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Abstract:

In the last few years, there has been an increasing application of gridded precipitation data sets for studies analysing seasonal and interannual precipitation variability as well as for performing validation analysis of climate and regional models. Consequently, the purpose of the present study is to analyse the representation of temporal variability and spatial patterns of precipitation in South America for the period 1971-2010, derived by three data sets based exclusively on rain gauge information (Climate Research Unit - CRU, Global Precipitation Climatology Centre - GPCC and University of Delaware - UDel), in order to identify discrepancies and/or agreements among them. Further analysis is performed for three particular sub-regions within the continent (southern sector of southeastern South America - SSESA, central South America - CSA and southeastern Brazil - SEBR). Results show that the three products represent key spatial features of precipitation analogously. Significant coherence in capturing the temporal variability, associated with the dominant modes of variability, is found in all sub-regions, though they differ largely in some areas, especially in CSA. Overall, depending on the region, the gridded products behave differently, without one particular data set standing out as an outlier in all the analysed cases. © 2016 Royal Meteorological Society.

Registro:

Documento: Artículo
Título:A spatio-temporal comparative study of the representation of precipitation over South America derived by three gridded data sets
Autor:Gulizia, C.; Camilloni, I.
Filiación:Departamento de Ciencias de la Atmósfera y los Océanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina
Centro de Investigaciones del Mar y la Atmósfera (CIMA), Universidad de Buenos Aires-Consejo Nacional de Investigaciones Científicas y Tecnicas, Argentina
Centro de Investigaciones del Mar y la Atmósfera (CIMA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad de Buenos Aires (UBA), DCAO/FCEN, Buenos Aires, Argentina
Unidad Mixta Internacional (UMI), Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos (IFAECI), Centre National de la Recherche Scientifique (CNRS), Ciudad Universitaria, Buenos Aires, Argentina
Palabras clave:Gridded data sets; Precipitation; South America; Climate models; Gages; Precipitation (chemical); Rain; Rain gages; Global precipitation; Gridded data sets; Precipitation variability; South America; Southeastern Brazil; Southeastern South America; Temporal variability; University of Delaware; Precipitation (meteorology); comparative study; data set; precipitation assessment; spatial variation; spatiotemporal analysis; temporal variation; South America
Año:2016
Volumen:36
Número:3
Página de inicio:1549
Página de fin:1559
DOI: http://dx.doi.org/10.1002/joc.4416
Título revista:International Journal of Climatology
Título revista abreviado:Int. J. Climatol.
ISSN:08998418
CODEN:IJCLE
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_08998418_v36_n3_p1549_Gulizia

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Citas:

---------- APA ----------
Gulizia, C. & Camilloni, I. (2016) . A spatio-temporal comparative study of the representation of precipitation over South America derived by three gridded data sets. International Journal of Climatology, 36(3), 1549-1559.
http://dx.doi.org/10.1002/joc.4416
---------- CHICAGO ----------
Gulizia, C., Camilloni, I. "A spatio-temporal comparative study of the representation of precipitation over South America derived by three gridded data sets" . International Journal of Climatology 36, no. 3 (2016) : 1549-1559.
http://dx.doi.org/10.1002/joc.4416
---------- MLA ----------
Gulizia, C., Camilloni, I. "A spatio-temporal comparative study of the representation of precipitation over South America derived by three gridded data sets" . International Journal of Climatology, vol. 36, no. 3, 2016, pp. 1549-1559.
http://dx.doi.org/10.1002/joc.4416
---------- VANCOUVER ----------
Gulizia, C., Camilloni, I. A spatio-temporal comparative study of the representation of precipitation over South America derived by three gridded data sets. Int. J. Climatol. 2016;36(3):1549-1559.
http://dx.doi.org/10.1002/joc.4416