Climate Dynamics

, Volume 45, Issue 7–8, pp 2193–2212 | Cite as

Regional climate modelling in CLARIS-LPB: a concerted approach towards twentyfirst century projections of regional temperature and precipitation over South America

  • E. Sánchez
  • S. Solman
  • A. R. C. Remedio
  • H. Berbery
  • P. Samuelsson
  • R. P. Da Rocha
  • C. Mourão
  • L. Li
  • J. Marengo
  • M. de Castro
  • D. Jacob


The results of an ensemble of regional climate model (RCM) simulations over South America are presented. This is the first coordinated exercise of regional climate modelling studies over the continent, as part of the CLARIS-LPB EU FP7 project. The results of different future periods, with the main focus on (2071–2100) is shown, when forced by several global climate models, all using the A1B greenhouse gases emissions scenario. The analysis is focused on the mean climate conditions for both temperature and precipitation. The common climate change signals show an overall increase of temperature for all the seasons and regions, generally larger for the austral winter season. Future climate shows a precipitation decrease over the tropical region, and an increase over the subtropical areas. These climate change signals arise independently of the driving global model and the RCM. The internal variability of the driving global models introduces a very small level of uncertainty, compared with that due to the choice of the driving model and the RCM. Moreover, the level of uncertainty is larger for longer horizon projections for both temperature and precipitation. The uncertainty in the temperature changes is larger for the subtropical than for the tropical ones. The current analysis allows identification of the common climate change signals and their associated uncertainties for several subregions within the South American continent.


Regional climate modelling Climate change South America 



CLARIS LPB A Europe-South America Network for Climate Change Assessment and Impact Studies in La Plata Basin EU-FP7 project (proposal 212492). This work has also been supported by the following Grants: FONCyT—PICT-2012-1972, PIP-CONICET No. 112-201101-00189 and UBACYT2014 No. 20020130200233BA. We acknowledge the German Climate Computing Centre (DKRZ) computing facilities for our REMO simulations. The remarks and suggestions from the reviewers helped much to a more accurate and precise description of the results and uncertainties.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • E. Sánchez
    • 1
  • S. Solman
    • 2
  • A. R. C. Remedio
    • 3
  • H. Berbery
    • 4
  • P. Samuelsson
    • 5
  • R. P. Da Rocha
    • 6
  • C. Mourão
    • 7
  • L. Li
    • 8
  • J. Marengo
    • 7
  • M. de Castro
    • 1
  • D. Jacob
    • 3
  1. 1.Faculty of Environmental Sciences and BiochemistryUniversity of Castilla La ManchaToledoSpain
  2. 2.Centro de Investigaciones del Mar y la Atmósfera (CIMA/CONICET-UBA), DCAO/FCEN-UBA UMI IFAECI/CNRSCiudad Universitaria Pabellón II Piso 2Buenos AiresArgentina
  3. 3.Climate Service Center 2.0HamburgGermany
  4. 4.Earth System Science Interdisciplinary Center (ESSIC)University of MarylandCollege ParkUSA
  5. 5.Rossby CentreSMHINorrköpingSweden
  6. 6.Dept Ciencias Atmosféricas, Instituto de Astronomía, Geofísica e Ciencias AtmosféricasUniversidade de São PauloSão PauloBrazil
  7. 7.Centro Ciencia Sistema Terrestre-Instituto Nacional Pesquisas Espaciais (CCST INPE)Cachoeira PaulistaBrazil
  8. 8.Laboratoire de Météorologie DynamiqueIPSL, CNRS/UPMCParisFrance

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