Oceanic Forcing of Sahel Rainfall on Interannual to Interdecadal Time Scales

Science

Volumn 302, Issue 5647, 2003, Pages 1027-1030

  Giannini, A ^a,c   Saravanan, R ^a   Chang, P ^b  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

^c Earth Institute   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATE CHANGE; DROUGHT; OCEANOGRAPHY;

OCEANIC FORCING;

RAIN;

RAIN;

ATMOSPHERE-BIOSPHERE INTERACTION; CLIMATE FORCING; CONVECTION; RAINFALL; SEA SURFACE TEMPERATURE; TIMESCALE;

AFRICA; ARTICLE; ATMOSPHERE; DROUGHT; ETHIOPIA; LAND BIOME; OCEAN ENVIRONMENT; POPULATION GROWTH; PRECIPITATION; PRIORITY JOURNAL; SEASONAL VARIATION; SENEGAL; SPACE FLIGHT; SUMMER;

AFRICA;

EID: 0242410711     PISSN: 00368075     EISSN: None     Source Type: Journal    
DOI: 10.1126/science.1089357     Document Type: Article

References (41)

1. S. E. Nicholson, Mon. Weather Rev. 108, 473 (1980).
2. M. H. Glantz, R. W. Katz, Ambio 14 (no. 6), 334 (1985).
3. J. G. Charney, Q. J. R. Meteorol. Soc. 101, 193 (1975).
4. The albedo-precipitation feedback popularized by Charney was first proposed by J. Otterman [Science 186, 531 (1974)].
5. Y. C. Sud, M. Fennessy, J. Clim. 2, 105 (1982).
6. Y. Xue, J. Shukla, J. Clim. 6, 2232 (1993).
7. C. M. Taylor, E. F. Lambin, N. Stephenne, R. J. Harding, R. L. H. Essery, J. Clim. 15, 3615 (2002).
8. J. Fairhead, M. Leach, Deforestation: Global analyses and local realities - studies in West Africa (Routledge, London, 1998).
9. E. F. Lambin et al., Global Environ. Change 11, 261 (2001).
10. K. Rasmussen et al., Global Environ. Change 11, 271 (2001).
11. C. J. Tucker, H. E. Dregne, W. W. Newcomb, Science 253, 299 (1991).
12. C. K. Folland, T. N. Palmer, D. E. Parker, Nature 320, 602 (1986).
13. T. N. Palmer, Nature 322, 251 (1986).
14. D. P. Rowell, C. K. Folland, K. Maskell, M. N. Ward, Q. J. R. Meteorol. Soc. 121, 669 (1995).
15. S. Hastenrath, P. J. Lamb, Mon. Weather Rev. 105, 1019 (1977).
16. P. J. Lamb, Mon. Weather Rev. 106, 482 (1978).
17. B. Fontaine, S. Janicot, J. Clim. 9, 2935 (1996).
18. NSIPP1, as described in abstract, J. T. Bacmeister, P. J. Pegion, S. D. Schubert, M. J. Suarez, NASA Technical Memo. 104606, vol. 17 (2000). Available at http:// nsipp.gsfc.nasa.gov.
19. SSTs from three different data sets were used to force the ensemble of atmospheric general circulation model (ACGM) integrations over the sub-periods 1930-48, 1949-81, and 1982-2000. The data sets are (i) the Hadley Centre product (31), (ii) the GISST product (32), and (iii) the "Reynolds" product (33). The temporal discontinuities in boundary conditions were found to be of no consequence to the analysis presented here: the regression pattern of Fig. 2F was recalculated using the Hadley Centre data set from 1930 to 1999 and found to be identical to the one presented here, calculated using the boundary condition data set. Also, projections of the same regression pattern onto the Hadley Centre product and onto the boundary condition data set were found to correlate at 0.97 when care was taken to exclude gridpoints south of 50°S.
20. R. S. Vose et al., The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea level pressure, and station pressure data. ORNL/CDIAC-53, NDP-041 (Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, TN, 1992).
21. PCA is a mathematical procedure routinely used in the geophysical sciences to extract the dominant patterns of variability. It identifies the spatial structures, or empirical orthogonal functions (EOFs), and related temporal structures, also known as PCs, that sequentially maximize the fraction of the total variability that they represent (34-36).
22. A. Giannini, R. Saravanan, P. Chang, data not shown.
23. The impact of tropical Atlantic SST anomalies on the West African monsoon has been the subject of observational studies dating back to the 1970s (15, 16), as well as of two recent modeling studies by Vizy and Cook (37, 38). In the presence of an equatorial Atlantic SST anomaly akin to the one associated with the model's Gulf of Guinea PC (Fig. 2C), a dipole in precipitation stands out in observations, with anomalies of opposite sign in the Sahel and along the Gulf of Guinea coast. This dipole is captured in our analysis of observed rainfall variability in the Sahel EOF (22); the regression of the observed Sahel PC onto SST (22) does bear the association out, with significant regression anomalies in the equatorial Atlantic, as well as in the rest of the tropical oceans. PCA of model output, in contrast, though separating rainfall variability in the Sahel from rainfall variability along the Gulf of Guinea coast (Fig. 2, A and D) in the two leading EOFs also decouples the association between eastern equatorial Atlantic SSTs and the rainfall dipole. AGCMs, thus far, have not been able to capture the dipole in precipitation, and the model analyzed here is no exception. Whether this model's failure to explicitly represent the dipole in precipitation is a dynamical limitation of the model, an artifact of PCA, or the expression of a substantial dynamical difference between Sahel and Gulf of Guinea precipitation, remains to be seen.
24. K. H. Cook, J. Clim. 7, 400 (1994).
25. Interannual SST variability is disabled in a 160-year long integration by substituting the observed record of SST with monthly climatology. Land-atmosphere interaction is disabled in a single integration forced with the observed record of SST over 1950-1999 by fixing evaporation efficiencies to monthly climatology, as computed from the ensemble of integrations. For details on the method, see (39, 40).
26. An interactive vegetation, in addition to the interactive land surface, could further amplify the ocean-forced signal, as in the intermediate complexity model of N. Zeng, J. D. Neelin, K.-M. Lau and C. J. Tucker [Science 286, 1537 (1999)]. Such an amplification could at least partially account for the difference in magnitude between observed and modeled rainfall variability (Fig. 1).
27. M. N. Ward, J. Clim. 11, 3167 (1998).
28. S. Janicot, A. Harzallah, B. Fontaine, V. Moron, J. Clim. 11, 1874 (1998).
29. J. C. H. Chiang, A. H. Sobel, J. Clim. 15, 2616 (2002).
30. C. Chou, J. D. Neelin, H. Su, Q. J. R. Meteorol. Soc. 127, 1869 (2001).
31. N. A. Rayner et al., in press.
32. N. A. Rayner, E. B. Horton, D. E. Parker, C. K. Folland, R. B. Hackett, Climate Research Technical Note 74 (1996). Available at: www.met-office.gov.uk/ research/hadleycentre/obsdata/GISST.html
33. W. R. Reynolds, T. M. Smith., J. Clim. 7, 929 (1994).
34. R. W. Preisendorfer, Principal Component Analysis in Meteorology and Oceanography, C. Mobley, Ed. (Elsevier, Amsterdam, 1988).
35. H. von Storch, F. W. Zwlers, Statistical Analysis in Climate Research (Cambridge Univ. Press, Cambridge, 1999).
36. J. P. Peixoto, A. H. Oort, Physics of Climate (American Institute of Physics, New York, 1992), appendix B.
37. E. K. Vizy, K. H. Cook, J. Clim. 14, 795 (2001).
38. E. K. Vizy, K. H. Cook, J. Geophys. Res. 107(D3), doi: 10.1029/2001JD000686 (2002).
39. R. D. Koster, M. J. Suarez, J. Geophys. Res. 100(D7), 13775 (1995).
40. R. D. Koster, M. J. Suarez, M. Heiser, J. Hydrometeorol. 1, 26 (2000).
41. We acknowledge the scientific advice and technical support provided by M. Suarez and the NSIPP Team at NASA/ GSFC (M. Rienecker, J. Bacmeister, H. Kistler, S. Schubert, P. Pegion, and N. Johnson). Supported in part by NASA InterAgency agreement W-19,750. The National Center for Atmospheric Research is operated by the University Corporation for Atmospheric Research under sponsorship of NSF.