A derecho climatology (2004–2021) in the United States based on machine learning identification of bow echoes

Li, Jianfeng; Geiss, Andrew; Feng, Zhe; Leung, L. Ruby; Qian, Yun; Cui, Wenjun

doi:https://doi.org/10.5194/essd-17-3721-2025

Articles | Volume 17, issue 8

https://doi.org/10.5194/essd-17-3721-2025

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

https://doi.org/10.5194/essd-17-3721-2025

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

Articles | Volume 17, issue 8

Data description paper

|

04 Aug 2025

Data description paper |

| 04 Aug 2025

A derecho climatology (2004–2021) in the United States based on machine learning identification of bow echoes

Jianfeng Li, Andrew Geiss, Zhe Feng, L. Ruby Leung, Yun Qian, and Wenjun Cui

Supplement

https://doi.org/10.5194/essd-17-3721-2025-supplement

Data sets

A derecho climatology over the United States from 2004 to 2021 Jianfeng Li et al. https://doi.org/10.5281/zenodo.14835362

Bow echo detection and segmentation Andrew Geiss et al. https://doi.org/10.5281/zenodo.10822721

Video supplement

Detection of bow echoes associated with mesoscale convective systems for June 2010 Andrew Geiss https://youtu.be/iHWY_OhaVUo

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Short summary

We developed a high-resolution (4 km and hourly) observational derecho dataset over the United States east of the Rocky Mountains from 2004 to 2021 by using a mesoscale convective system dataset, bow echoes detected by a machine learning method, hourly gust speeds, and physically based identification criteria.