Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 1: Temperature mean state and seasonal cycle in South America
Projections for South America of future climate change conditions in mean state and seasonal cycle for temperature during the twenty-first century are discussed. Our analysis includes one simulation of seven Atmospheric-Ocean Global Circulation Models, which participated in the Intergovernmental Pan...
Guardado en:
| Autores principales: | Martínez, Fernando Luis, Segura, Enrique Carlos |
|---|---|
| Publicado: |
2006
|
| Materias: | |
| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_09307575_v27_n2-3_p233_Boulanger http://hdl.handle.net/20.500.12110/paper_09307575_v27_n2-3_p233_Boulanger |
| Aporte de: |
Ejemplares similares
-
Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 1: Temperature mean state and seasonal cycle in South America
por: Boulanger, J.-P., et al. -
Seasonal-to-decadal predictability and prediction of South American climate
Publicado: (2006) -
Seasonal-to-decadal predictability and prediction of South American climate
por: Nobre, P., et al. -
Modeling the wind-driven variability of the South Indian Ocean
Publicado: (1999) -
Modeling the wind-driven variability of the South Indian Ocean
por: Matano, R.P., et al.