English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/127105
Compartir / Impacto:
Estadísticas
Add this article to your Mendeley library MendeleyBASE
Citado 6 veces en Web of Knowledge®  |  Ver citas en Google académico
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar otros formatos: Exportar EndNote (RIS)Exportar bibText (RIS)Exportar csv (RIS)
Título

Bias in the variance of gridded data sets leads to misleading conclusions about changes in climate variability

Autor Beguería, Santiago ; Vicente Serrano, Sergio M. ; Tomás-Burguera, Miquel ; Maneta, Marco
Fecha de publicación 2016
EditorJohn Wiley & Sons
Citación Beguería S, Vicente-Serrano SM, Tomás-Burguera M, Maneta M. Bias in the variance of gridded data sets leads to misleading conclusions about changes in climate variability 36 (9): 3413-3422 (2016)
ResumenMany studies addressing climate change and climate variability over large regions rely on gridded data. Grids are preferred to station-based data sets because they help avoiding bias arising from the irregular spatial distribution of the observations. However, while spatial interpolation techniques used for constructing gridded data are good at preserving the mean of the data, they do not offer an adequate representation of their variance. In fact, the grid's variance depends largely on the spatial density of observations used for constructing it. Most global and regional climate data sets are characterized by large temporal changes in the number of observations available for interpolation, with a strong reduction in the last 30 years. These changes in the sample size result in changes in the variance of gridded data that are merely an effect of the interpolation process, and ignoring this fact may lead to erroneous conclusions about changes in climate variability and extremes. We discuss this problem and we demonstrate its importance with a widely used global dataset of temperature and precipitation. We propose to move from interpolation techniques towards statistical simulation approaches that provide a better representation of climate variability when constructing climatic grids.
Descripción 10 Pags.- 10 Figs. The definitive version is available at: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0088
Versión del editorhttp://dx.doi.org/10.1002/joc.4561
URI http://hdl.handle.net/10261/127105
DOI10.1002/joc.4561
ISSN0899-8418
E-ISSN1097-0088
Aparece en las colecciones: (IPE) Artículos
(EEAD) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
BegueriaS_JClimatolog_2016.pdf12,71 MBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo
 



NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.