Construction of a daily precipitation grid for southeastern South America for the period 1961-2000
- Autores
- Jones, P.D.; Lister, D.H.; Harpham, C.; Rusticucci, M.; Penalba, O.
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Daily station precipitation totals are used to develop a gridded dataset for the region (14°-40°S, 45°-70°W) on a 0.5° × 0.5° latitude/longitude grid, primarily for comparison with regional climate model (RCM) simulations. The gridded dataset covers the period 1961-2000. Much of the paper discusses the quality control of the basic station precipitation series. Although the primary aim of the development has been RCM validation, we have assessed trends in seasonal precipitation totals as well as trends in two measures of precipitation extremes (R95p, the daily precipitation amount exceeded only 5% of the time and Rx5day, the maximum 5-d precipitation total during each season). Relatively few regions across the large domain have statistically significant trends, but those that do tend to be located in the eastern two thirds of the grid, particularly over southeastern Brazil and Uruguay. Significant trends are also more evident in the DJF and MAM seasons. There is good spatial agreement between the trends in seasonal totals and trends in the extreme indices. © 2012 Royal Meteorological Society.
Fil:Rusticucci, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Penalba, O. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. - Fuente
- Int. J. Climatol. 2013;33(11):2508-2519
- Materia
-
Gridding
Precipitation
South America
Daily precipitations
Gridding
Precipitation extremes
Regional climate modeling (RCM)
Seasonal precipitations
South America
Southeastern Brazil
Southeastern South America
Climatology
Precipitation (chemical)
Earth atmosphere
climate modeling
computer simulation
data set
extreme event
historical perspective
model validation
precipitation (climatology)
regional climate
seasonal variation
trend analysis
Brazil
Uruguay - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/2.5/ar
- Repositorio
- Institución
- Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
- OAI Identificador
- paperaa:paper_08998418_v33_n11_p2508_Jones
Ver los metadatos del registro completo
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spelling |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000Jones, P.D.Lister, D.H.Harpham, C.Rusticucci, M.Penalba, O.GriddingPrecipitationSouth AmericaDaily precipitationsGriddingPrecipitation extremesRegional climate modeling (RCM)Seasonal precipitationsSouth AmericaSoutheastern BrazilSoutheastern South AmericaClimatologyPrecipitation (chemical)Earth atmosphereclimate modelingcomputer simulationdata setextreme eventhistorical perspectivemodel validationprecipitation (climatology)regional climateseasonal variationtrend analysisBrazilUruguayDaily station precipitation totals are used to develop a gridded dataset for the region (14°-40°S, 45°-70°W) on a 0.5° × 0.5° latitude/longitude grid, primarily for comparison with regional climate model (RCM) simulations. The gridded dataset covers the period 1961-2000. Much of the paper discusses the quality control of the basic station precipitation series. Although the primary aim of the development has been RCM validation, we have assessed trends in seasonal precipitation totals as well as trends in two measures of precipitation extremes (R95p, the daily precipitation amount exceeded only 5% of the time and Rx5day, the maximum 5-d precipitation total during each season). Relatively few regions across the large domain have statistically significant trends, but those that do tend to be located in the eastern two thirds of the grid, particularly over southeastern Brazil and Uruguay. Significant trends are also more evident in the DJF and MAM seasons. There is good spatial agreement between the trends in seasonal totals and trends in the extreme indices. © 2012 Royal Meteorological Society.Fil:Rusticucci, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Penalba, O. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12110/paper_08998418_v33_n11_p2508_JonesInt. J. Climatol. 2013;33(11):2508-2519reponame:Biblioteca Digital (UBA-FCEN)instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesinstacron:UBA-FCENenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/2.5/ar2025-09-04T09:48:20Zpaperaa:paper_08998418_v33_n11_p2508_JonesInstitucionalhttps://digital.bl.fcen.uba.ar/Universidad públicaNo correspondehttps://digital.bl.fcen.uba.ar/cgi-bin/oaiserver.cgiana@bl.fcen.uba.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:18962025-09-04 09:48:22.377Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesfalse |
dc.title.none.fl_str_mv |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 |
title |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 |
spellingShingle |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 Jones, P.D. Gridding Precipitation South America Daily precipitations Gridding Precipitation extremes Regional climate modeling (RCM) Seasonal precipitations South America Southeastern Brazil Southeastern South America Climatology Precipitation (chemical) Earth atmosphere climate modeling computer simulation data set extreme event historical perspective model validation precipitation (climatology) regional climate seasonal variation trend analysis Brazil Uruguay |
title_short |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 |
title_full |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 |
title_fullStr |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 |
title_full_unstemmed |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 |
title_sort |
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000 |
dc.creator.none.fl_str_mv |
Jones, P.D. Lister, D.H. Harpham, C. Rusticucci, M. Penalba, O. |
author |
Jones, P.D. |
author_facet |
Jones, P.D. Lister, D.H. Harpham, C. Rusticucci, M. Penalba, O. |
author_role |
author |
author2 |
Lister, D.H. Harpham, C. Rusticucci, M. Penalba, O. |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Gridding Precipitation South America Daily precipitations Gridding Precipitation extremes Regional climate modeling (RCM) Seasonal precipitations South America Southeastern Brazil Southeastern South America Climatology Precipitation (chemical) Earth atmosphere climate modeling computer simulation data set extreme event historical perspective model validation precipitation (climatology) regional climate seasonal variation trend analysis Brazil Uruguay |
topic |
Gridding Precipitation South America Daily precipitations Gridding Precipitation extremes Regional climate modeling (RCM) Seasonal precipitations South America Southeastern Brazil Southeastern South America Climatology Precipitation (chemical) Earth atmosphere climate modeling computer simulation data set extreme event historical perspective model validation precipitation (climatology) regional climate seasonal variation trend analysis Brazil Uruguay |
dc.description.none.fl_txt_mv |
Daily station precipitation totals are used to develop a gridded dataset for the region (14°-40°S, 45°-70°W) on a 0.5° × 0.5° latitude/longitude grid, primarily for comparison with regional climate model (RCM) simulations. The gridded dataset covers the period 1961-2000. Much of the paper discusses the quality control of the basic station precipitation series. Although the primary aim of the development has been RCM validation, we have assessed trends in seasonal precipitation totals as well as trends in two measures of precipitation extremes (R95p, the daily precipitation amount exceeded only 5% of the time and Rx5day, the maximum 5-d precipitation total during each season). Relatively few regions across the large domain have statistically significant trends, but those that do tend to be located in the eastern two thirds of the grid, particularly over southeastern Brazil and Uruguay. Significant trends are also more evident in the DJF and MAM seasons. There is good spatial agreement between the trends in seasonal totals and trends in the extreme indices. © 2012 Royal Meteorological Society. Fil:Rusticucci, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Penalba, O. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. |
description |
Daily station precipitation totals are used to develop a gridded dataset for the region (14°-40°S, 45°-70°W) on a 0.5° × 0.5° latitude/longitude grid, primarily for comparison with regional climate model (RCM) simulations. The gridded dataset covers the period 1961-2000. Much of the paper discusses the quality control of the basic station precipitation series. Although the primary aim of the development has been RCM validation, we have assessed trends in seasonal precipitation totals as well as trends in two measures of precipitation extremes (R95p, the daily precipitation amount exceeded only 5% of the time and Rx5day, the maximum 5-d precipitation total during each season). Relatively few regions across the large domain have statistically significant trends, but those that do tend to be located in the eastern two thirds of the grid, particularly over southeastern Brazil and Uruguay. Significant trends are also more evident in the DJF and MAM seasons. There is good spatial agreement between the trends in seasonal totals and trends in the extreme indices. © 2012 Royal Meteorological Society. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/20.500.12110/paper_08998418_v33_n11_p2508_Jones |
url |
http://hdl.handle.net/20.500.12110/paper_08998418_v33_n11_p2508_Jones |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/2.5/ar |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
Int. J. Climatol. 2013;33(11):2508-2519 reponame:Biblioteca Digital (UBA-FCEN) instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales instacron:UBA-FCEN |
reponame_str |
Biblioteca Digital (UBA-FCEN) |
collection |
Biblioteca Digital (UBA-FCEN) |
instname_str |
Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales |
instacron_str |
UBA-FCEN |
institution |
UBA-FCEN |
repository.name.fl_str_mv |
Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales |
repository.mail.fl_str_mv |
ana@bl.fcen.uba.ar |
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