Cloud Water Resource in North China in 2017 Simulated by the CMA-CPEFS Cloud Resolving Model: Validation and Quantification


  • 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 precipitation, 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, precipitation, 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, advection 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.
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