Model for predicting potential for aircraft cold cloud precipitation enhancement in Da Xing’ anling Mountains in Inner Mongolia
Received date: 2024-09-04
Revised date: 2024-11-07
Online published: 2025-03-17
Da Xing’anling Mountains was of immeasurable significance in maintaining regional ecological balance and ecological security. However, it was also one of the key fire risk areas. The prediction model of aircraft cold cloud precipitation enhancement potential was established to provide important technical support for the precise operation of artificial rain enhancement for fire prevention and extinguishing in the Daxing’an Mountains. Based on the number concentrations of small and large cloud particles observed by aircraft from 2017 to 2020 and 2023, the potential for enhancing precipitation was divided into three categories: strongly seedable, seedable, and not seedable. Based on the ERA5 reanalysis data, the environmental parameters of the three types of precipitation enhancement potential samples were discussed, and the results showed that the relative humidity values of 750 hPa were 79.1% and 95.6%, that is, the relative humidity of the not seedable sample was less than 79.1%, and the relative humidity of the strongly seedable sample was greater than 95.6%, and the relative humidity value of the seedable sample was between the two. The dew point temperature differences at 700 hPa were 0.3 ℃ and 2.4 ℃, the vertical velocities at 650 hPa were 0.7 and -0.06 Pa·s-1, the liquid water contents at 650 and 700 hPa were 0.01 and 0.08 g·kg-1, the rainwater mixing ratios at 850 hPa were 0.01 and 0.07 g·kg-1, and the vertical cumulative supercooled water was 0.5 and 2.2 mm. Considering the accuracy with which the three samples could be distinguished using the environmental parameter thresholds and the collinearity relationships between the parameters, four environmental parameters were finally selected, and two model for predicting the potential to enhance precipitation were established using the Fisher and Bayes methods. The average recognition rate of the two models was 88.6% for the training set and 98.6% for the test set, providing strong support for the implementation of scientific and accurate weather modification operations.
YI Nana , Bilige , SHI Jinli , CAI Min , XU Zhili , ZHENG Fengjie , Lina . Model for predicting potential for aircraft cold cloud precipitation enhancement in Da Xing’ anling Mountains in Inner Mongolia[J]. Arid Zone Research, 2025 , 42(3) : 409 -419 . DOI: 10.13866/j.azr.2025.03.02
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