Jason C. Furtado Advisor: E. Di Lorenzo School of Earth & Atmospheric Sciences

1. What Uncertainties Exist in Tropical SST Reconstructions Derived From Tropical Precipitation Records? • Jason C. Furtado • Advisor: E. Di Lorenzo • School of Earth & Atmospheric Sciences • Georgia Institute of Technology • EAS Graduate Student Symposium • 2 November 2007

2. Previous Work Single Proxy Record Palmyra Coral Cobb et al. 2003 Multiple Proxy Records Reconstructed Leading SST Mode Evans et al. 2002

3. Aims of the Study Use tropical precipitation records to reconstruct tropical SSTs. • Compare two popular climate field reconstruction methods. • Examine the uncertainties associated with each method. • Evaluate the performance of a paleo-precipitation proxy network.

4. Data & Methods • Precipitation • CMAP (Xie and Arkin 1997) • Output from International Center for Theoretical Physics (ICTP) AGCM (Molteni 2003) • ERA-40 • SSTs - NOAA ER SSTs (Smith and Reynolds 2003) • Annual-mean anomalies used • Spatially smoothed and detrended • Reconstructions are done from 1979 - 2000.

5. Reconstruction Methods Premise:SSTs and precipitation are dynamically (and statistically) linked in the tropics. EOF METHOD 1) EOFs are time invariant 2) 3) Regression Coefficient

6. Reconstruction Methods Premise:SSTs and precipitation are dynamically (and statistically) linked in the tropics. EOF METHOD MULTIPLE REGRESSION Least-squares fitting (obtain optimal linear estimator E). 1) EOFs are time invariant 2) 3) Only retain first few covariability modes. Regression Coefficient Cross-validation method to test for robustness.

7. How Good Are The Reconstructions? • RMS Error: • Skill: • Spatial Correlation: Averaged over all 22 reconstructions

8. Evaluation - EOF Method

9. Evaluation -Multiple Regression

10. Spatial Correlations CMAP ICTP Correlation Mean r = 0.45 Mean r = 0.52 Mean r = 0.73 Mean r = 0.75 EOF Method EOF Method Multi-Regression Multi-Regression ERA-40 Mean r = 0.45 Mean r = 0.76 EOF Method Multi-Regression

11. Why is Multiple Regression Better? 1st Left Singular Vector 1st Right Singular Vector SST Precip. Dynamical Response to ENSO 2nd Left Singular Vector 2nd Right Singular Vector SST Precip. Dipole (Tripole) in Precipitation

12. Proxy Network Tree Rings Corals Marine Sediments Lake Sediments Speleothem Ice Cores Use multiple regression method with CMAP data from only these points for SST reconstructions

13. Evaluation - Proxy Network ~20% decrease in skill in the tropical Pacific and ~50% in the Indian Ocean Designing an Ideal Paleo-Precipitation Network Use the adjoint (ET) for sensitivity study.

14. But What About Stationarity? 1950 - 1978 1950-2000 SST RSV-2 (Precip) LSV-2 (SST) Out-of-phase relationship b/t Indian and E Pacific (1950-1978) In-phase relationship b/t Indian and E Pacific (1950-2000)

15. Conclusions • Multiproxy tropical precipitation records effectively reconstruct tropical SSTs. • The multiple regression method outperforms the EOF method, with a 20-30% improvement in skill in the tropical Pacific and much more in the Indian Ocean. • The paleo-precipitation proxy network recovers almost 50% of the observed variance in tropical SSTs and 80% of the skill vs. the full tropical precipitation field. • Is there a reconstruction technique that can account for the nonstationarity in the ENSO statistics / covariability modes?

16. Thank You! • Questions?

17. Add an error term to the precipitation in the linearized relationship: Define: ; sn = signal-to-noise ratio Error Propagation Analysis

18. Error Propagation Analysis