Abstract
Clouds have an important influence on Earth's water and energy balances, and cloud-related processes underpin key climate feedbacks. However, fundamental scientific understanding of water cloud forcing and feedbacks still remains one of the largest sources of uncertainty in climate sensitivity estimates. Cloud remote sensing from spaceborne sensors has been providing useful information for reducing such uncertainties in climate studies. Cloud droplet effective radius (CDER) and cloud optical thickness (COT) of water clouds are important observables obtained from remote sensing that characterize cloud droplet size distributions. Moreover they are indicators of the droplet growth such as condensational growth and collection processes. CDER and COT can be obtained from solar-reflected measurements by passive multispectral imagers such as Aqua/MODIS, EarthCARE/MSI, and GCOM-C/SGLI. However, interpretation of the obtained CDERs in terms of cloud structure and droplet growth is complex because clouds are typically inhomogeneous both vertically and horizontally. In this study, we discuss recent progress in interpreting CDERs obtained from satellites in terms of vertical and horizontal inhomogeneities by using numerical cloud models, high spatial resolution measurements, and active instruments. We first investigate the impact of in-cloud vertical structure and sub-pixel horizontal inhomogeneity upon obtained CDER by using a numerical cloud model and remote sensing simulators. Second, we introduce a research strategy for quantifying the effect of sub-pixel horizontal inhomogeneity by using high spatial resolution measurements from Terra/ASTER. Finally, we show a relationship between obtained CDER and droplet growth in nature based on combined use of spaceborne active and passive sensors (CloudSat and Aqua/MODIS).
