Clouds exert an important influence on the planet's water and energy balances and processes that relate to clouds underpin key climate feedbacks. IPCC AR4 pointed out that aerosols, clouds, and their interaction processes present large uncertainties in climate change study. Therefore, better understanding of cloud growth process is strongly required. Now scientists have some powerful tool for overcoming this problem. One is the satellite observation, the other is the cloud modeling especially, cloud resolving model and spectral bin cloud microphysical model.

One of the features of recent existing and/or planning satellite missions is installations of some active sensors such as radar and lidar that enable us to observe the vertical structure of cloud and aerosol. CloudSat and CALIPSO observations, with TRMM before it, represent a new epoch in Earth observations with the purpose of revealing the mechanism of particle transition, from cloud condensation nuclei (CCN) to rain droplets via cloud and drizzle particles, by estimating the vertical structure of aerosol, cloud, and rain properties from space. One of recent progress of the cloud observation results from space is contriving a new visualization of the CPR reflectivities, called CFODD (Contoured Frequency by Optical Depth Diagram) (Nakajima et al 2010, Suzuki et al. 2010). The CFODD grouped by cloud droplet size retrieved from passive imager (e.g. MODIS) show transition of cloud growth, from cloud droplet mode to rain mode via drizzle mode very clearly. Cloud model following these satellite observations. For example, diagnostic use of the satellite data for developing cloud model showed how the models are qualitatively similar to but quantitatively different from observations in terms of cloud-to-rain water conversion processes (Suzuki et al. 2011).

In this presentation, we will talk about the recent progresses of the cloud observations from A-Train, showing multi-sensor views (CloudSat and MODIS) of cloud droplet growth process, and some comparison results between observations vs models. We will also introduce future satellite missions, GCOM, EarthCARE and so on that contribute to the cloud sciences in present and future. We will also introduce an idea for observing the time-line of the cloud evolution process using the third generation geostationary satellites, e.g. Himawari (Japan), GOES (US), Meteosat (Europe), that enable global scale multispectral imaging by every 10 minutes or more frequently. Both polar orbit and geo-stationary satellites are key observation systems for better understanding of our climate.