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Bernhard Steinberger

Mantle evolution and dynamic topography of the African Plate. Bernhard Steinberger. Deutsches GeoForschungsZentrum, Potsdam and Physics of Geological Processes, Univ. Oslo and Center for Advanced Studies, Oslo. Motivation.

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Bernhard Steinberger

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  1. Mantle evolution and dynamic topography of the African Plate Bernhard Steinberger Deutsches GeoForschungsZentrum, Potsdam and Physics of Geological Processes, Univ. Oslo and Center for Advanced Studies, Oslo

  2. Motivation Understanding the mantle contribution to surface uplift and subsidence over time on a large scale

  3. Dynamic topography influences which regions are below sea level, and at what depth, and therefore where sediments and related natural resources may form • Before attempting to compute uplift and subsidence in the geologic past, we must first understand present-day dynamic topography Present-day topography

  4. Dynamic topography influences which regions are below sea level, and at what depth, and therefore where sediments and related natural resources may form • Before attempting to compute uplift and subsidence in the geologic past, we must first understand present-day dynamic topography Present-day topography + 200 m

  5. Dynamic topography influences which regions are below sea level, and at what depth, and therefore where sediments and related natural resources may form • Before attempting to compute uplift and subsidence in the geologic past, we must first understand present-day dynamic topography Present-day topography minus 200 m

  6. Outline • Mantle flow models based on seismic tomography • Dynamic topography for present-day – computation and comparision with observations • Inferring uplift and subsidence in the past from backward-advection of density anomalies and plate reconstructions

  7. Seismic tomography S-wave models (here: tx2007 of Simmons, Forte and Grand)

  8. Seismic tomography S-wave models (here: tx2007 of Simmons, Forte and Grand) • Conversion factor ~ 0.25 (Steinberger and Calderwood, 2006) – 4 % velocity variation ~ ~ 1 % density variation • Remove lithosphere

  9. Seismic tomography Converted to density anomalies • Conversion factor ~ 0.25 (Steinberger and Calderwood, 2006) – 4 % velocity variation ~ 1 % density variation • Remove lithosphere

  10. Computation of dynamic topography • radial viscosity structure based on mineral physics and optimizing fit to geoid etc. (Steinberger and Calderwood, 2006)‏ • Computation of dynamic topography through topography kernels (above: stress-free upper boundary; below: normal-stress-free with zero horizontal motion)

  11. Actual topography What to compare computations to for present-day

  12. Actual topography What to compare computations to for present-day MINUS Isostatic topography

  13. Actual topography What to compare computations to for present-day Non-isostatic topography = MINUS Isostatic topography

  14. Comparision non-isostatic vs. dynamic topography • TX2007 tomography • Lithosphere removed (cutoff 0.2%)

  15. Non-isostatic topography What to compare computations to for present-day

  16. Non-isostatic topography What to compare computations to for present-day MINUS Thermal topography

  17. Non-isostatic topography What to compare computations to for present-day residual topography = MINUS Thermal topography

  18. Comparision residual vs. dynamic topography • TX2007 tomography • Lithosphere removed (cutoff 0.2%) • Sea floor cooling removed

  19. Comparision residual vs. dynamic topography • TX2007 tomography • Lithosphere not removed • Sea floor cooling removed

  20. Correlation and ratio of dynamic vs. residual topography Best fit (in terms of variance reduction) Ratio globally Ratio on African plate Correlation on African plate Correlation globally

  21. Correlation and ratio of dynamic vs. residual topography Best fit (in terms of variance reduction) Ratio globally Ratio on African plate Correlation on African plate Correlation globally Further improvements by combination with surface tomography models, or ...

  22. Correlation and ratio of dynamic vs. residual topography Best fit (in terms of variance reduction) PRI-P05 PRI-S05 Ratio globally Ratio on African plate Correlation on African plate Correlation globally Mixing tomography models – here: Princeton P and S models

  23. TOPOS362D1 J362D28-P 4 6 Harvard Princeton 2 8 PRI-S05 PRI-P05 6 4 East West 6 4 SAW24B16 SAW642AN 4 6 Berkeley «smean» 7 3 9 1 TX2007 S20RTS

  24. Further improvements possible by using other lithosphere models Best results when using lithosphere thicknesses from Rychert et al. (based on seismic observations of Lithosphere-Asthenosphere-Boundary) where data are available ...

  25. Further improvements possible by using other lithosphere models Best results when using lithosphere thicknesses from Rychert et al. (based on seismic observations of Lithosphere-Asthenosphere-Boundary) Where data are available -- and the lithosphere model TC1 of Irina Artemieva (based on heat flow) elsewhere

  26. Comparision residual vs. dynamic topography • MIX-A tomography • Lithosphere from Rychert et al. (2010) and Artemieva (2006) • Sea floor cooling removed

  27. How much of the discrepancy is due to errors in observation-based “residual topography” and how much due to errors in modelled “dynamic topography”? What are the regional differences in this discrepancy? How does the agreement depend on spherical harmonic degree? Instead of looking at dynamic topography “in isolation” we hope to gain insight through also considering the geoid: Can we match the “expected” correlation and ratio of geoid and topography?

  28. In degree range 16 to 31 → expect high correlation → expect geoid-topography ratio around 0.01 residual topography too high above degree 10, too low below degree 6 ? Geoid / residual topography Model prediction for no-slip surface Geoid / uncorrected topography Model prediction for free-slip surface

  29. In degree range 16 to 31 → expect high correlation → expect geoid-topography ratio around 0.01 Higher correlation indicates better residual topography model

  30. In degree range 16 to 31 → expect high correlation → expect geoid-topography ratio around 0.01 Ratio about 1.4 % indicates better residual topography model 9 58 87 1.19 45

  31. Joint consideration with geoid indicates that discrepancies are, to a larger degree, caused by inaccuracies of residual topography model (e.g. inappropriate crustal model) Geoid / residual topography geoid-topography ratio Model predictions 9 58 87 45 1.19

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