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陈羿辰, 何晖. 基于偏振雷达的积层混合云降水增雨潜力识别方法研究[J]. 大气科学, 2017, 41(3): 578-592.. DOI: 10.3878/j.issn.1006-9895.1611.16171
引用本文: 陈羿辰, 何晖. 基于偏振雷达的积层混合云降水增雨潜力识别方法研究[J]. 大气科学, 2017, 41(3): 578-592.. DOI: 10.3878/j.issn.1006-9895.1611.16171
Yichen CHEN, Hui HE. A Study to Determine Enhancement Potential for Convective-Stratiform Mixed Precipitation Based on Polarimetric Radar[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(3): 578-592.. DOI: 10.3878/j.issn.1006-9895.1611.16171
Citation: Yichen CHEN, Hui HE. A Study to Determine Enhancement Potential for Convective-Stratiform Mixed Precipitation Based on Polarimetric Radar[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(3): 578-592.. DOI: 10.3878/j.issn.1006-9895.1611.16171

基于偏振雷达的积层混合云降水增雨潜力识别方法研究

A Study to Determine Enhancement Potential for Convective-Stratiform Mixed Precipitation Based on Polarimetric Radar

  • 摘要: 本文统计分析了北京地区近三年的有效降水,重点研究了积层混合云降水特点并对其分类,发现积层混合云降水出现频次约占总降水次数的61%,其中积层混合云降水以积层连结型和水平混合型为主,二者之和占近80%。重点分析了积层混合云中对流和层云两种不同特点降水类型的宏微观结构,确立了反射率因子Z、温度T、粒子含水量M、催化剂AgⅠ(碘化银)活化率NE和粒子相态HTC(hydrometeor type classification)为人工增雨潜力识别指标及这些识别指标的取值范围,同时也根据研究现状和人工影响天气需求总结制定出人工增雨潜力等级。利用偏振雷达构建模糊逻辑识别算法对积层混合云三种降水类型进行增雨潜力区域识别研究,结果表明:(1)对于播撒碘化银增雨来说,积层混合云的增雨潜力区在垂直方向上可分为上、中、下三层,上层(增雨等级为“不适合”)和下层(零度层及以下)分别受含水量和温度等影响不适合增雨,中间层(增雨等级大于等于“等级一”)是可增雨区域;(2)积层混合云中层云区增雨潜力较小,对流云区可增雨潜力要远大于层云区,开式流场型与积层连结型可增雨潜力要大于水平混合型;(3)当降水云中识别出霰粒子时,其附近的大部分区域会有较好的增雨潜力。通过偏振雷达实例检验和数值模式模拟在积层混合云不同部位播撒碘化银催化试验发现,在增雨潜力较好的区域催化有很明显增雨效果,模拟试验结论与偏振雷达识别增雨潜力区结果也基本一致,说明基于偏振雷达的增雨潜力区识别方法和结果是具有参考意义的。

     

    Abstract: Statistical analysis on effective precipitation enhancement in Beijing area over the past three years was conducted. Characteristics and classification of convective-stratiform mixed clouds were also studied in this paper. Results show that the frequency of mixed clouds precipitation accounted for 61% of the total frequency. Convective-stratiform connected type and horizontally mixed type are the main types of mixed clouds precipitation and the two types of precipitation account for 80% of the total. This study mainly analyzed the macro-and micro-physical structures of convective clouds and stratus clouds in convective-stratiform mixed clouds. Identification indexes, including the reflectivity factor Z, temperature T, particle water content M, AgⅠ nucleation efficiency (NE), hydrometeor type classification (HTC), and their ranges were determined. Levels of rain enhancement potential were established based on the research situation and weather modification demands. Fuzzy models and algorithms based on polarimetric radar data were established to identify regions of rain enhancement potential for convective-stratiform precipitation. The results show that three layers in the vertical (upper, middle, and lower) could be found in the rain enhancement potential area. Both the upper and lower layers are not suitable for artificial rain enhancement because of the influence of water content and temperature. Thereby only the middle layer is fit for artificial rain enhancement. It was also found that the stratus clouds in the mixed clouds have a small rain enhancement potential, whereas the convection clouds have a large potential. Of different types, the open airflow type and convective-stratiform connected type have a higher potential for artificial rain enhancement than the horizontally mixed type. Furthermore, when graupels are detected by radar, the nearby areas will have a large potential for artificial rain enhancement. Cloud seeding with AgⅠ in different layers was simulated using a numerical model. The result of the numerical model is basically consistent with the result of radar detection. This indicates that the identification method based on polarimetric radar has great implication for assessing artificial rain enhancement potential.

     

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