Jing Ren, Wenyu Zhang, Menggang Kou, Yongjing Ma, Xinyu Zhang

A Numerical Study of Critical Variables on Artificial Cold Cloud Precipitation Enhancement in the Qilian Mountains, China

  • Atmospheric Science
  • Environmental Science (miscellaneous)
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In this study, a mesoscale Weather Research and Forecast (WRF) model coupled with an AgI (silver iodide) cold cloud catalytic module were used to explore the potential impact of the catalytic position and rate in the catalytic module based on a ground rain enhancement operation in the Qilian Mountains, on 16 August 2020. Results show that the simulated precipitation, liquid water content (LWC), and water vapor content (PWV) are in good agreement with the observations, demonstrating that the WRF model using the coupled AgI cloud-seeding scheme is well-applicable to the precipitation simulation of the Qilian Mountains. It is also observed that there are some differences in the catalytic effect of catalysis at different cloud temperatures. The precipitation enhancement effect is the most favorable in the fifth layer of 15 km, followed by that in the fourth layer of 12 km and the sixth layer of 18 km. Considering the flight cost and catalytic efficiency, the fourth layer is highly recommended for seeding. Furthermore, the AgI seeding rate also plays a crucial impact on ground precipitation. In the case of a seeding rate of about 1.2 g·s−1, the precipitation enhancement effect tends to be stable, and the percentage of the precipitation increase reaches up to 10.4%. While in the case of a seeding rate of about 1.5 g·s−1, the percentage of ground precipitation increase is 10%, which is 0.4% lower than that of 1.2 g·s−1. In summary, the introduction of a AgI catalyst with a seeding rate of 1.2 g·s−1 can significantly increase the ground precipitation at a height of 12 km and a temperature of −3 °C in the Qilian Mountains.

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