1 / 22

Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales

IRI for climate prediction. Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales. A. Giannini (IRI) R. Saravanan (NCAR) and P. Chang (Texas A&M). Reflections on : Seasonal climate prediction - sensitivity of climate to boundary conditions Recent trends in climate

shakti
Download Presentation

Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. IRI for climate prediction Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales A. Giannini (IRI) R. Saravanan (NCAR) and P. Chang (Texas A&M)

  2. Reflections on: Seasonal climate prediction - sensitivity of climate to boundary conditions Recent trends in climate - are they related to global warming?

  3. r = 0.60

  4. The model used is NSIPP1 (version 1, NASA Seasonal to Interannual Prediction Project) Bacmeister et al 2000; Moorthi and Suarez 1992; Koster and Suarez 1992; Takacs and Suarez 1996 nsipp.gsfc.nasa.gov Results shown here are from the ensemble-mean of a 9-member ensemble of integrations forced over 1930-2000 with: 1) observed, interannually-varying sea surface temperature (SST); 2) constant atmospheric CO2 (350ppm); and 3) vegetation cover prescribed to vary seasonally, but not interannually

  5. Outline -statistical analysis -local land-atmosphere dynamics -tropical ocean teleconnections

  6. Statistical analysis Principal Component Analysis of July-September precipitation over tropical Africa (1930-2000)

  7. spatial signature of JAS African rainfall variability Gulf of Guinea pattern Sahel pattern

  8. temporal signature and relation to surface temperature

  9. land-atmosphere interaction

  10. precipitation surface temperature vertically-integrated moisture convergence evaporation

  11. surface temperature variability (1930-2000)

  12. Land surface-atmosphere interaction acts to amplify remotely-forced precipitation anomalies: -through local recycling of moisture, and -by modifying moisture convergence patterns A negative trend in precipitation is consistent with a positive trend in land surface temperature

  13. forcing from the global oceans

  14. (Sahel rainfall is sensitive to global, tropical SSTs)

  15. long-term v. interannual variability

  16. ENSO's impact on Northern Hemisphere summer climate Ropelewski and Halpert 1987 Yulaeva and Wallace 1994 Chiang and Sobel 2002 Neelin et al 2003

  17. Long-term trends and African climate variability Webster 1972 Gill 1980 Matsuno 1966

  18. Response to diabatic heating in the equatorial Indian Ocean

  19. Conclusions: Variability in Sahel rainfall on interannual to interdecadal time scales is strongly influenced by SST variability (ENSO and warming trends); The current generation of state-of-the-art atmospheric general circulation models displays skill in the prediction of Sahel rainfall when forced with 'perfect' SST anomalies; -how do we improve prediction of SSTs? (is it a coupled ocean-atmosphere problem?) How do we incorporate consideration of climate trends, e.g. trends attributed to climate change, in our predictions?

  20. What next? How can we improve predictions of sea surface temperature? How are the African and Indian monsoons connected? How is global warming going to affect tropical rainfall?

More Related