Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 2: Precipitation mean state and seasonal cycle in South America-Reference-Cited by-同舟云学术

Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 2: Precipitation mean state and seasonal cycle in South America

Published:2006-08-30 Issue:2-3 Volume:28 Page:255-271
ISSN:0930-7575
Container-title:Climate Dynamics
language:en
Short-container-title:Clim Dyn

Author:

Boulanger Jean-Philippe,Martinez Fernando,Segura Enrique C.

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

http://link.springer.com/content/pdf/10.1007/s00382-006-0182-0.pdf

Reference20 articles.

1. Boulanger J-P, Leloup J, Penalba O, Rusticucci M, Lafon F, Vargas W (2005) Low-frequency modes of observed precipitation variability over the La Plata basin. Clim Dyn 24:393–413

2. Boulanger J-P, Martinez F, Segura EC (2006) 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. Clim Dyn 27:233–259

3. Collins WD, Bitz CM, Blackmon ML, Bonan GB, Bretherton CS, Carton JA, Chang P, Doney SC, Hack JJ, Henderson TB, Kiehl JT, Large WG, McKenna DS, Santer BD, Smith RD (2006) The Community Climate System Model: CCSM3. J Clim 19:2122–2143

4. Delworth TL et al (2006) GFDL’s CM2 global coupled climate models. Part 1: Formulation and simulation characteristics. J Clim 19(5):643–674

5. Gnanadesikan A et al (2006) GFDL’s CM2 global coupled climate models. Part 2: The baseline ocean simulation. J Clim 19(5):675–697

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