The Koren Lab

This study employs a high-resolution (10 m) System for Atmospheric Modeling (SAM) coupled with the spectral bin microphysical (SBM) scheme to thoroughly investigate the processes governing the evolution of aerosol properties within and outside a shallow cumulus cloud. The model encompasses the complete life cycle of cloud droplets, starting from their formation through their evolution until their complete evaporation or sedimentation to the ground. Additionally, the model tracks the aerosols' evolution both within the droplets and in the air. Aerosols are transported within the droplets, grow by droplet coalescence, and are released into the atmosphere after droplet evaporation (regeneration process). The aerosol concentration increases by droplet evaporation and decreases along with falling drops. So, the effects of clouds on the surrounding aerosols depend on the microphysical and dynamic processes, which in turn depend on the amount of background aerosols; here, we compare clean and polluted conditions. It is shown that the regeneration process is highly important and that shallow trade cumulus clouds significantly impact the vertical profile of aerosol concentration in the lower troposphere, as well as their size distribution, and can serve as a source of large cloud condensation nuclei. Furthermore, it is shown that both precipitating and nonprecipitating boundary layer clouds contribute to a substantial increase in aerosol concentration within the inversion layer due to intense evaporation.

The glory, a striking optical phenomenon seen from space in unpolarized satellite images can be mapped onto the cloud's droplet sizes with a characteristic scale of 10 (Formula presented.). Such a mapping allows us to infer the mean and variance of the cloud droplets' radius, an important property that has remained elusive and inaccessible to passive unpolarized satellite sensing. Here, we propose a simple and robust polarization-like differential approach to map the glory's spectral properties to the desired moments of the droplet size distribution. By taking the differences between two spectrally close channels, we reduce multiple scattering contributions and amplify the single-scattering signal, thus allowing for a simple and rapidly converging map from glory to droplet size distribution. Moreover, the droplet information reflects the upper part of the cloud, adding another sample to the traditional multiple scattering-based retrievals that reflect droplet properties deeper in the cloud.

Cloud microphysics studies include how tiny cloud droplets grow and become rain. This is crucial for understanding cloud properties like size, life span, and impact on climate through radiative effects. Small weak-updraft clouds near the haze-to-cloud transition are especially difficult to measure and understand. They are abundant but hard to capture by satellites. Köhlers theory explains initial droplet growth but struggles with large particle groups. Here, we present a stochastic, analytical framework building on Köhlers theory to account for (monodisperse) aerosols and cloud droplet interaction through competitive growth in a limited water vapor field. These interactions are modeled by sink terms, while fluctuations in supersaturation affecting droplet growth are modeled by nonlinear white noise terms. Our results identify hysteresis mechanisms in the droplet activation and deactivation processes. Our approach allows for multimodal clouds droplet size distributions supported by laboratory experiments, offering a different perspective on haze-to-cloud transition and small cloud formation.