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dc.contributor.authorValdívia, Jairo M.
dc.contributor.authorFlores-Rojas, José Luis
dc.contributor.authorPrado, Josep J.
dc.contributor.authorGuizado, David
dc.contributor.authorVillalobos-Puma, Elver
dc.contributor.authorCallañaupa, Stephany
dc.contributor.authorSilva-Vidal, Yamina
dc.date.accessioned2024-06-20T21:01:52Z
dc.date.available2024-06-20T21:01:52Z
dc.date.issued2024
dc.identifier.citationValdivia, J. M., Flores-Rojas, J. L., Prado, J. J., Guizado, D., Villalobos-Puma, E., Callañaupa, S., and Silva-Vidal, Y. (2024). 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-17-2295-2024es_PE
dc.identifier.issn1867-1381
dc.identifier.urihttps://hdl.handle.net/20.500.12542/3406
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.es_PE
dc.formatapplication/pdfes_PE
dc.language.isospaes_PE
dc.publisherEuropean Geosciences Uniones_PE
dc.relation.urihttps://amt.copernicus.org/articles/17/2295/2024/amt-17-2295-2024.htmles_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.sourceRepositorio Institucional - SENAMHIes_PE
dc.sourceServicio Nacional de Meteorología e Hidrología del Perúes_PE
dc.subjectGranizoes_PE
dc.subjectAndeses_PE
dc.subjectClimatologíaes_PE
dc.titleHailstorm events in the Central Andes of Peru: Insights from historical data and radar microphysicses_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.doihttps://doi.org/10.5194/amt-17-2295-2024
dc.identifier.journalAtmospheric Measurement Techniqueses_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.05.09es_PE
dc.publisher.countryPEes_PE
dc.subject.siniavariabilidad climatica - Clima y Eventos Naturaleses_PE
dc.type.siniatext/publicacion cientificaes_PE
dc.identifier.urlhttps://hdl.handle.net/20.500.12542/3406
dc.identifier.urlhttps://hdl.handle.net/20.500.12542/3406


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