Fine structure of P-wave velocity variations underneath the Central Pacific from PKP waves recorded at the China Seismic Network (CSN)

Si Hua Zheng, Xin Lei Sun, Xiao Dong Song

Research output: Contribution to journalArticlepeer-review

Abstract

Seismic PKP arrivals are sensitive to P velocity structure in the lowermost mantle. Earthquakes in South America recorded at China Seismographic Network (CSN) provide excellent samples of the lowermost mantle underneath the Central Pacific. Here we use differential travels between the AB and DF branches of PKP waves to constrain the small-scale variation of P waves beneath the Central Pacific. The use of differential AB-DF times reduces the biases of errors of earthquake locations and origin time and heterogeneity of the upper mantle but is sensitive to the structure in the lowermost mantle. Our results show large positive AB-DF differential time residuals across large areas of the lowermost mantle beneath the central Pacific, which may indicate the source region of the "Pacific Super Plume". The observed PKP residuals consist with the predictions for Grand's tomographic S model. Our inferred P velocity variation (which is about 2% in the bottommost 200 km D″ layer) is about 36% of the S velocity variation. However, we observe significant variations in travel-time residuals both inside the Central Pacific Plume and near in boundaries. The results have implications for understanding the structure and nature of the Pacific Super Plume.

Original languageEnglish (US)
Pages (from-to)184-192
Number of pages9
JournalActa Geophysica Sinica
Volume50
Issue number1
StatePublished - Jan 2007

Keywords

  • AB-DF differential travel times
  • Central Pacific
  • China Seismographic Network
  • Lowermost mantle
  • P-wave velocity
  • PKP-waves
  • Variation

ASJC Scopus subject areas

  • Geophysics
  • Geochemistry and Petrology

Fingerprint Dive into the research topics of 'Fine structure of P-wave velocity variations underneath the Central Pacific from PKP waves recorded at the China Seismic Network (CSN)'. Together they form a unique fingerprint.

Cite this