Analysis of insoluble particles in hailstones in China

Zhang, Haifan; Lin, Xiangyu; Zhang, Qinghong; Bi, Kai; Ng, Chan-Pang; Ren, Yangze; Xue, Huiwen; Chen, Li; Chang, Zhuolin

doi:https://doi.org/10.5194/acp-23-13957-2023

Articles | Volume 23, issue 21

https://doi.org/10.5194/acp-23-13957-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-23-13957-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 21

Research article

|

09 Nov 2023

Research article |

| 09 Nov 2023

Analysis of insoluble particles in hailstones in China

Haifan Zhang, Xiangyu Lin, Qinghong Zhang, Kai Bi, Chan-Pang Ng, Yangze Ren, Huiwen Xue, Li Chen, and Zhuolin Chang

Data sets

ERA5 hourly data on single levels from 1959 to present, ERA5 hourly data on single levels from 1940 to present H. Hersbach, B. Bell, P. Berrisford, G. Biavati, A. Horányi, J. Muñoz Sabater, J. Nicolas, C. Peubey, R. Radu, I. Rozum, D. Schepers, A. Simmons, C. Soci, D., Dee, and J.-N. Thépaut https://doi.org/10.24381/cds.adbb2d47

Model code and software

Deep Learning Toolbox Documentation The MathWorks, Inc. https://ww2.mathworks.cn/help/deeplearning/index.html

Short summary

This work is the first study to simultaneously analyze the number concentrations and species of insoluble particles in hailstones. The size distribution of insoluble particles for each species vary greatly in different hailstorms but little in shells. Two classic size distribution modes of organics and dust were fitted for the description of insoluble particles in deep convection. Combining this study with future experiments will lead to refinement of weather and climate models.