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dc.creatorAlfaro Martínez, Eric J.
dc.creatorChourio, Xandre
dc.creatorMuñoz, Ángel G.
dc.creatorMason, Simon J.
dc.date.accessioned2018-10-19T21:21:45Z
dc.date.available2018-10-19T21:21:45Z
dc.date.issued2017
dc.identifier.citationhttps://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5366es_ES
dc.identifier.issn1097-0088
dc.identifier.urihttp://hdl.handle.net/10669/76038
dc.description.abstractThis study explores the predictive skill of seasonal rainfall characteristics for the first rainy (and planting) season, May–June, in Central America. Statistical predictive models were built using a Model Output Statistics (MOS) technique based on canonical correlation analysis, in which variables that forecast with the Climate Forecast System version 2 (CFSv2) were used as candidate predictors for the observed total precipitation, frequency of rainy days and mean number of extremely dry and wet events in the season. CFSv2 initializations from February to April were explored. The CFSv2 variables used in the study consist of rainfall, as in a typical MOS technique, and a combination of low‐level winds and convective available potential energy (CAPE), a blend that has been previously shown to be a good predictor for convective activity. The highest predictive skill was found for the seasonal frequency of rainy days, followed by the mean frequency of dry events. In terms of candidate predictors, the zonal transport of CAPE (uCAPE) at 925 hPa offers higher skill across Central America than rainfall, which is attributed in part to the high model uncertainties associated with precipitation in the region. As expected, dynamical model predictors initialized in February provide lower skill than those initialized later. Nonetheless, the skill is comparable for March and April initializations. These results suggest that the National Meteorological and Hydrological Services in Central America, and the Central American Regional Climate Outlook Forum, can produce earlier more skilful forecasts for May–June rainfall characteristics than previously stated.es_ES
dc.description.sponsorshipUniversidad de Costa Rica/[805-B6-143]/UCR/Costa Ricaes_ES
dc.description.sponsorshipUniversidad de Costa Rica/[805-B7-507]/UCR/Costa Ricaes_ES
dc.description.sponsorshipUniversidad de Costa Rica/[805-B7-286]/UCR/Costa Ricaes_ES
dc.description.sponsorshipUniversidad de Costa Rica/[805-B4-227]/UCR/Costa Ricaes_ES
dc.description.sponsorshipUniversidad de Costa Rica/[805-B3-600]/UCR/Costa Ricaes_ES
dc.description.sponsorshipUniversidad de Costa Rica/[805-B0-065]/UCR/Costa Ricaes_ES
dc.description.sponsorshipUniversidad de Costa Rica/[805-A9-532]/UCR/Costa Ricaes_ES
dc.language.isoen_USes_ES
dc.relation.ispartof
dc.sourceInternational Journal of Climatology, Vol. 38(S1), pp.e255-e268es_ES
dc.subjectSeasonal climate predictiones_ES
dc.subjectPrecipitationes_ES
dc.subjectCentral Americaes_ES
dc.subjectStatistical modelses_ES
dc.subjectMOS predictive schemeses_ES
dc.subjectCanonical correlation analysises_ES
dc.subject551.6 Climatología y estado atmosféricoes_ES
dc.titleImproved seasonal prediction skill of rainfall for the Primera season in Central Americaes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2018-10-02T19:51:35Z
dc.identifier.doi10.1002/joc.5366
dc.description.procedenceUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI)es_ES
dc.identifier.codproyecto805-B6-143
dc.identifier.codproyecto805-B7-507
dc.identifier.codproyecto805-B7-286
dc.identifier.codproyecto805-B4-227
dc.identifier.codproyecto805-B3-600
dc.identifier.codproyecto805-B0-065
dc.identifier.codproyecto805-A9-532


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