Application of Seasonal CRM Integrations to Develop Statistics and Improved GCM Parameterization of Subgrid Cloud-Radiation Interactions

Wu, Xiaoqing ; Liang, Xin-Zhong ; Park, Sunwook

Dr. Xiaoqing Wu/Iowa State University

关键词: Statistics;    Cloud-Resolving Model;    Clouds;    General Circulation Model;    Simulation;   

DOI  :  10.2172/897856
RP-ID  :  DOE/ER/63483-1
RP-ID  :  FG02-02ER63483
RP-ID  :  897856

美国|英语

来源: UNT Digital Library

【 摘 要 】

The works supported by this ARM project lay the solid foundation for improving the parameterization of subgrid cloud-radiation interactions in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and concurrent ARM observations to produce long-term, consistent cloud and radiative property datasets at the cloud scale (Wu et al. 2006, 2007). With these datasets, we have investigated the mesoscale enhancement of cloud systems on surface heat fluxes (Wu and Guimond 2006), quantified the effects of cloud horizontal inhomogeneity and vertical overlap on the domain-averaged radiative fluxes (Wu and Liang 2005), and subsequently validated and improved the physically-based mosaic treatment of subgrid cloud-radiation interactions (Liang and Wu 2005). We have implemented the mosaic treatment into the CCM3. The 5-year (1979-1983) AMIP-type simulation showed significant impacts of subgrid cloud-radiation interaction on the climate simulations (Wu and Liang 2005). We have actively participated in CRM intercomparisons that foster the identification and physical understanding of common errors in cloud-scale modeling (Xie et al. 2005; Xu et al. 2005, Grabowski et al. 2005).