Effect of hygroscopic seeding on warm rain clouds – numerical study using a hybrid cloud microphysical model

Abstract

Abstract. The effect of hygroscopic seeding on warm rain clouds was examined using a hybrid cloud microphysical model combining a Lagrangian Cloud Condensation Nuclei (CCN) activation model, a semi-Lagrangian droplet growth model, and an Eulerian spatial model for advection and sedimentation of droplets. This hybrid cloud microphysical model accurately estimated the effects of CCN on cloud microstructure and suggested the following conclusions for a moderate continental air mass (an air mass with a large number of background CCN). (1) Seeding can hasten the onset of surface rainfall and increase the accumulated amount of surface rainfall if the amount and radius of seeding particles are appropriate. (2) The optimal radius of monodisperse particles to increase rainfall becomes larger with the increase in the total mass of seeding particles. (3) Seeding with salt micro-powder can hasten the onset of surface rainfall and increase the accumulated amount of surface rainfall if the amount of seeding particles is sufficient. (4) Seeding by a hygroscopic flare decreases rainfall in the case of large updraft velocity (shallow convective cloud) and increases rainfall slightly in the case of small updraft velocity (stratiform cloud). (5) Seeding with hygroscopic flares including ultragiant particles (r>5 µm) hastens the onset of surface rainfall but may not significantly increase the accumulated surface rainfall amount. (6) Hygroscopic seeding increases surface rainfall by two kinds of effects: the "competition effect" by Correspondence to: N. Kuba (kuba@jamstec.go.jp) which large soluble particles prevent the activation of smaller particles and the "raindrop embryo effect" in which giant soluble particles can immediately become raindrop embryos. In some cases, one of the effects works, and in other cases, both effects work, depending on the updraft velocity and the amount and size of seeding particles.

Aerosol Characterization by Dual-Wavelength Polarization Lidar Measurements over Kochi, Japan during the Warm Seasons of 2008 to 2010

“…For example, Kuba and Fujiyoshi (2006) and Kuba and Murakami (2010) demonstrated by using a hybrid cloud microphysical model that the effect of cloud seeding on the raindrop formation rate depends the characteristics of the background aerosol. They showed that seeding with large-particle cloud condensation nuclei (CCN) increases the amount of rainfall under polluted conditions (i.e., when there is a large number concentration of small hygroscopic particles), whereas it decreases the amount of rainfall under unpolluted conditions (i.e., a small number concentration of small hygroscopic particles).…”

Relationships between layer-mean radar reflectivity and columnar effective radius of warm cloud: Numerical study using a cloud microphysical bin model

“…The model used in this study is a hybrid microphysical cloud model with a two‐moment bin method [ Kuba and Fujiyoshi , ; Kuba and Murakami , ] that was developed to estimate the number concentration and size distribution of cloud droplets accurately, along with the effect of CCN on cloud microstructures. The activation of CCN and the initial condensational growth were computed in a Lagrangian particle framework using a parcel model.…”

Assessing the impact of the Kuroshio Current on vertical cloud structure using CloudSat data

“…Recently, the non-hydrostatic icosahedral atmospheric model (NICAM; e.g., Tomita and Satoh, 2004;Satoh et al, 2008) has made it possible to reproduce cloud-related phenomena with a horizontal resolution of less than 1 km (Miyamoto et al, 2013). Furthermore, a hybrid microphysical cloud model with a two-moment bin method (Kuba and Fujiyoshi, 2006;Kuba and Murakami, 2010) has been developed; therefore, the understanding of the smaller-scale phenomena is crucially necessary. Incorporating the results of this study into these models would greatly improve the accuracy of model simulations through motivating better representations of the rainfall parameterization and physically based process description.…”