Diagnostic Quantification of the Cloud Water Resource in China during 2000–2019

By using the diagnostic quantification method for cloud water resource (CWR), the three-dimensional (3D) cloud fields of 1° × 1° resolution during 2000–2019 in China are firstly obtained based on the NCEP reanalysis data and related satellite data. Then, combined with the Global Precipitation Climatology Project (GPCP) products, a 1° × 1° gridded CWR dataset of China in recent 20 years is established. On this basis, the monthly and annual CWR and related variables in China and its six weather modification operation sub-regions are obtained, and the CWR characteristics in different regions are analyzed finally. The results show that in the past 20 years, the annual total amount of atmospheric hydrometeors (GM_h) and water vapor (GM_v) in the Chinese mainland are about 838.1 and 3835.9 mm, respectively. After deducting the annual mean precipitation of China (P_s, 661.7 mm), the annual CWR is about 176.4 mm. Among the six sub-regions, the southeast region has the largest amount of cloud condensation (C_vh) and precipitation, leading to the largest GM_h and CWR there. In contrast, the annual P_s, GM_h, and CWR are all the least in the northwest region. Furthermore, the monthly and interannual variation trends of P_s, C_vh, and GM_h in different regions are identical, and the evolution characteristics of CWR are also consistent with the hydrometeor inflow (Q_hi). For the north, northwest, and northeast regions, in spring and autumn the precipitation efficiency of hydrometeors (PE_h) is not high (20%–60%), the renewal time of hydrometeors (RT_h) is relatively long (5–25 h), and GM_h is relatively high. Therefore, there is great potential for the development of CWR through artificial precipitation enhancement (APE). For the central region, spring, autumn, and winter are suitable seasons for CWR development. For the southeast and southwest regions, P_s and PE_h in summer are so high that the development of CWR should be avoided. For different spatial scales, there are significant differences in the characteristics of CWR.