资源环境科技发展态势分析平台

This study proposes a new approach that probes particle growth processes of liquid clouds with satellite observables from passive imagers. Based on the notion that the condensation growth and the coalescence process are characterized by constant cloud droplet number concentration (CDNC) and liquid water path (LWP), respectively, the method adopted used spatial variances of imager-derived cloud properties to estimate relative contributions from these processes embedded in the cloud system. The relative standard deviations (RSDs) of CDNC and LWP associated with their horizontal variances were compared in the form of their ratio. This approach was applied to the GCOM-C/SGLI cloud product, and spatial variability in this RSD ratio was consistent with cloud horizontal morphology such as open- and closed-cell structures. The results suggest that spatial variances of imager-derived cloud properties depict signatures of cloud microphysical processes in the way mappable on the horizontal extent of the cloud system.

Plain Language Summary In low-level clouds consisting of liquid water droplets, called warm clouds, droplets grow via the condensation and coalescence processes. The condensation process involves the growth of particles by absorption of water vapor and typically occurs in the early stages of cloud development. The coalescence process involves collision and coalescence with other particles and typically occurs when droplets grow to a size large enough for them to collide with each other. This study proposes a new approach that employs satellite observations to quantitatively estimate how these two processes occur in a given cloud system and to display it in the form of a geographical map of a quantity representing relative contributions of the two processes. The quantity was computed using spatial variances of satellite-observed cloud properties such as cloud droplet number concentration and liquid water path to diagnose the two processes characterized by conservation of each property. The results highlight that spatial variability in relative contributions of the two processes was consistent with cloud horizontal morphology such as open- and closed-cell structures that are identified as honeycomb-like patterns of cloudiness. The proposed approach may serve as a satellite-based way of "geographical process mapping" of warm clouds in the spatial context.