内蒙古大兴安岭飞机冷云增雨潜势预报模型

doi:10.13866/j.azr.2025.03.02

Abstract

Abstract:

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.

Key words: weather modification, Da Xing’ anling Mountains in Inner Mongolia, environmental parameters, forecasting models

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.

Figures/Tables 13

Tab. 1

Tab. 2

Tab. 3

The environmental parameters of samples"

强可播、可播与不可播样本环境参量
第一类			第二类
降水	水汽	比湿 $（ q ）$	增雨	垂直累积过冷水 $（ S L ）$
		相对湿度 $（ R H ）$		雨水混合比 $（ Q R ）$
		温度露点差 $（ T D D ）$		液态水混合比 $（ Q L ）$
		大气可降水量 $（ P W V ）$		冰晶混合比 $（ Q I ）$
	层结	假相当位温 $（ θ s e ）$		雪水混合比 $（ Q S ）$
	层结	温度差 $（ T D ）$		冰面饱和水汽压 $（ e s i ）$
	抬升	垂直速度 $（ W ）$
	抬升	散度 $（ D I V ）$

Tab. 3

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Tab. 4

Fig. 8

Fig. 9

References 35

[1]	李伟克, 舒立福, 王明玉, 等. 黑龙江大兴安岭林区雷击火与人为火发生规律及变化趋势[J]. 林业科学, 2024, 60(4): 136-146.
	[Li Weike, Shu Lifu, Wang Mingyu, et al. Occurrence pattern and changing trend of lightning induced fires and human-caused fires in Da Xingan’ling Mountains of Heilongjiang Province[J]. Forestry Science, 2024, 60(4): 136-146.]
[2]	张煜星, 王雪军, 蒲莹, 等. 1949—2018年中国森林资源碳储量变化研究[J]. 北京林业大学学报, 2021, 43(5): 1-14.
	[Zhang Yuxing, Wang Xuejun, Pu Ying, et al. Changes in forest resource carbon storage in China between 1949 and 2018[J]. Journal of Beijing Forestry University, 2021, 43(5): 1-14.]
[3]	Wees D V, Werf G R V D, Randerson J T, et al. The role of fire in global forest loss dynamics[J]. Global Change Biology, 2021, 27(11): 2377-2391.
[4]	贾丙瑞, 周广胜. 北方针叶林对气候变化响应的研究进展[J]. 地球科学进展, 2009, 24(6): 668-674. doi: 10.11867/j.issn.1001-8166.2009.06.0668
	[Jia Bingrui, Zhou Guangsheng. Advances in the studies of the response of boreal forest to climate change[J]. Advances in Earth Science, 2009, 24(6): 668-674.] doi: 10.11867/j.issn.1001-8166.2009.06.0668
[5]	韩士杰, 王庆贵. 北方森林生态系统对全球气候变化的响应研究进展[J]. 北京林业大学学报, 2016, 38(4): 1-20.
	[Han Shijie, Wang Qinggui. Response of boreal forest ecosystem to global climate change: A review[J]. Journal of Beijing Forestry University, 2016, 38(4): 1-20.]
[6]	魏书精, 罗斯生, 罗碧珍, 等. 气候变化背景下森林火灾发生规律研究[J]. 林业与环境科学, 2020, 36(2): 133-143.
	[Wei Shujing, Luo Sisheng, Luo Bizhen, et al. Occurrence regularity of forest fire under the background of climate change[J]. Forestry and Environmental Science, 2020, 36(2): 133-143.]
[7]	Doerr S H, Santin C. Global trends in wildfire and its impacts: Perceptions versus realities in a changing world[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2016, 371(1696): 1-19.
[8]	余珊, 陈悦, 路晓燕, 等. 我国近年森林火灾情况及森林防火政策措施简析[J]. 森林防火, 2023, 41(2): 7-10.
	[Yu Shan, Chen Yue, Lu Xiaoyan, et al. Brief analysis of the forest fires situation and forest fire prevention policy measures in China in recent years[J]. Journal of Wildland Fire Science, 2023, 41(2): 7-10.]
[9]	王秋华, 王劲, 王亚荣, 等. 国内外重大森林火灾研究进展[J]. 消防科学与技术, 2022, 41(10): 1455-1459.
	[Wang Qiuhua, Wang Jin, Wang Yarong, et al. Research progress of major forest fires at home and abroad[J]. Fire Science and Technology, 2022, 41(10): 1455-1459.]
[10]	刘丽丽. 山西省森林雷击火发生原因分析与对策研究[J]. 山西林业, 2024(1): 34-35.
	[Liu Lili. Analysis of the causes and countermeasures of forest lightning fires in Shanxi Province[J]. Shanxi Forestry, 2024(1): 34-35.]
[11]	蔡恒明, 魏航, 陈圣东. 大兴安岭地区森林火灾和气象因子相关性研究[J]. 林业科技, 2021, 46(1): 49-51.
	[Cai Hengming, Wei Hang, Chen Shengdong. Research on the correlation between forest fires and meteorological factors in Daxing’anling[J]. Forestry Science and Technology, 2021, 46(1): 49-51.]
[12]	Yoo C, Chang K H, Ma J H, et al. Effect of cloud seeding in winter on soil moisture and forest fire risk in spring: A case study for eastern mountain region in Korea[J]. Journal of Hydrology: Regional Studies, 2024. DOI: 10.2139/ssrn.4761959.
[13]	李思宇, 梁达, 韦燕芳, 等. 基于贝叶斯网络的干旱—森林火灾灾害链定量建模研究[J]. 自然灾害学报, 2023, 32(1): 38-46.
	[Li Siyu, Liang Da, Wei Yanfang, et al. Quantitative modeling of drought-forest fire hazard chain based on bayesian network[J]. Journal of Natural Disasters, 2023, 32(1): 38-46.]
[14]	尹春, 罗汉, 何金梅, 等. 地面人工增雨作业对祁连山森林火险气象等级的影响[J]. 陕西气象, 2023(5): 48-53.
	[Yin Chun, Luo Han, He Jinmei, et al. Effect of ground artificial precipitation enhancement operation on forest fire danger meteorological level in Qilian Mountains[J]. Shaanxi Meteorology, 2023(5): 48-53.]
[15]	Ro Y, Chang K H, Chae S, et al. Estimation of the total amount of enhanced rainfall for a cloud seeding experiment: Case studies of preventing forest fire, drought, and dust[J]. Advances in Meteorology, 2023, 1: 5478666.
[16]	沈淑婧, 史月琴, 刘卫国, 等. 云降水和人工影响天气暖云催化数值模式研发与应用进展[J]. 地球科学进展, 2024, 39(7): 671-684. doi: 10.11867/j.issn.1001-8166.2024.055
	[Shen Shujing, Shi Yueqin, Liu Weiguo, et al. Development and application of the warm cloud seeding models in weather modification[J]. Advances in Earth Science, 2024, 39(7): 671-684.] doi: 10.11867/j.issn.1001-8166.2024.055
[17]	Sandhyavitri A, Perdana M A, Sutikno S, et al. The roles of weather modification technology in mitigation of the peat fires during a period of dry season in Bengkalis, Indonesia[C] // IOP Conference Series: Materials Science and Engineering. IOP Publishing, 2018, 309(1): 012016.
[18]	孙玉稳, 孙云, 吴志会, 等. “4. 17”森林灭火飞机增雨过程分析[J]. 中国农学通报, 2012, 28(34): 92-101.
	[Sun Yuwen, Sun Yun, Wu Zhihui, et al. Analysis of artificial rainfall effects aircraft on forest firefighting on April 17th[J]. Chinese Agricultural Science Bulletin, 2012, 28(34): 92-101.]
[19]	樊志超, 刘富来, 肖清, 等. 湖南一次重大森林火灾人工增雨作业条件与效果分析[J]. 气象与环境学报, 2019, 35(5): 100-107.
	[Fan Zhichao, Liu Fulai, Xiao Qing, et al. Analysis of the seeding conditions and effects of an artificial precipitation enhancement operations on a serious forest fire fighting in Hunan Province[J]. Journal of Meteorology and Environment, 2019, 35(5): 100-107.]
[20]	宋宁. 空地联合扑救山区森林火灾——以沂源县“4. 6”森林火灾为例[J]. 森林防火, 2023, 41(3): 59-62.
	[Song Ning. Air-ground cooperation in fighting forest fire in mountainous areas: Taking the April 6th forest fire in Yiyuan County as an example[J]. Journal of Wildland Fire Science, 2023, 41(3): 59-62.]
[21]	毛节泰, 郑国光. 对人工影响天气若干问题的探讨[J]. 应用气象学报, 2006, 21(5): 643-646.
	[Mao Jietai, Zheng Guoguang. Discussion on some weather modification issues[J]. Journal of Applied Meteorological Science, 2006, 21(5): 643-646.]
[22]	李红斌, 何玉科, 姚展予, 等. 多普勒雷达速度场特征在人工增雨作业中的判据指标应用[J]. 气象, 2008, 34(6): 102-106.
	[Li Hongbin, He Yuke, Yao Zhanyu, et al. Application of doppler radar velocity field characters to precipitation enhancement operation[J]. Meteorology Monthly, 2008, 34(6): 102-106.]
[23]	唐林, 李琼, 黎祖贤, 等. 一次积层混合云云系微物理结构数值模拟与增雨条件分析[J]. 干旱气象, 2020, 38(1): 100-108.
	[Tang Lin, Li Qiong, Li Zuxian, et al. Numerical simulation of microphysical structure of a mixed convective stratiform cloud system and analysis of seeding conditions[J]. Journal of Arid Meteorology, 2020, 38(1): 100-108.]
[24]	白婷, 黄毅梅, 樊奇. 河南一次降水天气过程人工增雨作业条件综合分析[J]. 气象, 2020, 46(12): 1633-1640.
	[Bai Ting, Huang Yimei, Fan Qi, Comprehensive analysis on the conditions of artificial precipitation enhancement during a precipitation weather process in Henan Province[J]. Meteorological Monthly, 2020, 46(12): 1633-1640.]
[25]	孙晶, 杨文霞, 周毓荃. 河北一次降水层状云系结构和增雨条件的模拟研究[J]. 高原气象, 2015, 34(6): 1699-1710. doi: 10.7522/j.issn.1000-0534.2014.00086
	[Sun Jing, Yang Wenxia, Zhou Yuquan. Numerical simulations of cloud structure and seedability of a precipitation stratiform in Hebei[J]. Plateau Meteorology, 2015, 34(6): 1699-1710.] doi: 10.7522/j.issn.1000-0534.2014.00086
[26]	丁莉, 丁元武, 唐林, 等. 湖南省飞机人工增雨预报技术研究[J]. 西南师范大学学报(自然科学版), 2021, 46(12): 63-71.
	[Ding Li, Ding Yuanwu, Tang Lin, et al. Study on forecast technology of aircraft artificial precipitation in Hunan Province[J]. Journal of Southwest Normal University (Natural Science Edition), 2021, 46(12): 63-71.]
[27]	尚博, 蔡淼, 霍也, 等. 吉林省春季人工增雨潜势及指标的数值模拟研究[J]. 气象与环境学报, 2020, 36(1): 74-81.
	[Shang Bo, Cai Miao, Huo Ye, et al. Numerical simulation analysis on the potential and index of artificial precipitation enhancement in spring in Jilin Province[J]. Journal of Meteorology and Environment, 2020, 36(1): 74-81.]
[28]	张磊, 宋哲, 徐铖, 等. 浙江省夏秋季人工增雨作业雷达指标研究[J]. 干旱气象, 2022, 40(5): 888-896. doi: 10.11755/j.issn.1006-7639(2022)-05-0888
	[Zhang Lei, Song Zhe, Xu Cheng, et al. Indexes of doppler radar echo for rainfall enhancement in summer and autumn in Zhejiang Province[J]. Journal of Arid Meteorology, 2022, 40(5): 888-896.]
[29]	孙莉娟, 徐阳, 鲁德金, 等. 雷达和GPS水汽资料在人工增雨指标中的应用[J]. 现代农业科技, 2020, 16: 160-162.
	[Sun Lijuan, Xu Yang, Lu Dejin, et al. Application of radar and GPS water vapor data in artificial precipitation enhancement indicators[J]. Modern Agricultural Science and Technology, 2020, 16: 160-162.]
[30]	雷成亮. 大兴安岭森林火烈度遥感估测方法研究[D]. 哈尔滨: 东北林业大学, 2014.
	[Lei Chengliang. Estimating Burned Severity with Multiple Methods in Da Xing’ anling Mountains[D]. Harbin: Northeast Forestry University, 2014.]
[31]	衣娜娜, 苏立娟, 郑旭程, 等. 冰雹天气的环境参量及预报模型[J]. 干旱区研究, 2024, 41(1): 13-23.
	[Yi Nana, Su Lijuan, Zheng Xucheng, et al. Environmental parameters and forecast models of hail events[J]. Arid Zone Research, 2024, 41(1): 13-23.]
[32]	郑家亨. 统计大辞典[M]. 北京: 中国统计出版社, 1995.
	[Zheng Jiaheng. Statistical Dictionary[M]. Beijing: China Statistics Press, 1995.]
[33]	黄长全. 贝叶斯统计及其R实现6(第二版)[M]. 北京: 清华大学出版社, 2023.
	[Huang Changquan. Bayesian Statistics and their R realizations 6[M]. 2nd ed. Beijing: Tsinghua University Press, 2023.]
[34]	翟菁, 黄勇, 胡雯, 等. 一次积层混合云降水过程增雨条件分析[J]. 气象, 2010, 36(11): 59-67.
	[Zhai Jing, Huang Yong, Hu Wen, et al. Analysis on conditions of precipitation enhancement catalyzing operation based on mesoscale model, CINRAD, and satellite[J]. Meteorology Monthly, 2010, 36(11): 59-67.]
[35]	蔡淼, 欧建军, 周毓荃, 等. L波段探空判别云区方法的研究[J]. 大气科学, 2014, 38(2): 213-222.
	[Cai Miao, Ou Jianjun, Zhou Yuquan, et al. Discriminating cloud area by using L-band sounding data[J]. Chinese Journal of Atmospheric Sciences, 2014, 38(2): 213-222.]

		小云粒子数浓度/（个·cm^-3）
		<65	≥65
大云粒子数浓度/（个·cm^-3）	<20	不可播	强可播
大云粒子数浓度/（个·cm^-3）	≥20	不可播	可播

	样本数/个
	强可播	可播	不可播
训练集	1571	922	1510
测试集	176	32	478

Model for predicting potential for aircraft cold cloud precipitation enhancement in Da Xing’ anling Mountains in Inner Mongolia

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	总样本数/个	Fisher		Bayes
	总样本数/个	识别样本数/个	识别率/%	识别样本数/个	识别率/%
可播	32	32	100	30	93.8
强可播	176	174	98.9	174	98.9
不可播	478	478	100	478	100

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