熊婧媛,刘晓莉,王静,楚志刚. 2024. 河北省一次层状云冰相粒子及融化层微物理特性研究. 气象学报,82(1):95-112. DOI: 10.11676/qxxb2024.20230120
引用本文: 熊婧媛,刘晓莉,王静,楚志刚. 2024. 河北省一次层状云冰相粒子及融化层微物理特性研究. 气象学报,82(1):95-112. DOI: 10.11676/qxxb2024.20230120
Xiong Jingyuan, Liu Xiaoli, Wang Jing, Chu Zhigang. 2024. Aircraft observed microphysical evolution of ice particles and melting layer in the stratiform clouds on 24 August 2019 over Hebei province, China. Acta Meteorologica Sinica, 82(1):95-112. DOI: 10.11676/qxxb2024.20230120
Citation: Xiong Jingyuan, Liu Xiaoli, Wang Jing, Chu Zhigang. 2024. Aircraft observed microphysical evolution of ice particles and melting layer in the stratiform clouds on 24 August 2019 over Hebei province, China. Acta Meteorologica Sinica, 82(1):95-112. DOI: 10.11676/qxxb2024.20230120

河北省一次层状云冰相粒子及融化层微物理特性研究

Aircraft observed microphysical evolution of ice particles and melting layer in the stratiform clouds on 24 August 2019 over Hebei province, China

  • 摘要: 层状云中冰粒子、融化层及以下粒子微物理特性演变规律的科学认识对于中国云降水参数化、降水预报及人工影响天气研究具有重要意义。利用2019年8月24日河北省一次层状云飞机观测资料,分析云中负温层、融化层及以下粒子群微物理特性的演变。研究表明,云中负温层冰相粒子以聚合体为主,部分区域存在霰粒子。云中冰相粒子通过凇附、碰连和贝吉龙过程增长。相对来说,上升气流较强及相对湿度较高云区的冰相粒子数浓度较高、粒子谱较宽。融化层中,中等大小粒子数浓度存在增大趋势,说明融化层中不同粒径冰相粒子的融化速率存在差异。研究发现,高相对湿度区(RH≥95%)粒子融化速率较低相对湿度区(RH<95%)快,低相对湿度区中表面融化的粒子蒸发吸收潜热,使环境温度降低,减缓粒子融化速率。融化层高相对湿度区降水粒子谱分布的截距大于低相对湿度区,斜率与低相对湿度区接近。融化层降水粒子负指数谱分布的截距与斜率均大于负温层,0℃层高度以下HVPS探测到的粒子谱分布参数 N_0 λ呈正相关,线性函数能较好地拟合二者的关系。对于 D_\mathrmm\mathrma\mathrmx 大于1000 μm的降水粒子,谱参数λ D_\mathrmm\mathrma\mathrmx 呈负相关,幂函数能较好地拟合二者的关系。数值研究发现,0℃层之下云内存在混合相态粒子,观测和模拟结果均发现0℃层之下中等大小的粒子数浓度更高。分档方案数值模拟得到的降水粒子平均谱的截距与观测资料一致,但斜率大于观测结果。研究结合飞机观测资料与模式,对云内融化层中粒子微物理特性有了更加深入的认识。

     

    Abstract: Scientific understanding of evolution of microphysical properties of ice particles in the melting layer and below for stratified clouds is of great significance for the development of cloud precipitation parameterization, precipitation forecast and weather modification in China. Based on aircraft observations of stratiform clouds in Hebei province on 24 August 2019, the evolution of microphysical properties of particles in negative temperature cloud layers and below the melting layer are analyzed. The study shows that ice particles in the negative temperature layer in the cloud are mainly aggregates, and graupel particles exist in some areas. In the melting layer, the concentration of medium sized particles (600—1500 μm) increases, indicating that the melting rates of ice phase particles with different sizes are different. It is found that the melting rate of particles in the region of high relative humidity (RH≥95%) is faster than that in the region of low relative humidity (RH<95%). In the region of low relative humidity, surface melting on particles leads to evaporation and latent heat absorption, which reduce ambient temperature and slow down the melting rate of particles. The intercept of precipitation particle spectrum distribution in the melting layer of high relative humidity area is larger than that in the low relative humidity area and the slope is similar to that in the low relative humidity area. It is found that the intercept and slope of the negative exponential spectrum distribution of precipitation particles in the melting layer are greater than those in the negative temperature layer. The particle spectrum distribution parameter N_0 detected by HVPS below 0℃ layer is positively correlated with λ, and the linear function can better fit the relationship between them. For precipitation particles whose D_\mathrmm\mathrma\mathrmx is Larger than 1000 μm, λ is negatively correlated with D_\mathrmm\mathrma\mathrmx , and the power function can fit their relationship well. Numerical simulation results show that there are mixed phase particles in the cloud below the 0℃ layer, and observations and simulations show that the medium particle number concentration is higher below the 0℃ layer. The intercept of precipitation particle mean spectrum in the classification scheme is consistent with observations, but the slope is greater than the observed result. In this work, the microphysical characteristics of particles in the melting layer in the cloud have been more deeply understood by combining aircraft observations and model simulations.

     

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