Hailstorm events in the Central Andes of Peru: insights from historical data and radar microphysics

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dc.contributor.authorJairo M. Valdivia
dc.contributor.authorJosé Luis Flores-Rojas
dc.contributor.authorJosep J. Prado
dc.contributor.authorDavid Guizado
dc.contributor.authorElver Villalobos-Puma
dc.contributor.authorStephany Callañaupa
dc.contributor.authorYamina Silva-Vidal
dc.date.accessioned2026-07-22T15:59:37Z
dc.date.available2026-07-22T15:59:37Z
dc.date.issued2024-04-18
dc.description.abstractHailstorms, while fascinating from a meteorological perspective, pose significant risks to communities, agriculture, and infrastructure. In regions such as the Central Andes of Peru, the characteristics and frequency of these extreme weather events remain largely uncharted. This study fills this gap by investigating the historical frequency and vertical structure of hailstorms in this region. We analyzed historical hailstorm records dating back to 1958 alongside 4 years of observations (2017–2021) from the Parsivel2 disdrometer and a cloud-profiling radar MIRA35c. Our findings indicate a trend of decreasing hail frequency (−0.5 events per decade). However, the p value of 0.07 suggests the need for further investigation, particularly in relation to environmental changes and reporting methods. The results show that hailstorms predominantly occur during the austral summer months, with peak frequency in December, and are most common during the afternoon and early evening hours. The analysis of radar variables such as reflectivity, radial velocity, spectral width, and linear depolarization ratio (LDR) reveals distinct vertical profiles for hail events. Two case studies highlight the diversity in the radar measurements of hailstorms, underscoring the complexity of accurate hail detection. This study suggests the need for refining the Parsivel2 algorithm and further understanding its classification of hydrometeors. Additionally, the limitations of conventional radar variables for hail detection are discussed, recommending the use of LDR and Doppler spectrum analysis for future research. Our findings lay the groundwork for the development of more efficient hail detection algorithms and improved understanding of hailstorms in the Central Andes of Peru.
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dc.identifier.citationValdivia, J. M., Flores-Rojas, J. L., Prado, J. J., Guizado, D., Villalobos-Puma, E., Callañaupa, S., and Silva-Vidal, Y.: Hailstorm events in the Central Andes of Peru: insights from historical data and radar microphysics, Atmos. Meas. Tech., 17, 2295–2316, https://doi.org/10.5194/amt-17-2295-2024, 2024.
dc.identifier.doi10.5194/amt-17-2295-2024
dc.identifier.issn1867-8548
dc.identifier.urihttps://hdl.handle.net/20.500.12748/681
dc.language.isospa
dc.publisherCopernicus GmbH
dc.relation.ispartofAtmospheric Measurement Techniques
dc.relation.urihttps://doi.org/10.5194/amt-17-2295-2024
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourcehttps://doi.org/10.5194/amt-17-2295-2024
dc.subjectHailstorm events
dc.subjectAndes
dc.subjectradar microphysics
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.00.00
dc.titleHailstorm events in the Central Andes of Peru: insights from historical data and radar microphysics
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
oaire.citation.issue8
oaire.citation.volume17

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