Evaluation of the First Negative Ion-Based Cloud Seeding and Rain Enhancement Trial in China

Abstract

Negative ion-based cloud seeding has been shown to be an effective means in the laboratory. China’s first negative ion-based cloud seeding outfield trial was conducted in the northwestern interior. This paper briefly introduces the principle of the ion-based precipitation enhancement, and the trial location is described. The design of the ionization system and meteorological monitoring network are presented. The implementation plan of the outfield trial is explained. In addition, the evaluation of experimental effects is detailed in this paper. We designed various analytical methods to investigate both the overall precipitation variation of the experimental area and the precipitation variation within the experimental area. The overall precipitation of the experimental area was predicted using a neural network, and then the actual precipitation was compared with the predicted precipitation to evaluate the effectiveness of the experiment. The effectiveness of the experiment was also evaluated using historical precipitation data and the result of the randomized comparative trial. This paper also explores the effects of geographic location differences and wind direction differences on the precipitation differences within the trial area. The changes in the number of negative ions and clouds in the sky were also analyzed. From these analyses, we obtained quantitative assessment results. These results could indicate that the outfield trial basically met the expected requirements, which is to increase the rainfall of the trial area by 20%.

Preliminary Application of a Multi-Physical Ensemble Transform Kalman Filter in Cloud and Precipitation Forecasts

“…Weather modification in China has become an essential basic public welfare undertaking for the coordinated development of state and local governments after years of development [1][2][3]. Many studies have shown that a successful weather modification operation is inseparable from a comprehensive understanding of the cloud features [4][5][6][7]. Therefore, the accurate forecast of cloud features in the atmosphere is the key to the efficient development of cloud water resources and artificial rainfall.…”