Articles | Volume 17, issue 8
https://doi.org/10.5194/essd-17-3721-2025
https://doi.org/10.5194/essd-17-3721-2025
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

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Revised manuscript accepted for ESSD
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Cited articles

Adams-Selin, R. D. and Johnson, R. H.: Mesoscale surface pressure and temperature features associated with bow echoes, Mon. Weather Rev., 138, 212–227, https://doi.org/10.1175/2009MWR2892.1, 2010. 
Ardon-Dryer, K., Gill, T. E., and Tong, D. Q.: When a Dust Storm Is Not a Dust Storm: Reliability of Dust Records From the Storm Events Database and Implications for Geohealth Applications, GeoHealth, 7, e2022GH000699, https://doi.org/10.1029/2022GH000699, 2023. 
Ashley, W. S. and Mote, T. L.: Derecho hazards in the United States, B. Am. Meteorol. Soc., 86, 1577–1592, https://doi.org/10.1175/BAMS-86-11-1577, 2005. 
Bardis, M., Houshyar, R., Chantaduly, C., Ushinsky, A., Glavis-Bloom, J., Shaver, M., Chow, D., Uchio, E., and Chang, P.: Deep learning with limited data: Organ segmentation performance by U-Net, Electronics, 9, 1199, https://doi.org/10.3390/electronics9081199, 2020. 
Bentley, M. L. and Mote, T. L.: A climatology of derecho-producing mesoscale convective systems in the central and eastern United States, 1986–95. Part I: Temporal and spatial distribution, B. Am. Meteorol. Soc., 79, 2527–2540, https://doi.org/10.1175/1520-0477(1998)079<2527:ACODPM>2.0.CO;2, 1998. 
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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.
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