Jason C. Furtado Advisor: E. Di Lorenzo School of Earth & Atmospheric Sciences
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Transcript of Jason C. Furtado Advisor: E. Di Lorenzo School of Earth & Atmospheric Sciences
What Uncertainties Exist in Tropical SST
Reconstructions Derived From Tropical
Precipitation Records?
Jason C. FurtadoAdvisor: E. Di Lorenzo
School of Earth & Atmospheric SciencesGeorgia Institute of TechnologyEAS Graduate Student Symposium
2 November 2007
Previous Work
Single Proxy Record
Multiple Proxy Records
Cobb et al. 2003
Evans et al. 2002
Palmyra Coral
ReconstructedLeading SST Mode
Aims of the Study
•Compare two popular climate field reconstruction methods.
•Examine the uncertainties associated with each method.
•Evaluate the performance of a paleo-precipitation proxy network.
Use tropical precipitation records to reconstruct tropical SSTs.
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.
Reconstruction Methods
EOF METHOD
Premise: SSTs and precipitation are dynamically(and statistically) linked in the tropics.
Regression Coefficient
1) EOFs are time invariant2) 3)
Reconstruction Methods
MULTIPLE REGRESSION
Premise: SSTs and precipitation are dynamically(and statistically) linked in the tropics.
Least-squares fitting (obtain optimal linear estimator E).
Only retain first few covariability modes.
Cross-validation method to test for robustness.
EOF METHOD
Regression Coefficient
1) EOFs are time invariant2) 3)
How Good Are The Reconstructions?
•RMS Error:
•Skill:
•Spatial Correlation:
Averaged over all22 reconstructions
Evaluation - EOF MethodRMS ERROR SKILL
CMAP
ICTP MODEL OUTPUT
ERA-40
Evaluation -Multiple Regression
RMS ERROR SKILL
CMAP
ICTP MODEL OUTPUT
ERA-40
Spatial CorrelationsCorrelation
EOF MethodMulti-Regression
Mean r = 0.73
ICTP
EOF MethodMulti-Regression
Mean r = 0.75
CMAP
ERA-40
EOF MethodMulti-Regression
Mean r = 0.76
Mean r = 0.45 Mean r = 0.52
Mean r = 0.45
Why is Multiple Regression Better?
1st Left Singular Vector
2nd Left Singular Vector
1st Right Singular Vector
2nd Right Singular Vector
Dynamical
Response
to ENSO
Dipole (Tripole) in Precipitation
SST
SST
Precip.
Precip.
Proxy Network
Tree RingsCoralsMarine
SedimentsLake SedimentsSpeleothemIce Cores
Use multiple regression method with
CMAP data from only these points for SST
reconstructions
Evaluation - Proxy Network
~20% decrease in skill in the tropical Pacific and ~50% in the Indian OceanDesigning an Ideal Paleo-Precipitation Network
Use the adjoint (ET) for sensitivity study.
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)
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?
Thank You!
Questions?
Error Propagation Analysis•Add an error term to the precipitation in
the linearized relationship:
•Define: ; sn = signal-to-noise ratio
Error Propagation Analysissn = 10 sn = 2
Nonzero np
everywhere
np = 0 in
Eastern Hemisphe
renp = 0 in
Western Hemisphe
re