Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-407-2024
https://doi.org/10.5194/amt-17-407-2024
Research article
 | 
19 Jan 2024
Research article |  | 19 Jan 2024

Radar and environment-based hail damage estimates using machine learning

Luis Ackermann, Joshua Soderholm, Alain Protat, Rhys Whitley, Lisa Ye, and Nina Ridder

Related authors

Contributions of the synoptic meteorology to the seasonal cloud condensation nuclei cycle over the Southern Ocean
Tahereh Alinejadtabrizi, Yi Huang, Francisco Lang, Steven Siems, Michael Manton, Luis Ackermann, Melita Keywood, Ruhi Humphries, Paul Krummel, Alastair Williams, and Greg Ayers
Atmos. Chem. Phys., 25, 2631–2648, https://doi.org/10.5194/acp-25-2631-2025,https://doi.org/10.5194/acp-25-2631-2025, 2025
Short summary
On the relationship between mesoscale cellular convection and meteorological forcing: comparing the Southern Ocean against the North Pacific
Francisco Lang, Steven T. Siems, Yi Huang, Tahereh Alinejadtabrizi, and Luis Ackermann
Atmos. Chem. Phys., 24, 1451–1466, https://doi.org/10.5194/acp-24-1451-2024,https://doi.org/10.5194/acp-24-1451-2024, 2024
Short summary
Strong wintertime ozone events in the Upper Green River basin, Wyoming
B. Rappenglück, L. Ackermann, S. Alvarez, J. Golovko, M. Buhr, R. A. Field, J. Soltis, D. C. Montague, B. Hauze, S. Adamson, D. Risch, G. Wilkerson, D. Bush, T. Stoeckenius, and C. Keslar
Atmos. Chem. Phys., 14, 4909–4934, https://doi.org/10.5194/acp-14-4909-2014,https://doi.org/10.5194/acp-14-4909-2014, 2014

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
TanSat-2: a new satellite for mapping solar-induced chlorophyll fluorescence at both red and far-red bands with high spatiotemporal resolution
Dianrun Zhao, Shanshan Du, Chu Zou, Longfei Tian, Meng Fan, Yulu Du, and Liangyun Liu
Atmos. Meas. Tech., 18, 3647–3667, https://doi.org/10.5194/amt-18-3647-2025,https://doi.org/10.5194/amt-18-3647-2025, 2025
Short summary
Propagating information content: an example with advection
David D. Turner, Maria P. Cadeddu, Julia M. Simonson, and Timothy J. Wagner
Atmos. Meas. Tech., 18, 3533–3546, https://doi.org/10.5194/amt-18-3533-2025,https://doi.org/10.5194/amt-18-3533-2025, 2025
Short summary
Best estimate of the planetary boundary layer height from multiple remote sensing measurements
Damao Zhang, Jennifer Comstock, Chitra Sivaraman, Kefei Mo, Raghavendra Krishnamurthy, Jingjing Tian, Tianning Su, Zhanqing Li, and Natalia Roldán-Henao
Atmos. Meas. Tech., 18, 3453–3475, https://doi.org/10.5194/amt-18-3453-2025,https://doi.org/10.5194/amt-18-3453-2025, 2025
Short summary
Observing atmospheric rivers using multi-GNSS airborne radio occultation: system description and data evaluation
Bing Cao, Jennifer S. Haase, Michael J. Murphy Jr., and Anna M. Wilson
Atmos. Meas. Tech., 18, 3361–3392, https://doi.org/10.5194/amt-18-3361-2025,https://doi.org/10.5194/amt-18-3361-2025, 2025
Short summary
Evolution of wind field in the atmospheric boundary layer using multiple-source observations during the passage of Super Typhoon Doksuri (2305)
Xiaoye Wang, Jing Xu, Songhua Wu, Qichao Wang, Guangyao Dai, Peizhi Zhu, Zhizhong Su, Sai Chen, Xiaomeng Shi, and Mengqi Fan
Atmos. Meas. Tech., 18, 3305–3320, https://doi.org/10.5194/amt-18-3305-2025,https://doi.org/10.5194/amt-18-3305-2025, 2025
Short summary

Cited articles

Allen, J. T. and Tippett, M. K.: The Characteristics of United States Hail Reports: 1955–2014, E-Journal of Severe Storms Meteorology, 10, 1–31, https://doi.org/10.55599/EJSSM.V10I3.60, 2015. a
Blong, R.: Residential building damage and natural perils: Australian examples and issues, Build. Res. Inf., 32, 379–390, https://doi.org/10.1080/0961321042000221007, 2007. a
Brook, J. P., Protat, A., Soderholm, J., Carlin, J. T., McGowan, H., and Warren, R. A.: HailTrack–Improving Radar-Based Hailfall Estimates by Modeling Hail Trajectories, J. Appl. Meteorol. Clim., 60, 237–254, https://doi.org/10.1175/JAMC-D-20-0087.1, 2021. a, b, c, d
Brook, J. P., Protat, A., Soderholm, J. S., Warren, R. A., and McGowan, H.: A Variational Interpolation Method for Gridding Weather Radar Data, J. Atmos. Ocean. Tech., 39, 1633–1654, https://doi.org/10.1175/JTECH-D-22-0015.1, 2022. a, b
Download
Short summary
The paper addresses the crucial topic of hail damage quantification using radar observations. We propose a new radar-derived hail product that utilizes a large dataset of insurance hail damage claims and radar observations. A deep neural network was employed, trained with local meteorological variables and the radar observations, to better quantify hail damage. Key meteorological variables were identified to have the most predictive capability in this regard.
Share