Bernhard Steinberger

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
6 4
PRI-S05 PRI-P05
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
32
(No Transcript)
33
(No Transcript)
34
(No Transcript)
35
(No Transcript)
36
(No Transcript)
37
(No Transcript)
38
(No Transcript)
39
(No Transcript)
40
(No Transcript)
41
(No Transcript)
42
(No Transcript)
43
(No Transcript)
44
(No Transcript)
45
(No Transcript)
46
(No Transcript)
47
(No Transcript)
48
(No Transcript)
49
(No Transcript)
50
(No Transcript)
51
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
52
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
53
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
54
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
55
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
56
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
57
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
58
Kufra
Taoudeni
Chad
Afar
Congo
South Africa
59
Afar
Kufra
Chad
Congo
South Africa
Taoudeni
60
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