| Session Details | |
| Section | AS - Atmospheric Sciences |
| Session Title | Application of Cloud-resolving Model Simulations for Studying Cloud-related Processes in Climate |
| Main Convener | Dr. Wei-Kuo Tao (NASA Goddard Space Flight Center, United States) |
| Co-convener(s) | Prof. Chung-Hsiung Sui (National Taiwan University, Taiwan) Prof. Masaki Satoh (The University of Tokyo, Japan) Prof. Pay-Liam Lin (National Central University, Taiwan) Prof. Qinghong Zhang (Peking University, China) |
| Session Description | Cloud-system-related problems are at the heart of global and regional climate simulations and the understanding of climate change. Convective clouds not only release latent heat from condensation and vertically redistribute heat and moisture, but also play important role in the global and regional hydrological cycle through the precipitation and the modification of shortwave and longwave radiative fluxes at the ocean and land surface. However, the representation of cloud systems in general circulation models (GCMs) and regional climate models (RCMs) remains one of major challenges for the climate simulations. The improvement to the existing convection and cloud parameterization schemes in GCMs has been slow. The development of cloud-resolving models (CRMs) provides a unique opportunity to evaluate and improve the existing convection, cloud and radiation schemes. While GCMs require convection and cloud parameterizations, CRMs explicitly resolve convection and mesoscale organization, where cloud microphysical processes and cloud-radiation interactions directly respond to the cloud-scale dynamics. Increasing studies have been focused on the application of CRM simulations to improve parameterizations of subgrid-scale physical processes in GCMs; to understand the interaction of cloud systems with large-scale circulations; and to replace the cloud-related parameterizations in GCMs. The goal of this session is to showcase the current efforts on this challenging task and encourage the collaboration between the CRM, GCM and RCM modelers. |