Advances in Meteorology (Jan 2023)

Estimation of the Total Amount of Enhanced Rainfall for a Cloud Seeding Experiment: Case Studies of Preventing Forest Fire, Drought, and Dust

  • Yonghun Ro,
  • Ki-Ho Chang,
  • Sanghee Chae,
  • Yun-Kyu Lim,
  • Jung Mo Ku,
  • Woonseon Jung

DOI
https://doi.org/10.1155/2023/5478666
Journal volume & issue
Vol. 2023

Abstract

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In this study, a method for verifying the effect of cloud seeding in the case of a mixture of natural and artificial rainfall bands was proposed, and its applicability to each experimental case was evaluated. Water resources that could be secured through cloud seeding were also quantified for the experiments on forest fire prevention, drought mitigation, and dust reduction in 2020. Data on numerical simulations, radar-derived rainfall, rain gauge-derived rainfall, and weather conditions were applied. Areas with seeding and nonseeding effects were classified according to the numerical simulation results and wind system, and enhanced rainfall was determined by comparing the changes in rainfall between the two areas. The amount of water resources was determined by considering the area of the seeding effect and rainfall density. As a result, 1.74 mm (4.75 million tons) of rainfall increased from the experiment on forest fire prevention, 0.84 mm (1.30 million tons) on drought mitigation, and 2.78 mm (24.44 million tons) on dust reduction. Thus, an average rainfall of 1.0 mm could be achieved through the experiment. These results helped verify the pure seeding effect and achieve the experimental purpose.