气象学报（英文版）2022，Vol.36Issue(3)：1-48,48.
中尺度云分辨耦合模式(CMA-CPEFS)对中国华北区域2017年云水资源的模拟估算与检验
Cloud Water Resource in North China in 2017 Simulated by the CMA-CPEFS Cloud Resolving Model: Validation and Quantification
摘要
Abstract
Based on the concept of cloud water resource (CWR) and the cloud microphysical scheme developed by the Chinese Academy of Meteorological Sciences (CAMS), a coupled mesoscale and cloud-resolving model system is developed in the study for CWR numerical quantification (CWR-NQ) in North China for 2017. The results show that (1) the model system is stable and capable for performing 1-yr continuous simulation with a water budget error of less than 0.2％, which indicates a good water balance. (2) Compared with the observational data, it is confirmed that the simulating capability of the CWR-NQ approach is decent for the spatial distribution of yearly cumulative precipit- ation, daily precipitation intensity, yearly average spatial distribution of water vapor. (3) Compared with the CWR diagnostic quantification (CWR-DQ), the results from the CWR-NQ differ mainly in cloud condensation and cloud evaporation. However, the deviation of the net condensation (condensation minus evaporation) between the two methods is less than 1％. For other composition variables, such as water vapor advection, surface evaporation, precip- itation, cloud condensation, and total atmospheric water substances, the relative differences between the CWR-NQ and the CWR-DQ are less than 5％. (4) The spatiotemporal features of the CWR in North China are also studied. The positive correlation between water vapor convergence and precipitation on monthly and seasonal scales, and the lag of precipitation relative to water vapor convergence on hourly and daily scales are analyzed in detail, indicating the significance of the state term on hourly and daily scales. The effects of different spatial scales on the state term, ad- vection term, source–sink term, and total amount are analyzed. It is shown that the advective term varies greatly at different spatiotemporal scales, which leads to differences at different spatiotemporal scales in CWR and related characteristic quantities.关键词
中尺度-云分辨耦合模式/云水资源/水分收支/数值评估方法/长时间连续模拟Key words
cloud water resource/atmospheric moisture budget/long-term continuous simulation/model validation/spatiotemporal characteristics引用本文复制引用
谭超,蔡淼,周毓荃,刘卫国,胡志晋..中尺度云分辨耦合模式(CMA-CPEFS)对中国华北区域2017年云水资源的模拟估算与检验[J].气象学报（英文版）,2022,36(3):1-48,48.基金项目
Supported by the National Key Research and Development Program of China(2016YFA0601701),National Natural Science Founda-tion of China(42075191),and National High Technology Research and Development Program of China(2012AA120902). （2016YFA0601701）
