Seasonal-to-decadal predictability and prediction of South American climate

The dynamical basis for seasonal to decadal climate predictions and predictability over South America is reviewed. It is shown that, while global tropical SSTs affect both predictability and predictions over South America, the current lack of SST predictability over the tropical Atlantic represents...

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Autores principales: Nobre, P., Marengo, J.A., Cavalcanti, I.F.A., Obregon, G., Barros, V., Camilloni, I., Campos, N., Ferreira, A.G.
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_08948755_v19_n23_p5988_Nobre
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spelling todo:paper_08948755_v19_n23_p5988_Nobre2023-10-03T15:42:10Z Seasonal-to-decadal predictability and prediction of South American climate Nobre, P. Marengo, J.A. Cavalcanti, I.F.A. Obregon, G. Barros, V. Camilloni, I. Campos, N. Ferreira, A.G. Atmospheric temperature Climate change Weather forecasting Climate predictions Climate variations Decadal climate Seasonal climate Climatology atmosphere-ocean coupling climate change climate modeling climate prediction decadal variation global change sea surface temperature seasonal variation Atlantic Ocean Atlantic Ocean (South) Brazil South America The dynamical basis for seasonal to decadal climate predictions and predictability over South America is reviewed. It is shown that, while global tropical SSTs affect both predictability and predictions over South America, the current lack of SST predictability over the tropical Atlantic represents a limiting factor to seasonal climate predictions over some parts of the continent. The model's skill varies with the continental region: the highest skill is found in the "Nordeste" region and the lowest skill over southeastern Brazil. It is also suggested that current two-tier approaches to predict seasonal climate variations might represent a major limitation to forecast coupled ocean-atmosphere phenomena like the South Atlantic convergence zone. Also discussed are the possible effects of global climate change on regional predictability of seasonal climate. © 2006 American Meteorological Society. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_08948755_v19_n23_p5988_Nobre
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Atmospheric temperature
Climate change
Weather forecasting
Climate predictions
Climate variations
Decadal climate
Seasonal climate
Climatology
atmosphere-ocean coupling
climate change
climate modeling
climate prediction
decadal variation
global change
sea surface temperature
seasonal variation
Atlantic Ocean
Atlantic Ocean (South)
Brazil
South America
spellingShingle Atmospheric temperature
Climate change
Weather forecasting
Climate predictions
Climate variations
Decadal climate
Seasonal climate
Climatology
atmosphere-ocean coupling
climate change
climate modeling
climate prediction
decadal variation
global change
sea surface temperature
seasonal variation
Atlantic Ocean
Atlantic Ocean (South)
Brazil
South America
Nobre, P.
Marengo, J.A.
Cavalcanti, I.F.A.
Obregon, G.
Barros, V.
Camilloni, I.
Campos, N.
Ferreira, A.G.
Seasonal-to-decadal predictability and prediction of South American climate
topic_facet Atmospheric temperature
Climate change
Weather forecasting
Climate predictions
Climate variations
Decadal climate
Seasonal climate
Climatology
atmosphere-ocean coupling
climate change
climate modeling
climate prediction
decadal variation
global change
sea surface temperature
seasonal variation
Atlantic Ocean
Atlantic Ocean (South)
Brazil
South America
description The dynamical basis for seasonal to decadal climate predictions and predictability over South America is reviewed. It is shown that, while global tropical SSTs affect both predictability and predictions over South America, the current lack of SST predictability over the tropical Atlantic represents a limiting factor to seasonal climate predictions over some parts of the continent. The model's skill varies with the continental region: the highest skill is found in the "Nordeste" region and the lowest skill over southeastern Brazil. It is also suggested that current two-tier approaches to predict seasonal climate variations might represent a major limitation to forecast coupled ocean-atmosphere phenomena like the South Atlantic convergence zone. Also discussed are the possible effects of global climate change on regional predictability of seasonal climate. © 2006 American Meteorological Society.
format JOUR
author Nobre, P.
Marengo, J.A.
Cavalcanti, I.F.A.
Obregon, G.
Barros, V.
Camilloni, I.
Campos, N.
Ferreira, A.G.
author_facet Nobre, P.
Marengo, J.A.
Cavalcanti, I.F.A.
Obregon, G.
Barros, V.
Camilloni, I.
Campos, N.
Ferreira, A.G.
author_sort Nobre, P.
title Seasonal-to-decadal predictability and prediction of South American climate
title_short Seasonal-to-decadal predictability and prediction of South American climate
title_full Seasonal-to-decadal predictability and prediction of South American climate
title_fullStr Seasonal-to-decadal predictability and prediction of South American climate
title_full_unstemmed Seasonal-to-decadal predictability and prediction of South American climate
title_sort seasonal-to-decadal predictability and prediction of south american climate
url http://hdl.handle.net/20.500.12110/paper_08948755_v19_n23_p5988_Nobre
work_keys_str_mv AT nobrep seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
AT marengoja seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
AT cavalcantiifa seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
AT obregong seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
AT barrosv seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
AT camillonii seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
AT camposn seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
AT ferreiraag seasonaltodecadalpredictabilityandpredictionofsouthamericanclimate
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