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dc.contributor.author
Antico, Andres
dc.contributor.author
Schlotthauer, Gaston
dc.contributor.author
Torres, Maria Eugenia
dc.date.available
2019-10-15T21:48:58Z
dc.date.issued
2014-02
dc.identifier.citation
Antico, Andres; Schlotthauer, Gaston; Torres, Maria Eugenia; Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin; American Geophysical Union; Journal of Geophysical Research; 119; 3; 2-2014; 1218-1233
dc.identifier.issn
2169-8996
dc.identifier.uri
http://hdl.handle.net/11336/85993
dc.description.abstract
The current understanding of hydroclimatic processes is largely based on time series analysis of observations such as river discharge. Although records of these variables are often nonlinear and nonstationary, they have been commonly analyzed by classical methods designed for linear and/or stationary data. This study investigates the possibility of analyzing hydroclimatic time series using a novel data-driven method named Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), which is suitable for nonlinear and nonstationary signals. CEEMDAN is here applied to a monthly mean discharge record (1904–2010) of the Paraná River (South America). The results obtained in this way are interpreted by comparing them with CEEMDAN decompositions of other records such as climate index time series. It is found that Paraná flow modes consist of (i) annual and intraannual oscillations reflecting the rainfall seasonality of different Paraná Basin sectors, and (ii) interannual to interdecadal changes linked to climate cycles like El Niño/Southern Oscillation, the North Atlantic Oscillation, and the Interdecadal Pacific Oscillation. A nonlinear trend of Paraná discharge is found and reveals a monotonic increase that could be attributed to global warming and anthropogenic land-cover changes. The spectral separation of modes obtained using CEEMDAN is cleaner than that achieved by the Ensemble Empirical Mode Decomposition technique. This makes it easier to interpret CEEMDAN results. Hence, CEEMDAN is proposed as a powerful method for extracting physically meaningful information from hydroclimatic data.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Geophysical Union
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Empirical Mode Decomposition
dc.subject
Complete EEMD with Adaptive Noise
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Nonlinear Trends
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Paraná River
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Hydroclimatic Variability
dc.subject.classification
Investigación Climatológica
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Ciencias de la Tierra y relacionadas con el Medio Ambiente
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-10-10T17:50:26Z
dc.journal.volume
119
dc.journal.number
3
dc.journal.pagination
1218-1233
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Antico, Andres. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina
dc.description.fil
Fil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina
dc.description.fil
Fil: Torres, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina
dc.journal.title
Journal of Geophysical Research
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1002/2013JD020420
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013JD020420
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