Climate Dynamics

, Volume 26, Issue 4, pp 367–385 | Cite as

On the tropical origin of uncertainties in the global land precipitation response to global warming

Article

Abstract

Understanding the response of the global hydrological cycle to recent and future anthropogenic emissions of greenhouse gases and aerosols is a major challenge for the climate modelling community. Recent climate scenarios produced for the fourth assessment report of the Intergovernmental Panel on Climate Change are analysed here to explore the geographical origin of, and the possible reasons for, uncertainties in the hydrological model response to global warming. Using the twentieth century simulations and the SRES-A2 scenarios from eight different coupled ocean–atmosphere models, it is shown that the main uncertainties originate from the tropics, where even the sign of the zonal mean precipitation change remains uncertain over land. Given the large interannual fluctuations of tropical precipitation, it is then suggested that the El Niño Southern Ocillation (ENSO) variability can be used as a surrogate of climate change to better constrain the model reponse. While the simulated sensitivity of global land precipitation to global mean surface temperature indeed shows a remarkable similarity between the interannual and climate change timescales respectively, the model ability to capture the ENSO-precipitation relationship is not a major constraint on the global hydrological projections. Only the model that exhibits the highest precipitation sensitivity clearly appears as an outlier. Besides deficiencies in the simulation of the ENSO-tropical rainfall teleconnections, the study indicates that uncertainties in the twenty-first century evolution of these teleconnections represent an important contribution to the model spread, thus emphasizing the need for improving the simulation of the tropical Pacific variability to provide more reliable scenarios of the global hydrological cycle. It also suggests that validating the mean present-day climate is not sufficient to assess the reliability of climate projections, and that interannual variability is another suitable and possibly more useful candidate for constraining the model response. Finally, it is shown that uncertainties in precipitation change are, like precipitation itself, very unevenly distributed over the globe, the most vulnerable countries sometimes being those where the anticipated precipitation changes are the most uncertain.

Notes

Acknowledgements

The authors are very grateful to all IPCC4 participants and to the PCMDI for the build up of the IPCC4 data base. Thanks are also due to the anonymous reviewers, as well as to Dr. A. Gershunov, Dr. J-F. Royer and Dr. S. Conil for their helpful comments. This work has been supported by the European Commission Sixth Framework Program (ENSEMBLES contract GOCE-CT-2003-505539).

References

  1. Adler et al (2003) The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-present). J Hydrometeor 4:1147–1167CrossRefGoogle Scholar
  2. Allen MR, Ingram WJ (2002) Constraints on future changes in climate and the hydrological cycle. Nature 419:224–232CrossRefPubMedGoogle Scholar
  3. Ashrit RG, Douville H, Rupa Kumar K (2003) Response of the Indian monsoon and ENSO-monsoon teleconnection to enhanced greenhouse effect in the CNRM coupled model. J Meteor Soc Jpn 81:779–803CrossRefGoogle Scholar
  4. Bosilovich MG, Schubert SD, Walker GK (2005) Global changes of the water cycle intensity. J Clim 18:1591–1608CrossRefGoogle Scholar
  5. Brooks N (2004) Drought in the African Sahel: long term perspectives and future prospects. Tyndall Centre working paper no 61: 31ppGoogle Scholar
  6. Camberlin P, Zhao Y, Chauvin F, Douville H (2004) Simulated ENSO-tropical rainfall teleconnections as from the ARPEGE-OPA coupled ocean-atmosphere model. Climate Dyn 23:641–657CrossRefGoogle Scholar
  7. Diaz HF, Hoerling MP, Eischeid JK (2001) ENSO variability, teleconnections and climate change. Int J Climatol 21:1845–1862CrossRefGoogle Scholar
  8. Douville H, Royer J-F, Polcher J, Cox P, Gedney N, Stephenson DB, Valdes PJ (2000) Impact of CO2 doubling on the Asian summer monsoon: robust versus model dependent responses. J Meteorol Soc Jpn 78:1–19Google Scholar
  9. Douville H, Chauvin F, Planton S, Royer J-F, Salas Mélia D, Tyteca S (2002) Sensitivity of the hydrological cycle to increasing amounts of greenhouse gases and aerosols. Climate Dyn 20:45–68CrossRefGoogle Scholar
  10. Douville H (2005) Impact of regional SST anomalies on the Indian monsoon response to global warming in the CNRM climate model. J Climate (revised)Google Scholar
  11. Gershunov A, Barnett T (1998) Inter-decadal modulation of ENSO teleconnections. BAMS 79:2715–2725CrossRefGoogle Scholar
  12. Gershunov A, Schneider N, Barnett T (2001) Low-frequency modulation of the ENSO-Indian monsoon rainfall relationship: signal or noise? J Clim 14:2486–2492CrossRefGoogle Scholar
  13. Hulme M, Osborn TJ, Johns TC (1998) Precipitation sensitivity to global warming: comparison of observations with HadCM2 simulations. Geophys Res Lett 25:3379–3382CrossRefGoogle Scholar
  14. IPCC (2001) Climate change 2001: the scientific basis. In: Houghton JT et al (eds) Cambridge University Press, CambridgeGoogle Scholar
  15. Jancovici J-M (2004) Energy and climate change: discussing two opposite evolutions. J de Phys (Proce) 121:171–184Google Scholar
  16. Kumar A, Yang F, Goddard L, Schubert S (2004) Differing trends in the tropical surface temperatures and precipitation over land and oceans. J Clim 17:653–664CrossRefGoogle Scholar
  17. Lau KM, Ho CH, Chou MD (1996) Water vapor and cloud feedback over the tropical oceans: Can we use ENSO as a surrogate for climate change? Geophys Res Lett 23:2971–2974CrossRefGoogle Scholar
  18. Liepert BG, Feichter J, Lohmann U, Roeckner E (2004) Can aerosols spin down the water cycle in a warmer and moister world? Geophys Res Lett 31: doi:10.1029/2003GL019060Google Scholar
  19. Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 430:768–772CrossRefPubMedGoogle Scholar
  20. Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice and night maritime air temperature since the late nineteenth century. J Geophys Res 108: doi:10.1029/2002JD002670Google Scholar
  21. Soden BJ (2000) The sensitivity of the tropical hydrological cycle to ENSO. J Clim 13:538–549CrossRefGoogle Scholar
  22. Timmerman A, Oberhuber J, Bacher A, Esch M, Latif M, Roeckner E (1999) Increased El Niño frequency in a climate model forced by future greenhouse warming. Nature 398:694–697CrossRefGoogle Scholar
  23. Yang F, Kumar A, Schlesinger ME, Wang W (2003) Intensity of hydrological cycles in warmer climates. J Clim 16:2419–2423CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Météo-France/CNRMToulouse Cedex 01France

Personalised recommendations