Assessment of Cloud Responses and Effects of Artificial Precipitation Enhancement Using Doppler Dual-Polarization Radar Observations
- 1School of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
- 2Jinan Municipal Center for Weather Modification, Jinan 250101, China
Abstract
The cloud and precipitation response characteristics following artificial precipitation enhancement serve as an essential basis for evaluating rain enhancement effectiveness. Based on cloud seeding operation records, S-band weather radar products, and precipitation data from automatic surface weather stations in Jinan from 2023 to 2025, a comparison area was selected using a similarity metric coefficient. Combined with a rationality analysis of the seeding operations, 107 seeding cases with significant positive effects were identified, and the post-seeding cloud and precipitation response characteristics were investigated. The results reveal marked differences in the capability of various radar products to indicate precipitation response. Vertically integrated liquid water content (VIL) exhibits the highest explanatory power (R2=0.302), followed by reflectivity at the 0 °C (R2=0.204). Specific differential phase (KDP) and −10 °C levels (R₀, R₋₁₀) outperforms echo top height (ET) and composite reflectivity (CR). Thus, VIL, KDP, and the reflectivity at key temperature levels jointly reveal the connection between post-seeding cloud microphysical characteristics and precipitation response. In addition, a multiple linear regression model integrating CR, ET, VIL, R₀, R₋₁₀, and KDP was established. This model demonstrates superior indicative capability for weak precipitation cloud systems and can be used to estimate the average 5 min precipitation amount within one hour after seeding.
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BibTeX
@article{feng2026assessment,
title = {{Assessment of Cloud Responses and Effects of Artificial Precipitation Enhancement Using Doppler Dual-Polarization Radar Observations}},
author = {Yuduo Feng and Debin Su and Ning Yang and Hui Sun and Yi Su and Dan Ren},
journal = {Atmosphere},
year = {2026},
month = oct,
doi = {10.3390/atmos17100991},
url = {https://doi.org/10.3390/atmos17100991},
note = {CC BY},
}
RIS
TY - JOUR
TI - Assessment of Cloud Responses and Effects of Artificial Precipitation Enhancement Using Doppler Dual-Polarization Radar Observations
AU - Yuduo Feng
AU - Debin Su
AU - Ning Yang
AU - Hui Sun
AU - Yi Su
AU - Dan Ren
PY - 2026
DA - 2026/10/26
JO - Atmosphere
DO - 10.3390/atmos17100991
UR - https://doi.org/10.3390/atmos17100991
AB - The cloud and precipitation response characteristics following artificial precipitation enhancement serve as an essential basis for evaluating rain enhancement effectiveness. Based on cloud seeding operation records, S-band weather radar products, and precipitation data from automatic surface weather stations in Jinan from 2023 to 2025, a comparison area was selected using a similarity metric coefficient. Combined with a rationality analysis of the seeding operations, 107 seeding cases with significant positive effects were identified, and the post-seeding cloud and precipitation response characteristics were investigated. The results reveal marked differences in the capability of various radar products to indicate precipitation response. Vertically integrated liquid water content (VIL) exhibits the highest explanatory power (R2=0.302), followed by reflectivity at the 0 °C (R2=0.204). Specific differential phase (KDP) and −10 °C levels (R₀, R₋₁₀) outperforms echo top height (ET) and composite reflectivity (CR). Thus, VIL, KDP, and the reflectivity at key temperature levels jointly reveal the connection between post-seeding cloud microphysical characteristics and precipitation response. In addition, a multiple linear regression model integrating CR, ET, VIL, R₀, R₋₁₀, and KDP was established. This model demonstrates superior indicative capability for weak precipitation cloud systems and can be used to estimate the average 5 min precipitation amount within one hour after seeding.
SN - 2073-4433
ER -