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Global Distribution of Crustal Material
Inferred by Seismology
Nozomu Takeuchi
(ERI, Univ of Tokyo)
(1) Importance of Directional Measurements
from geophysicists’ point of view
(2) Improvements of Neutrino Flux Modeling
in the seismological aspects
Parameters Required for Geo-neutrino Simulation
= Parameters Resolved by Geo-neutrino Observation
• Earth’s Composition
(compositions of crust & mantle)
• Earth’s Structure
(distributions of crustal materials)
Approach for Retrieving Earth’s Structure
• “Geophysical Decomposition” as a tool for interpretation
of the observed data
Importance of directional measurements
Fate of the Oceanic Crusts (1)
Prediction by High Pressure Experiments
Density measurements in the
upper mantle conditions
Ringwood & Irifune (1988)
Oceanic crusts can be
trapped around the 660, but
finally entrained into the lower mantle.
Fate of the Oceanic Crusts (2)
Suggestion by Mantle Convection Simulation
Nakagawa & Tackley (2005)
Oceanic crusts can
sink into the lowermost mantle, and
accumulate at the bottom of upwelling regions.
Fate of the Oceanic Crusts (3)
Indirect Evidence by Seismic Tomography
S velocity
Bulk-sound velocity
Masters et al. (2000)
Chemical heterogeneities are suggested
at the bottom of upwelling regions.
possible accumulation of oceanic crusts
Example Classification of Geo-Neutrino Source
(1) Surface Crust
(3) Crust in and around
Subducting Slabs
(2) Ambient Mantle
(4) Crust at the bottom of
upwelling regions (LLSVPs)
detector
Can we decompose the observed flux into the above four components?
We can utilize differences in incoming directions (directivities).
Expected Directivity by the Surface Crust (1)
Formulation by Enomoto et al. (2007)
dΦ Eν , 𝐫 ′
A dn Eν
=
dEν
dEν
neutrino flux
=
at the detector (r’)
d3 𝐫
V
decay rate x
a 𝐫 ′ ρ 𝐫 ′ P Eν , 𝐫 − 𝐫 ′
4π 𝐫 − 𝐫 ′ 2
intensity factor determined by
source distributions
U at Eν =1.2 MeV
Intensity Factor from j-th Directional Bin
d3 𝐫
ΔIj =
ΔVj
a 𝐫 ′ ρ 𝐫 ′ P Eν , 𝐫 − 𝐫 ′
4π 𝐫 − 𝐫 ′ 2
ΔVj
Expected Directivity by the Surface Crust (2)
N
W
E
S
distance from the center
bottoming radius
direction from the center
azimuth
painted color
log ΔIj
Difference in Expected Directivities
N
240-290 km depth
W
E
S
+2%
+1%
550-630 km depth
Obayashi et al. (2009)
“Geophysical Decomposition” As an Interpretation Tool
Ψ θ, ϕ
obs
= a1 Ψ θ, ϕ
crust
+ a3 Ψ θ, ϕ
θ : incident angle
reference model :
+ a2 Ψ θ, ϕ
slab
mantle
+ a4 Ψ θ, ϕ
LLSVP
ϕ : incident azimuth
a1 = a2 = 𝑎3 = 𝑎4 = 1
Coefficients can be determined by solving an inverse problem.
a1 > 1
larger mass fraction of depleted mantle?
a2 > 1
anomalies in bulk composition of the Earth?
a3 > 1
entrainments of continental crust?
megalith on the 660?
a4 > 1
enriched elements in the lowermost mantle?
Appropriate Choice of the Tomography Models
(short period data)
(broadband data)
Fukao et al. (2001)
Type of Seismic Data
short period (high sensitivity) sensor
broadband sensor
Usefulness of Broadband Waveforms
all frequencies
0.01-0.05 Hz
0.1-0.5 Hz
0.5-1 Hz
1-5 Hz
5-10 Hz
Short period data
broadband data
0.05-0.1 Hz
Comparison of Station Coverage
Broadband data
short period data
200 stations
20,000 stations
homogeneous
heterogeneous
Data Type and Obtained Tomography Models
Short period data
broadband data
500 km depth
Masters et al. (2000)
500 km depth
Bijwaard et al. (1998)
Models Obtained by Using
broadband data
:
overall structures, structures beneath oceans
short period data
:
detailed structures in subduction zones
Difficulties to Obtain Data-Based Crustal Models
• Current global model (CRUST 2.0) is not fully data-based.
• Too thin to resolve the global map.
• Sensitive frequency band is very “noisy”.
Recent Progresses in Seismology
• Dense broadband arrays with sufficient resolving power.
• Use of “noise” to reveal crustal structures.
Improvements in Crust Models (1)
Mapping by Broadband Data
Dense broadband arrays are beginning
to reveal crustal maps
Zheng et al. (2011)
Improvements in Crust Models (2)
Future Challenge
Broadband networks installed by ERI
• Use of broadband OBS data
• Data based crustal map in wide areas around Japan
Challenge to Detection of Crusts in the Mantle (1)
coherent
phase incoherent phase
(scattered waves)
Station 1
Station 2
Conventional
tomography
Station 3
coherent phase:
sensitive to larger-scale structures
incoherent phase: sensitive to smaller-scale structures
This Study
Challenge to Detection of Crusts in the Mantle (2)
Required Resolution
Current Resolution
Use of incoherent phases may fill the gap
between supply and demand.
Summary of The Talk
• “Geophysical Decomposition”
Importance of Directional Measurements
• Data Based Seismological Earth Models
Use of “noise” in our broadband OBS
Use of “incoherence” in seismic waveforms