Global Distribution of Crustal MaterialInferred 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

• Earth’s Structure

(compositions of crust & mantle)

(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

Prediction by High Pressure Experiments

Ringwood & Irifune (1988)

Density measurements in theupper mantle conditions

Oceanic crusts can be trapped around the 660, but finally entrained into the lower mantle.

Fate of the Oceanic Crusts (1)

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 (2)

Fate of the Oceanic Crusts (3)Indirect Evidence by Seismic Tomography

S velocity Bulk-sound velocity

Masters et al. (2000)

Chemical heterogeneities are suggestedat the bottom of upwelling regions.

possible accumulation of oceanic crusts

Example Classification of Geo-Neutrino Source

continental crust oceanic crust

(1) Surface Crust (2) Ambient Mantle

(3) Crust in and around Subducting Slabs

(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).

dΦ (Eν ,𝐫 ′ )d Eν

=Adn (Eν )d E ν

∫ d3𝐫a (𝐫 ′ ) ρ (𝐫 ′) P (Eν ,|𝐫−𝐫 ′|)

4 π|𝐫−𝐫 ′|2

neutrino fluxat the detector (r’) decay rate= x intensity factor determined by

source distributions

(U at Eν=1.2  MeV )

Formulation by Enomoto et al. (2007)

Expected Directivity by the Surface Crust (1)

Intensity Factor from j-th Directional Bin

ΔI j=∫ΔV j

d3𝐫a (𝐫 ′ ) ρ (𝐫 ′ ) P (E ν ,|𝐫−𝐫′|)

4 π|𝐫−𝐫 ′|2

ΔV j

V

Expected Directivity by the Surface Crust (2)

N

S

EW

distance from the center bottoming radius

azimuthdirection from the center

painted color log ΔI j

Difference in Expected Directivities

+2% +1%

N

S

EW

240-290 km depth

550-630 km depth

Obayashi et al. (2009)

“Geophysical Decomposition” As an Interpretation Tool

+a3Ψ (θ ,ϕ )slab+a4Ψ (θ ,ϕ )LLSVPΨ (θ ,ϕ )obs=a1Ψ (θ ,ϕ )crust+a2Ψ (θ ,ϕ )mantle

θ ϕ: incident angle : incident azimuth

Coefficients can be determined by solving an inverse problem.

a1=a2=𝑎3=𝑎4=1reference model :

a1>1

a2>1

larger mass fraction of depleted mantle?

anomalies in bulk composition of the Earth?

a3>1entrainments of continental crust?megalith on the 660?

a4>1 enriched elements in the lowermost mantle?

(short period data)

(broadband data)

Appropriate Choice of the Tomography Models

Fukao et al. (2001)

broadband sensorshort period (high sensitivity) sensor

Type of Seismic Data

0.01-0.05 Hz

0.05-0.1 Hz

0.1-0.5 Hz

0.5-1 Hz

1-5 Hz

5-10 Hz

Usefulness of Broadband Waveforms

all frequencies

broa

dban

d da

taShort period data

Comparison of Station Coverage

200 stations 20,000 stations

short period dataBroadband data

homogeneous heterogeneous

500 km depthMasters et al. (2000)

Data Type and Obtained Tomography Models

Bijwaard et al. (1998)500 km depth

broadband data Short period data

Models Obtained by Using

: overall structures, structures beneath oceansbroadband data

short period data : detailed structures in subduction zones

Difficulties to Obtain Data-Based Crustal Models

• 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.

• Current global model (CRUST 2.0) is not fully data-based.

Improvements in Crust Models (1)

Zheng et al. (2011)

Dense broadband arrays are beginningto reveal crustal maps

Mapping by Broadband Data

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)

Station 1

Station 2

Station 3

coherentphase incoherent phase

(scattered waves)

coherent phase: sensitive to larger-scale structures

incoherent phase: sensitive to smaller-scale structures

Conventionaltomography

This Study

Challenge to Detection of Crusts in the Mantle (2)

Required Resolution Current Resolution

Use of incoherent phases may fill the gapbetween 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