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dc.contributor.authorMendoza Siguenza, Daniel Emilio
dc.contributor.authorSamaniego Alvarado, Esteban Patricio
dc.contributor.authorMora Serrano, Diego Esteban
dc.contributor.authorEspinoza Mejia, Jorge Mauricio
dc.contributor.authorCampozano Parra, Lenin Vladimir
dc.date.accessioned2019-03-13T20:50:37Z-
dc.date.available2019-03-13T20:50:37Z-
dc.date.issued2019
dc.identifier.issn0930-7575
dc.identifier.urihttps://link.springer.com/article/10.1007/s00382-018-4400-3
dc.descriptionGlobal climate is a multi-scale system whose subsystems interact complexly. Notably, the Tropical-Andean region has a strong rainfall variability because of the confluence of many global climate processes altered by morphological features. An approach for a synthetical climate description is the use of global indicators and their regional teleconnections. However, typically this is carried out using filters and correlations, which results in seasonal and inter-annual teleconnections information, which are difficult to integrate into a modeling framework. A new methodology, based on rainfall signal extraction using dynamic-harmonic-regressions (DHR) and stochastic-multiple-linear-regressions (SMLR) between rainfall components and global signals for searching intra-annual and inter-annual teleconnections, is proposed. DHR gives non-stationary inter-annual trends and intra-annual quasi-periodic oscillations for monthly rainfall measurements. Time-variable amplitudes of quasi-periodical oscillations are crucial for finding intra-annual teleconnections using SMLR, while trends are better suited for the case of inter-annual ones. The methodology is tested over a Tropical-Andean region in southern Ecuador. The following results were obtained: (1) trans-Niño-Index (TNI) and Tropical-South-Atlantic signals are strongly connected to inter-annual and intra-annual time-scales. (2) However, TNI progressively weakens its relation with intra-annual components; meanwhile, El-Niño-Southern-Oscillation 3 gains ground for such time-scales. (3) Finally, an inter-annual connection with the North-Atlantic-Oscillation (NAO) is revealed. These results are consistent with previous literature, although the TNI and NAO connections are interesting findings, taking into account the differences in the connected scales. These results show the methodology’s capability of unraveling global teleconnections in different space and time scales using attributes embedded in an integral mathematical framework, which could be interesting for other purposes—such as the analysis of climate mechanisms or climate modeling. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
dc.description.abstractGlobal climate is a multi-scale system whose subsystems interact complexly. Notably, the Tropical-Andean region has a strong rainfall variability because of the confluence of many global climate processes altered by morphological features. An approach for a synthetical climate description is the use of global indicators and their regional teleconnections. However, typically this is carried out using filters and correlations, which results in seasonal and inter-annual teleconnections information, which are difficult to integrate into a modeling framework. A new methodology, based on rainfall signal extraction using dynamic-harmonic-regressions (DHR) and stochastic-multiple-linear-regressions (SMLR) between rainfall components and global signals for searching intra-annual and inter-annual teleconnections, is proposed. DHR gives non-stationary inter-annual trends and intra-annual quasi-periodic oscillations for monthly rainfall measurements. Time-variable amplitudes of quasi-periodical oscillations are crucial for finding intra-annual teleconnections using SMLR, while trends are better suited for the case of inter-annual ones. The methodology is tested over a Tropical-Andean region in southern Ecuador. The following results were obtained: (1) trans-Niño-Index (TNI) and Tropical-South-Atlantic signals are strongly connected to inter-annual and intra-annual time-scales. (2) However, TNI progressively weakens its relation with intra-annual components; meanwhile, El-Niño-Southern-Oscillation 3 gains ground for such time-scales. (3) Finally, an inter-annual connection with the North-Atlantic-Oscillation (NAO) is revealed. These results are consistent with previous literature, although the TNI and NAO connections are interesting findings, taking into account the differences in the connected scales. These results show the methodology’s capability of unraveling global teleconnections in different space and time scales using attributes embedded in an integral mathematical framework, which could be interesting for other purposes—such as the analysis of climate mechanisms or climate modeling. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
dc.language.isoes_ES
dc.sourceClimate Dynamics
dc.subjectENSO 3
dc.subjectInter-annual-scales
dc.subjectIntra-annual-scales
dc.subjectNorth-Atlantic-Oscillation
dc.subjectStochastic-multiple-linear-regressions
dc.subjectTrans-Index
dc.subjectTropical-South-Atlantic
dc.titlefinding teleconnections from decomposed rainfall signals using dynamic harmonic regressions: a tropical andean case study
dc.typeARTÍCULO
dc.ucuenca.idautor0103901070
dc.ucuenca.idautor0102052594
dc.ucuenca.idautor0102423506
dc.ucuenca.idautor0102778818
dc.ucuenca.idautor0102677200
dc.identifier.doi10.1007/s00382-018-4400-3
dc.ucuenca.versionVersión publicada
dc.ucuenca.areaconocimientounescoamplio05 - Ciencias Físicas, Ciencias Naturales, Matemáticas y Estadísticas
dc.ucuenca.afiliacionMendoza, D., Universidad de Cuenca, Facultad de Ingeniería, Cuenca, Ecuador; Mendoza, D., Universidad de Cuenca, Departamento de Ingeniería Civil, Cuenca, Ecuador
dc.ucuenca.afiliacionSamaniego, E., Universidad de Cuenca, Facultad de Ingeniería, Cuenca, Ecuador; Samaniego, E., Universidad de Cuenca, Departamento de Recursos Hídricos y Ciencias Ambientales, Cuenca, Ecuador
dc.ucuenca.afiliacionMora, D., Universidad de Cuenca, Departamento de Ingeniería Civil, Cuenca, Ecuador
dc.ucuenca.afiliacionEspinoza, J., Universidad de Cuenca, Departamento de Ciencias de la Computación, Cuenca, Ecuador
dc.ucuenca.afiliacionCampozano, L., Universidad de Cuenca, Departamento de Recursos Hídricos y Ciencias Ambientales, Cuenca, Ecuador; Campozano, L., Universidad de Cuenca, Facultad de Ingeniería, Cuenca, Ecuador
dc.ucuenca.volumenvol.52 , no. 7-8
dc.ucuenca.indicebibliograficoSCOPUS
dc.ucuenca.factorimpacto2.445
dc.ucuenca.cuartilQ1
dc.ucuenca.numerocitaciones0
dc.ucuenca.areaconocimientofrascatiamplio1. Ciencias Naturales y Exactas
dc.ucuenca.areaconocimientofrascatiespecifico1.5 Ciencias de la Tierra y el Ambiente
dc.ucuenca.areaconocimientofrascatidetallado1.5.8 Ciencias del Medioambiente
dc.ucuenca.areaconocimientounescoespecifico052 - Medio Ambiente
dc.ucuenca.areaconocimientounescodetallado0521 - Ciencias Ambientales
dc.ucuenca.urifuentehttps://link.springer.com/journal/volumesAndIssues/382
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