• Adler, R. F., and Coauthors, 2003: The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–present). J. Hydrometeor., 4, 11471167.

    • Search Google Scholar
    • Export Citation
  • Barreiro, M., , P. Chang, , and R. Saravanan, 2002: Variability of the South Atlantic convergence zone simulated by an atmospheric general circulation model. J. Climate, 15, 745763.

    • Search Google Scholar
    • Export Citation
  • Barreiro, M., , P. Chang, , and R. Saravanan, 2005: Simulated precipitation response to SST forcing and potential predictability in the region of the South Atlantic convergence zone. Climate Dyn., 24, 105114.

    • Search Google Scholar
    • Export Citation
  • Barsugli, J. J., , and D. S. Battisti, 1998: The basic effects of atmosphere–ocean thermal coupling on midlatitude variability. J. Atmos. Sci., 55, 477493.

    • Search Google Scholar
    • Export Citation
  • Bourlès, B., and Coauthors, 2008: The PIRATA Program: History, accomplishments, and future directions. Bull. Amer. Meteor. Soc., 89, 11111125.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., , and D. S. Battisti, 2000: An interpretation of the results from atmospheric general circulation models forced by the time history of the observed sea surface temperature distribution. Geophys. Res. Lett., 27, 767770.

    • Search Google Scholar
    • Export Citation
  • Carvalho, L. M. V., , C. Jones, , and B. Liebmann, 2004: The South Atlantic convergence zone: Intensity, form, persistence and relationships with intraseasonal to interannual activity and extreme rainfall. J. Climate, 17, 88118.

    • Search Google Scholar
    • Export Citation
  • Chang, P., , C. Penland, , L. Ji, , L. Matrosova, , and H. Li, 1998: Prediction of tropical Atlantic sea surface temperature. Geophys. Res. Lett., 25, 11931196.

    • Search Google Scholar
    • Export Citation
  • Chang, P., , R. Saravanan, , L. Ji, , and G. C. Hegerl, 2000: The effect of local sea surface temperatures on atmospheric circulation over the tropical Atlantic sector. J. Climate, 13, 21952216.

    • Search Google Scholar
    • Export Citation
  • Chang, P., , L. Ji, , and R. Saravanan, 2001: A hybrid coupled model study of tropical Atlantic variability. J. Climate, 14, 361390.

  • Chaves, R. R., , and P. Nobre, 2004: Interactions between sea surface temperature over the South Atlantic Ocean and the South Atlantic Convergence Zone. Geophys. Res. Lett., 31, L03204, doi:10.1029/2003GL018647.

    • Search Google Scholar
    • Export Citation
  • Chiang, J. C. H., , Y. Kushnir, , and A. Giannini, 2002: Deconstructing Atlantic Intertropical Convergence Zone variability: Influence of the local cross-equatorial sea surface temperature gradient and remote forcing from the eastern equatorial Pacific. J. Geophys. Res., 107, 4004, doi:10.1029/2000JD000307.

    • Search Google Scholar
    • Export Citation
  • Davies, R., 1982: Documentation of the solar radiation parameterization in the GLAS climate models. NASA Tech. Memo. 83961, 57 pp.

  • De Almeida, R. A. F., , P. Nobre, , R. J. Haarsma, , and E. J. D. Campos, 2007: Negative ocean-atmosphere feedback in the South Atlantic Convergence Zone. Geophys. Res. Lett., 34, L18809, doi:10.1029/2007GL030401.

    • Search Google Scholar
    • Export Citation
  • Grell, G. A., 1993: Prognostic evaluation of assumptions used by cumulus parameterizations. Mon. Wea. Rev., 121, 764787.

  • Griffies, S. M., 2010: Elements of MOM4p1. GFDL Ocean Group Tech. Rep. 6, NOAA/Geophysical Fluid Dynamics Laboratory, 444 pp.

  • Grimm, A. M., 2003: The El Niño impact on the summer monsoon in Brazil: Regional processes versus remote influences. J. Climate, 16, 263280.

    • Search Google Scholar
    • Export Citation
  • Grimm, A. M., , J. S. Pal, , and F. Giorgi, 2007: Connection between spring conditions and peak summer monsoon rainfall in South America: Role of soil moisture, surface temperature, and topography in eastern Brazil. J. Climate, 20, 59295945.

    • Search Google Scholar
    • Export Citation
  • Harshvardhan, , R. Davies, , D. A. Randall, , and T. G. Corsetti, 1987: A fast radiation parameterization for atmospheric circulation models. J. Geophys. Res., 92 (D1), 10091016.

    • Search Google Scholar
    • Export Citation
  • Hastenrath, S., , and P. J. Lamb, 1977: Climatic Atlas of the Tropical Atlantic and Eastern Pacific Oceans. University of Wisconsin Press, 113 pp.

  • Huang, B., , P. S. Schopf, , and Z. Pan, 2002: The ENSO effect on the tropical Atlantic variability: A regionally coupled model study. Geophys. Res. Lett., 29, 2039, doi:10.1029/2002GL014872.

    • Search Google Scholar
    • Export Citation
  • Huang, B., , P. S. Schopf, , and J. Shukla, 2004: Intrinsic ocean–atmosphere variability of the tropical Atlantic Ocean. J. Climate, 17, 20582077.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., , R. F. Adler, , D. T. Bolvin, , and G. Gu, 2009: Improving the global precipitation record: GPCP Version 2.1. Geophys. Res. Lett., 36, L17808, doi:10.1029/2009GL040000.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis project. Bull. Amer. Meteor. Soc., 77, 437471.

  • Kitoh, A., , T. Motoi, , and H. Koide, 1999: SST variability and its mechanism in a coupled atmosphere–mixed layer ocean model. J. Climate, 12, 12211239.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., , and M. P. Hoerling, 1998: Specification of regional sea surface temperatures in atmospheric general circulation model simulations. J. Geophys. Res., 103 (D8), 89018907.

    • Search Google Scholar
    • Export Citation
  • Kumar, K. K., , M. P. Hoerling, , and B. Rajagopalan, 2005: Advancing dynamical prediction of Indian monsoon rainfall. Geophys. Res. Lett., 32, L08704, doi:10.1029/2004GL021979.

    • Search Google Scholar
    • Export Citation
  • Lacis, A. A., , and J. Hansen, 1974: A parameterization for the absorption of solar radiation in the earth’s atmosphere. J. Atmos. Sci., 31, 118133.

    • Search Google Scholar
    • Export Citation
  • Large, W., , and S. Yeager, 2009: The global climatology of an interannually varying air–sea flux data set. Climate Dyn., 33, 341364.

    • Search Google Scholar
    • Export Citation
  • Lenters, J. D., , and K. H. Cook, 1999: Summertime precipitation variability over South America: Role of the large-scale circulation. Mon. Wea. Rev., 127, 409431.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., , G. N. Kiladis, , J. A. Marengo, , T. Ambrizzi, , and J. D. Glick, 1999: Submonthly convective variability over South America and the South Atlantic convergence zone. J. Climate, 12, 18771891.

    • Search Google Scholar
    • Export Citation
  • Lin, J.-L., , T. Shinoda, , B. Liebmann, , T. Qian, , W. Han, , P. Roundy, , J. Zhou, , and Y. Zheng, 2009: Intraseasonal variability associated with summer precipitation over South America simulated by 14 IPCC AR4 coupled GCMs. Mon. Wea. Rev., 137, 29312954.

    • Search Google Scholar
    • Export Citation
  • Marengo, J. A., and Coauthors, 2003: Ensemble simulation of regional rainfall features in the CPTEC/COLA atmospheric GCM. Skill and predictability assessment and applications to climate predictions. Climate Dyn., 21, 459475.

    • Search Google Scholar
    • Export Citation
  • Mellor, G. L., , and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Phys., 20, 851875.

    • Search Google Scholar
    • Export Citation
  • Nobre, P., , S. E. Zebiak, , and B. P. Kirtman, 2003: Local and remote sources of tropical Atlantic variability as inferred from the results of a hybrid ocean-atmosphere coupled model. Geophys. Res. Lett., 30, 8008, doi:10.1029/2002GL015785.

    • Search Google Scholar
    • Export Citation
  • Nobre, P., , J. A. Marengo, , I. F. A. Cavalcanti, , G. Obregon, , V. Barros, , I. Camilloni, , N. Campos, , and A. G. Ferreira, 2006: Seasonal-to-decadal predictability and prediction of South American climate. J. Climate, 19, 59886004.

    • Search Google Scholar
    • Export Citation
  • Nogués-Paegle, J., , and K. C. Mo, 1997: Alternating wet and dry conditions over South America during summer. Mon. Wea. Rev., 125, 279291.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., , N. A. Rayner, , T. M. Smith, , D. C. Stokes, , and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625.

    • Search Google Scholar
    • Export Citation
  • Richter, I., , and S.-P. Xie, 2008: On the origin of equatorial Atlantic biases in coupled general circulation models. Climate Dyn., 31, 587598.

    • Search Google Scholar
    • Export Citation
  • Robertson, A. W., , and C. R. Mechoso, 2000: Interannual and interdecadal variability of the South Atlantic convergence zone. Mon. Wea. Rev., 128, 29472957.

    • Search Google Scholar
    • Export Citation
  • Robertson, A. W., , J. D. Ferrara, , and C. R. Mechoso, 2003: Simulations of the atmospheric response to South Atlantic sea surface temperature anomalies. J. Climate, 16, 25402551.

    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1984: The sensitivity of the time mean large-scale flow to cumulus convection in the ECMWF model. Proc. Workshop on Convection in Large-Scale Numerical Models, Reading, United Kingdom, ECMWF, 297–316.

  • Van der Linden, P., , and J. F. B. Mitchell, 2009: ENSEMBLES: Climate change and its impacts: Summary of research and results from the ENSEMBLES project. Met Office Hadley Centre Rep., 160 pp. [Available online at http://ensembles-eu.metoffice.com/docs/Ensembles_final_report_Nov09.pdf.]

  • Wang, B., , Q. Ding, , X. Fu, , I.-S. Kang, , K. Jin, , J. Shukla, , and F. Doblas-Reyes, 2005: Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys. Res. Lett., 32, L15711, doi:10.1029/2005GL022734.

    • Search Google Scholar
    • Export Citation
  • Wu, L., , F. He, , Z. Liu, , and C. Li, 2007: Atmospheric teleconnections of tropical Atlantic variability: Interhemispheric, tropical–extratropical, and cross-basin interactions. J. Climate, 20, 856870.

    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., , Y. Tanimoto, , H. Noguchi, , and T. Matsuno, 1999: How and why climate variability differs between the tropical Atlantic and Pacific. Geophys. Res. Lett., 26, 16091612.

    • Search Google Scholar
    • Export Citation
  • Xue, Y., , P. J. Sellers, , J. L. Kinter, , and J. Shukla, 1991: A simplified biosphere model for global climate studies. J. Climate, 4, 345364.

    • Search Google Scholar
    • Export Citation
  • Zebiak, S. E., 1993: Air-sea interaction in the equatorial Atlantic region. J. Climate, 6, 15671586.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 54 54 9
PDF Downloads 40 40 5

Coupled Ocean–Atmosphere Variations over the South Atlantic Ocean

View More View Less
  • 1 National Institute for Space Research (INPE), Cachoeira Paulista, Brazil
© Get Permissions
Restricted access

Abstract

The impact of ocean–atmosphere interactions on summer rainfall over the South Atlantic Ocean is explored through the use of coupled ocean–atmosphere models. The Brazilian Center for Weather Forecast and Climate Studies (CPTEC) coupled ocean–atmosphere general circulation model (CGCM) and its atmospheric general circulation model (AGCM) are used to gauge the role of coupled modes of variability of the climate system over the South Atlantic at seasonal time scales. Twenty-six years of summer [December–February (DJF)] simulations were done with the CGCM in ensemble mode and the AGCM forced with both observed sea surface temperature (SST) and SST generated by the CGCM forecasts to investigate the dynamics/thermodynamics of the two major convergence zones in the tropical Atlantic: the intertropical convergence zone (ITCZ) and the South Atlantic convergence zone (SACZ). The results present both numerical model and observational evidence supporting the hypothesis that the ITCZ is a thermally direct, SST-driven atmospheric circulation, while the SACZ is a thermally indirect atmospheric circulation controlling SST variability underneath—a consequence of ocean–atmosphere interactions not captured by the atmospheric model forced by prescribed ocean temperatures. Six CGCM model results of the Ensemble-based Predictions of Climate Changes and their Impacts (ENSEMBLES) project, NCEP–NCAR reanalysis data, and oceanic and atmospheric data from buoys of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Project over the tropical Atlantic are used to validate CPTEC’s coupled and uncoupled model simulations.

Corresponding author address: Paulo Nobre, National Institute for Space Research (INPE), Cachoeira Paulista, SP, 12630-000, Brazil. E-mail: paulo.nobre@cptec.inpe.br

Abstract

The impact of ocean–atmosphere interactions on summer rainfall over the South Atlantic Ocean is explored through the use of coupled ocean–atmosphere models. The Brazilian Center for Weather Forecast and Climate Studies (CPTEC) coupled ocean–atmosphere general circulation model (CGCM) and its atmospheric general circulation model (AGCM) are used to gauge the role of coupled modes of variability of the climate system over the South Atlantic at seasonal time scales. Twenty-six years of summer [December–February (DJF)] simulations were done with the CGCM in ensemble mode and the AGCM forced with both observed sea surface temperature (SST) and SST generated by the CGCM forecasts to investigate the dynamics/thermodynamics of the two major convergence zones in the tropical Atlantic: the intertropical convergence zone (ITCZ) and the South Atlantic convergence zone (SACZ). The results present both numerical model and observational evidence supporting the hypothesis that the ITCZ is a thermally direct, SST-driven atmospheric circulation, while the SACZ is a thermally indirect atmospheric circulation controlling SST variability underneath—a consequence of ocean–atmosphere interactions not captured by the atmospheric model forced by prescribed ocean temperatures. Six CGCM model results of the Ensemble-based Predictions of Climate Changes and their Impacts (ENSEMBLES) project, NCEP–NCAR reanalysis data, and oceanic and atmospheric data from buoys of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Project over the tropical Atlantic are used to validate CPTEC’s coupled and uncoupled model simulations.

Corresponding author address: Paulo Nobre, National Institute for Space Research (INPE), Cachoeira Paulista, SP, 12630-000, Brazil. E-mail: paulo.nobre@cptec.inpe.br
Save