulations.