Bernhard Steinberger

Mantle evolution and dynamic topography of the African Plate

Deutsches GeoForschungsZentrum, Potsdam and

Physics of Geological Processes, Univ. Osloand

Center for Advanced Studies, Oslo

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

Motivation

•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

•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

•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

Outline

Mantle flow models based on seismic tomographyDynamic topography for present-day – computation and comparision with observationsInferring uplift and subsidence in the past from backward-advection of density anomalies and plate reconstructions

Seismic tomography

S-wave models (here: tx2007 of Simmons, Forte and Grand)

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

Seismic tomography

Converted to density anomalies

•Conversion factor ~ 0.25 (Steinberger and Calderwood, 2006) – 4 % velocity variation ~ 1 % density variation Remove lithosphere

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)

Actual topography What to compare computations to for present-day

Actual topography

MINUSIsostatic topography

What to compare computations to for present-day

Actual topography

MINUSIsostatic topography

Non-isostatic topography

=

What to compare computations to for present-day

Comparision non-isostatic vs. dynamic topographyTX2007 tomographyLithosphere removed (cutoff 0.2%)

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

Non-isostatic topography

MINUSThermal topography

What to compare computations to for present-day

Non-isostatic topography

residual topography

MINUSThermal topography =

What to compare computations to for present-day

Comparision residual vs. dynamic topographyTX2007 tomographyLithosphere removed (cutoff 0.2%)Sea floor cooling removed

Comparision residual vs. dynamic topographyTX2007 tomographyLithosphere not removedSea floor cooling removed

Correlation globally

Correlation on African plate

Correlation and ratio of dynamic vs. residual topography

Ratio globally

Ratio on African plate

Best fit (in terms of variance reduction)

Correlation globally

Correlation on African plate

Correlation and ratio of dynamic vs. residual topography

Ratio globally

Ratio on African plate

Best fit (in terms of variance reduction)

Further improvements by combination with surface tomography models, or ...

Correlation globally

Correlation on African plate

Correlation and ratio of dynamic vs. residual topography

Ratio globally

Ratio on African plate

Best fit (in terms of variance reduction)

Mixing tomography models – here: Princeton P and S models

PRI-P05 PRI-S05

TOPOS362D1 J362D28-P

4 6

TX2007 S20RTS 9 1

4 6

6 4

SAW24B16 SAW642AN

PRI-S05 PRI-P05Harvard Princeton

Berkeley «smean»

2 8

7 3

East West

6 4

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

Further improvements possible by using other lithosphere modelsBest 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

Comparision residual vs. dynamic topographyMIX-A tomographyLithosphere from Rychert et al. (2010) and Artemieva (2006)Sea floor cooling removed

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?

Model prediction for no-slip surface

Model prediction for free-slip surface

Geoid / uncorrectedtopography

Geoid / residual topography

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 ?

In degree range 16 to 31→ expect high correlation→ expect geoid-topography ratio around 0.01

Higher correlation indicates better residual topography model

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

Joint consideration with geoid indicates that discrepancies are, to a larger degree, caused by inaccuracies of residual topography model (e.g. inappropriate crustal model)

9 58

87 1.19 45

geoid

-topogra

phy r

ati

o

Geoid / residual topography

Model predictions

CongoAfar

South Africa

KufraChad

Taoudeni

CongoAfar

South Africa

KufraChad

Taoudeni

CongoAfar

South Africa

KufraChad

Taoudeni

CongoAfar

South Africa

KufraChad

Taoudeni

CongoAfar

South Africa

KufraChad

Taoudeni

CongoAfar

South Africa

KufraChad

Taoudeni

CongoAfar

South Africa

KufraChad

Taoudeni

CongoAfar

South Africa

KufraChad

Taoudeni

Afar

CongoSouth Africa

KufraChad

Taoudeni

Conclusions→ Present-day dynamic topography computed from mantle density anomalies inferred from tomography→ Need to “cut out” lithosphere→ Better fit through «mixing» tomography models→ Further improved fit with lithosphere models based on thermal and (where available) seismic data→ Joint consideration of geoid and topography indicates that much of the remaining misfit is due to errors in residual topography. → Past dynamic topography through combining plate reconstructions in absolute reference frame with backward-advected density and flow→ Problem: signal decays back in time→ Possible solution (partially): adjoint methods