In estimates of climate sensitivity obtained from global models, the need to represent clouds introduces a great deal of uncertainty. To address this issue, approaches using a high-resolution global non-hydrostatic model are promising: the model captures cloud structure by explicitly simulating meso-scale convective systems, and the results compare reasonably well with satellite observations. We review the outcomes of a 5-year project aimed at reducing the uncertainty in climate models due to cloud processes using a global non-hydrostatic model. In our project, which was conducted as a subgroup of the Program for Risk Information on Climate Change, or SOUSEI, we use the non-hydrostatic icosahedral atmospheric model (NICAM) to study cloud processes related to climate change. NICAM performs numerical simulations with much higher resolution (about 7 km or 14 km mesh) than conventional global climate models (GCMs) using cloud microphysics schemes without a cumulus parameterization scheme, which causes uncertainties in climate projection. The subgroup had three research targets: analyzing cloud changes in global warming simulations with NICAM with the time-slice approach, sensitivity of the results to the cloud microphysics scheme employed, and evaluating circulation changes due to global warming. The research project also implemented a double-moment bulk cloud microphysics scheme and evaluated its results using satellite observation, as well as comparing it with a bin cloud microphysics scheme. The future projection simulations show in general increase in high cloud coverage, contrary to results with other GCMs. Changes in cloud horizontal-size distribution size and structures of tropical/extratropical cyclones can be discussed with high resolution simulations. At the conclusion of our review, we also describe the future prospects of research for global warming using NICAM in the program that followed SOUSEI, known as TOUGOU.

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.

Abstract. First, a hybrid cloud microphysical model was developed that incorporates both Lagrangian and Eulerian frameworks to study quantitatively the effect of cloud condensation nuclei (CCN) on the precipitation of warm clouds. A parcel model and a grid model comprise the cloud model. The condensation growth of CCN in each parcel is estimated in a Lagrangian framework. Changes in cloud droplet size distribution arising from condensation and coalescence are calculated on grid points using a two-moment bin method in a semi-Lagrangian framework. Sedimentation and advection are estimated in the Eulerian framework between grid points.Results from the cloud model show that an increase in the number of CCN affects both the amount and the area of precipitation. Additionally, results from the hybrid microphysical model and Kessler's parameterization were compared.Second, new parameterizations were developed that estimate the number and size distribution of cloud droplets given the updraft velocity and the number of CCN. The parameterizations were derived from the results of numerous numerical experiments that used the cloud microphysical parcel model. The input information of CCN for these parameterizations is only several values of CCN spectrum (they are given by CCN counter for example). It is more convenient than conventional parameterizations those need values concerned with CCN spectrum, C and k in the equation of N=CS k , or, breadth, total number and median radius, for example. The new parameterizations' predictions of initial cloud droplet size distribution for the bin method were verified by using the aforesaid hybrid microphysical model. The newly developed parameterizations will save computing time, and can effectively approximate components of cloud Correspondence to: N. Kuba (kuba@jamstec.go.jp) microphysics in a non-hydrostatic cloud model. The parameterizations are useful not only in the bin method in the regional cloud-resolving model but also both for a two-moment bulk microphysical model and for a global model. The effects of sea salt, sulfate, and organic carbon particles were also studied with these parameterizations and global model.

The effect of the size distribution and chemical composition of cloud condensation nuclei (CCN) on the size distribution of cloud droplets was studied by a numerical model of an adiabatically ascending air-parcel.Specially the formation of a broad droplet size distribution was discussed.Results of computation show that the supersaturation realized in the air-parcel is reduced, a broader size distribution of cloud droplets is produced. If the number concentration of CCN is higher in one air-parcel than that in the other air-parcel, the broader size distribution of droplets is produced in the former air-parcel. Both the addition of anthropogenic CCN in the range of Aitken size and the slower ascent of the air-parcel also produce the broader size distribution of droplets. The growth rate of a droplet formed on a small nucleus is sensitive to the change in supersaturation because of small molarity of the solution droplet, while a droplet formed on a large nucleus grows insensitively to the change in supersaturation because of large molarity. Therefore the droplet size distribution in the air-parcel of lower supersaturation is broader than that in the air-parcel of higher supersaturation. The size distribution of cloud droplets formed on nuclei in which water-insoluble matter is internally mixed is narrower than that of cloud droplets on non-mixed nuclei, if the size distribution of mixed nuclei is the same as that of non-mixed nuclei. But the size distribution of droplets formed on mixed nuclei is hardly different from that associated with non-mixed nuclei, if the mass distribution of soluble matter of mixed nuclei is the same as that of non-mixed nuclei.

Size‐resolved distributions of the hygroscopic growth factor (g) and the ratios of cloud condensation nuclei (CCN) to condensation nuclei were observed at a forest site during summer in Japan. The g distributions at 85% relative humidity were unimodal. During 0900–2100 Japan Standard Time (JST) on new particle formation (NPF) event days, less hygroscopic particles (g ~ 1.1) were dominant in the Aitken‐mode range and the CCN activation diameters of the aerosols were large. These results are explained by the substantial contribution from newly formed biogenic secondary organic aerosol (BSOA). Hygroscopicity parameter κ for newly formed Aitken particles, calculated from g and CCN activation diameters, were 0.12 and 0.16, respectively, which were estimated to be the κ of organics. The κ values of particles were higher during 2100–0900 JST on NPF event days, in which the aerosols were characterized by the dominance of large and more hygroscopic particles. The number fractions of CCN that were predicted from time‐ and size‐resolved g at 0.23% and 0.41% supersaturations better matched the measured values compared to the cases with the time‐averaged g and/or g for the bulk composition, which suggests that the differences in particle hygroscopicity with time and size are important to CCN activation. A cloud parcel model indicates that the contributions from less hygroscopic particles to the number concentrations of CCN and cloud droplets were potentially large during NPF event days, which suggests a marked contribution from locally formed BSOA particles alongside particles from background air.