Impact of hygroscopic seeding on the initiation of precipitation formation: results of a hybrid bin microphysics parcel model

Abstract

Abstract. A hybrid bin microphysical scheme is developed in a parcel model framework to study how natural aerosol particles and different types of hygroscopic seeding materials affect the precipitation formation. A novel parameter is introduced to describe the impact of different seeding particles on the evolution of the drop size distribution. The results of more than 100 numerical experiments using the hybrid bin parcel model show that (a) the Ostwald-ripening effect has a substantial contribution to the broadening of the drop size distribution near the cloud base. The efficiency of this effect increases as the updraft velocity decreases. (b) The efficiency of hygroscopic seeding is significant only if the size of the seeding particles is in the coarse particle size range. The presence of the water-soluble background coarse particles reduces the efficiency of the seeding, (c) The efficient broadening of the size distribution due to the seeding depends on the width of the size distribution of water drops in the control cases, but the relation is not as straightforward as in the case of the glaciogenic seeding.

CAIPEEX: Indian Cloud Seeding Scientific Experiment

“…The seed particles with larger average sizes than the background aerosols support the tail effect (broadening of DSDs), leading to more rapid precipitation and reducing precipitation efficiency (Konwar et al 2023). Hygroscopic seeding impacts using direct numerical simulations (DNS) and a hybrid parcel model and the role of the ripening effect and low updraft favoring diffusion growth are documented in other studies (Chen et al 2020(Chen et al , 2021Geresdi et al 2021). The enhanced supersaturation is available due to strong updrafts for activating cloud droplets; the formation of small cloud droplets and the seed particles within clouds can be attributed to the competition effect (Gayatri et al 2023).…”

Numerical prediction of fog: A novel parameterization for droplet formation

“…The Lagrangian (moving bin) method inherently conserves the number concentration of particles and allows the tracking of aerosol mass inside of drops without numerical diffusion in mass and spatial dimensions. In this scheme the diffusional growth of wet aerosol particles is calculated even before the drops surpass the critical size, so no parameterization is needed for evaluation of the number concentration of drops formed on the activated aerosol particles (Geresdi et al, 2021).…”

“…This overestimation of the activation rate occurs when the aerosol particles can deplete the water vapor efficiently due to their larger size ( r m ≥0.5 μm) and larger hygroscopicity ( κ ≥ 0.5), but the available vapor content is small due to the weak cooling rate (≥ −2·10 −4 K·s −1 ). This discrepancy stems from the fact that in the case of small supersaturation like in fog, it takes hours for the drops formed on micron size aerosol particles to reach the critical size (Geresdi et al, 2021). However, the bulk parameterization scheme allows instant drop formation without taking into account the duration necessary to reach the critical drop size.…”

“…Severe haze episodes can form if the concentration of PM2.5 is high (e.g., X. Yang et al, 2020). The hygroscopic aerosol particles can absorb a significant amount of vapor even in subsaturated environments (Geresdi et al, 2021). This effect can be negligible if cloud formation is simulated; however, in the case of fog, the amount of vapor absorbed by the non‐activated aerosol particles can be comparable to vapor condensed on activated aerosol particles.…”