期刊论文

Dejun Li

英文

Water

2073-4441

2023

15

8

1585-

10.3390/w15081585

Conceptualization, R.L.; Data curation, D.L. and H.Z.; Formal analysis, R.L. and D.L.; Funding acquisition, L.Z.; Investigation, L.Z. and P.X.; Methodology, R.L., D.L. and P.X.; Project administration, R.L.; Software, R.L. and P.X.; Supervision, L.Z. and H.Z.; Writing—original draft, R.L.; Writing—review and editing, R.L. All authors have read and agreed to the published version of the manuscript. This work was supported by Hubei Provincial Natural Science Foundation of China (Grant No. 2022CFD019) and Open project of Hubei Provincial Key Laboratory of Intelligent Robot, the Innovation and Development Project of China Meteorological Administration (Grant No. CXFZ2022J036) and the Wuhan Knowledge Innovation Special Project (Grant No. 2022022101015009) and the National Natural Science Foundation of China (Grant No. 62171327).

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The evaluation of the effects of artificial precipitation enhancement remains one of the most important and challenging issues in the fields of meteorology. Rainfall is the most important evaluation metric for artificial precipitation enhancement, which is mainly achieved through physics-based models that simulate physical phenomena and data-driven statistical models. The series of effect evaluation methods requires the selection of a comparison area for effect comparison, and idealized assumptions and simplifications have been made for the actual cloud precipitation process, leading to unreli...