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Climate Dynamics

, Volume 41, Issue 11–12, pp 2937–2955 | Cite as

Simulation of rainfall anomalies leading to the 2005 drought in Amazonia using the CLARIS LPB regional climate models

  • J. MarengoEmail author
  • S. Chou
  • C. Mourao
  • S. Solman
  • E. Sanchez
  • P. Samuelsson
  • R. P. da Rocha
  • L. Li
  • N. Pessacg
  • A. R. C. Remedio
  • A. F. Carril
  • I. F Cavalcanti
  • D. Jacob
Article

Abstract

The meteorological characteristics of the drought of 2005 in Amazonia, one of the most severe in the last 100 years were assessed using a suite of seven regional models obtained from the CLARIS LPB project. The models were forced with the ERA-Interim reanalyses as boundary conditions. We used a combination of rainfall and temperature observations and the low-level circulation and evaporation fields from the reanalyses to determine the climatic and meteorological characteristics of this particular drought. The models reproduce in some degree the observed annual cycle of precipitation and the geographical distribution of negative rainfall anomalies during the summer months of 2005. With respect to the evolution of rainfall during 2004–2006, some of the models were able to simulate the negative rainfall departures during early summer of 2005 (December 2004 to February 2005). The interannual variability of rainfall anomalies for both austral summer and fall over northern and southern Amazonia show a large spread among models, with some of them capable of reproducing the 2005 observed negative rainfall departures (four out of seven models in southern Amazonia during DJF). In comparison, all models simulated the observed southern Amazonia negative rainfall and positive air temperature anomalies during the El Nino-related drought in 1998. The spatial structure of the simulated rainfall and temperature anomalies in DJF and MAM 2005 shows biases that are different among models. While some models simulated the observed negative rainfall anomalies over parts of western and southern Amazonia during DJF, others simulated positive rainfall departures over central Amazonia. The simulated circulation patterns indicate a weaker northeasterly flow from the tropical North Atlantic into Amazonia, and reduced flows from southern Amazonia into the La Plata basin in DJF, which is consistent with observations. In general, we can say that in some degree the regional models are able to capture the response to the forcing from the tropical Atlantic during the drought of 2005 in Amazonia. Moreover, extreme climatic conditions in response to anomalous low-level circulation features are also well captured, since the boundary conditions come from reanalysis and the models are largely constrained by the information provided at the boundaries. The analysis of the 2005 drought suggests that when the forcing leading to extreme anomalous conditions is associated with both local and non-local mechanisms (soil moisture feedbacks and remote SST anomalies, respectively) the models are not fully capable of representing these feedbacks and hence, the associated anomalies. The reason may be a deficient reproduction of the land–atmosphere interactions.

Keywords

Amazonia Drought Downscaling Regional models 

Notes

Acknowledgments

The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 212492: CLARIS LPB, Europe-South America Network for Climate Change Assessment and Impact Studies in La Plata Basin. Additional funding was provided by RedeCLIMA, the National Institute of Science and Technology (INCT) for Climate Change funded by CNPq Grant Number 573797/2008-0 and FAPESP Grant Number 57719-9, the FAPESPAssessment of Impacts and Vulnerability to Climate Change in Brazil and strategies for Adaptation options project (Ref. 2008/581611). This work has been partially supported by UBACyT Grant X160, UBACyT Grant Y028 and Conicet Grant PIP 112-200801-00195.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • J. Marengo
    • 1
    Email author
  • S. Chou
    • 2
  • C. Mourao
    • 1
  • S. Solman
    • 3
    • 10
    • 11
  • E. Sanchez
    • 4
  • P. Samuelsson
    • 5
  • R. P. da Rocha
    • 6
  • L. Li
    • 7
  • N. Pessacg
    • 8
  • A. R. C. Remedio
    • 9
  • A. F. Carril
    • 3
    • 10
    • 11
  • I. F Cavalcanti
    • 2
  • D. Jacob
    • 9
    • 12
  1. 1.Centro de Ciência do Sistema Terrestre, Instituto Nacional de Pesquisas Espaciais (CCST INPE)Cachoeira PaulistaBrazil
  2. 2.Centro de Previsao de Tempo e Estudos Climaticos, Instituto Nacional de Pesquisas Espaciais (CPTEC INPE)Cachoeira PaulistaBrazil
  3. 3.Centro de Investigaciones del Mar y la Atmósfera (CIMA)CONICET-UBABuenos AiresArgentina
  4. 4.Facultad Ciencias Ambientales y BioquimicaUniversidad de Castilla-La ManchaToledoSpain
  5. 5.Rossby CentreSMHINorrköpingSweden
  6. 6.Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências AtmosféricasUniversidade de São PauloSão PauloBrazil
  7. 7.Laboratoire de Météorologie Dynamique, IPSLCNRS/UPMCParisFrance
  8. 8.Centro Nacional Patagónico (CENPAT/CONICET)Puerto MadrynArgentina
  9. 9.Max Planck Institute for MeteorologyHamburgGermany
  10. 10.Departamento de Ciencias de la Atmósfera y los Océanos (DCAO), FCENUniversidad de Buenos AiresBuenos AiresArgentina
  11. 11.UMI IFAECI/CNRSBuenos AiresArgentina
  12. 12.Climate Services Center (CSC)HamburgGermany

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