A high-resolution divergence and vorticity  dataset in Beijing derived from radar  wind profiler mesonet measurements

Guo, Xiaoran; Guo, Jianping; Meng, Deli; Sun, Yuping; Zhang, Zhen; Xu, Hui; Zeng, Liping; Chen, Juan; Li, Ning; Chen, Tianmeng

doi:https://doi.org/10.5194/essd-17-3541-2025

Articles | Volume 17, issue 7

https://doi.org/10.5194/essd-17-3541-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-17-3541-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 7

Data description paper

|

24 Jul 2025

Data description paper |

| 24 Jul 2025

A high-resolution divergence and vorticity dataset in Beijing derived from radar wind profiler mesonet measurements

Xiaoran Guo, Jianping Guo, Deli Meng, Yuping Sun, Zhen Zhang, Hui Xu, Liping Zeng, Juan Chen, Ning Li, and Tianmeng Chen

Data sets

A temporally continuous divergence and vorticity dataset in Beijing derived from the radar wind profiler mesonet during 2023 Jianping Guo and Xiaoran Guo https://doi.org/10.5281/zenodo.15297246

ERA5 hourly data on pressure levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.bd0915c6

Short summary

Optimal atmospheric dynamic conditions are essential for convective storms. This study generates a dataset of high-resolution divergence and vorticity profiles using the measurements of a radar wind profiler mesonet in Beijing. The negative divergence and positive vorticity are present ahead of rainfall events. This suggests that this dataset can help improve our understanding of the pre-storm environment and has the potential to be applied in weather forecasting.