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 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 the upper 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 suggested at 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).

neutrino flux at the detector (r’) decay rate = x intensity factor determined by source distributions Formulation by Enomoto et al. (2007) Expected Directivity by the Surface Crust (1) Intensity Factor from j-th Directional Bin V

Expected Directivity by the Surface Crust (2) N S EW distance from the center bottoming radius azimuth direction from the center painted color

Difference in Expected Directivities +2%+1% N S EW km depth km depth Obayashi et al. (2009)

“Geophysical Decomposition” As an Interpretation Tool : incident angle : incident azimuth Coefficients can be determined by solving an inverse problem. reference model : larger mass fraction of depleted mantle? anomalies in bulk composition of the Earth? entrainments of continental crust? megalith on the 660? 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

Hz Hz Hz Hz 1-5 Hz 5-10 Hz Usefulness of Broadband Waveforms all frequencies broadband data Short period data

Comparison of Station Coverage 200 stations 20,000 stations short period data Broadband data homogeneous heterogeneous

500 km depth Masters 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 oceans broadband 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.

Importance of Data Based Science Kodaira et al. (2010) Crust 2.0 Crustal Structure by Exploration Data Improvements in Crust Models (1) (short period data)

Improvements in Crust Models (1) Zheng et al. (2011) Dense broadband arrays are beginning to 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

OBS observations in (short period data) Validation of our crustal map Further refinements in the resolved regions

Challenge to Detection of Crusts in the Mantle (1) Station 1 Station 2 Station 3 coherent phase incoherent phase (scattered waves) coherent phase: sensitive to larger-scale structures incoherent phase: sensitive to smaller-scale structures Conventional tomography This Study

Challenge to Detection of Crusts in the Mantle (2) Required ResolutionCurrent 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

Comparison of 3-D Seismic Velocity Models Predominance of larger lateral scale length of heterogeneities. S velocity structure at 2800 km depth Low velocity province beneath the Pacific and Africa.