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dc.contributor.author Moya Álvarez, Aldo Saturnino
dc.contributor.author Gálvez, José
dc.contributor.author Holguín, Andrea
dc.contributor.author Estevan, René
dc.contributor.author Kumar, Shailendra
dc.contributor.author Villalobos Puma, Elver Edmundo
dc.contributor.author Martínez Castro, Daniel
dc.contributor.author Silva Vidal, Yamina
dc.date.accessioned 2019-01-03T17:04:09Z
dc.date.available 2019-01-03T17:04:09Z
dc.date.issued 2018-09-18
dc.identifier.citation Moya-Álvarez, A., Gálvez, J., Holguín, A., Estevan, R., Kumar, S., Villalobos, E., ... Silva, Y. (2018). Extreme rainfall forecast with the WRF-ARW model in the Central Andes of Peru. Atmosphere, 9(9), 362. es_ES
dc.identifier.govdoc index-oti2018
dc.identifier.uri http://repositorio.igp.gob.pe/handle/IGP/3921
dc.description En: Atmosphere 2018, 9(9), 362.
dc.description.abstract The ability of the WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to forecast extreme rainfall in the Central Andes of Peru is evaluated in this study, using observations from stations located in the Mantaro basin and GOES (Geostationary Operational Environmental Satellite) images. The evaluation analyzes the synoptic conditions averaged over 40 extreme event cases, and considers model simulations organized in 4 nested domains. We first establish that atypical events in the region are those with more than 27 mm of rainfall per day when averaging over all the stations. More than 50% of the selected cases occurred during January, February, and April, with the most extreme occurring during February. The average synoptic conditions show negative geopotential anomalies and positive humidity anomalies in 700 and 500 hPa. At 200 hPa, the subtropical upper ridge or “Bolivian high” was present, with its northern divergent flank over the Mantaro basin. Simulation results show that the Weather Research and Forecasting (WRF) model underestimates rainfall totals in approximately 50–60% of cases, mainly in the south of the basin and in the extreme west along the mountain range. The analysis of two case studies shows that the underestimation by the model is probably due to three reasons: inability to generate convection in the upstream Amazon during early morning hours, apparently related to processes of larger scales; limitations on describing mesoscale processes that lead to vertical movements capable of producing extreme rainfall; and limitations on the microphysics scheme to generate heavy rainfall. es_ES
dc.format application/pdf es_ES
dc.language.iso eng es_ES
dc.publisher MDPI es_ES
dc.rights info:eu-repo/semantics/closedAccess es_ES
dc.source Repositorio institucional - IGP es_ES
dc.subject Precipitación es_ES
dc.subject Precipitación--Andes centrales es_ES
dc.subject Pronósticos meteorológicos es_ES
dc.subject Modelo WRF es_ES
dc.subject Investigación del Clima es_ES
dc.title Extreme Rainfall Forecast with the WRF-ARW Model in the Central Andes of Peru es_ES
dc.type info:eu-repo/semantics/article es_ES
dc.subject.ocde Meteorología y Ciencias Atmosféricas es_ES
dc.subject.ocde Investigación del Clima es_ES
dc.subject.ocde Oceanografía, Hidrología y Recursos del Agua es_ES
dc.identifier.journal Atmosphere es_ES
dc.identifier.doi http://dx.doi.org/10.3390/atmos9090362 es_ES

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