Investigation of Microphysical Characteristics of Precipitation Under the Action of Acoustic Waves in the Source Region of the Yellow River
Abstract
As a potentially effective technology for particle removal, acoustic agglomeration technology has been tested for weather modification. The mechanism of acoustic agglomeration technology is to emit low-frequency acoustic waves to target cloud layer, to manipulate the motion of airborne particles through utilization of the energy transmission and momentum exchange between acoustic waves and discrete particles, to intensify the vibration and collision process of aerosols and improve agglomeration efficiency. To date, small-scale experiments and simulation studies have shown that acoustic waves can accelerate agglomeration of droplets and aerosol particles, but this has not been confirmed by large-scale field experiments and observations. In this study, 49 field experiments in the source region of Yellow River (SRYR) in the summer of 2019 were performed to investigate cloud and precipitation interference by low-frequency acoustic waves. Macro- and micro- physical characteristics of cloud and precipitation in the stratiform and convective precipitation system were monitored by multi-sensor observation, namely, tipping bucket rain gauges, disdrometer, micro rain radar, wind profiler radar, microwave radiometer, and Doppler radar with Ka/Ku bands. The cloud and precipitation related observations were further adopted to verify the physical response criteria and precipitation estimation of artificial precipitation-enhancement.
The ground-based observations show that acoustic waves could significantly affect rainfall distribution and microphysical parameters of precipitation particles such as rain rate (R), radar reflectivity factor (Z), liquid water content (Lwc) and height of cloud base (Hc). The average values of rainfall have increased by 18.98%, 10.61%, and 8.74% within 2 km, 3 km and 4 km from the operation center with acoustic application. The arithmetic mean values of R, Z, and Lwc become larger under the action of acoustic waves, and Hc values become lower with acoustic operation. Moreover, spectral parameters λ against μ, Z against R, and Lwc against R at different sampling altitudes and for different precipitation systems follow a quadratic function, power function, and linear function, respectively.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMA142.0001S
- Keywords:
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- 3310 Clouds and cloud feedbacks;
- ATMOSPHERIC PROCESSES;
- 3354 Precipitation;
- ATMOSPHERIC PROCESSES;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 1847 Modeling;
- HYDROLOGY