The thin hot plume beneath Iceland

  • Richard M. Allen
  • , Guust Nolet
  • , W. Jason Morgan
  • , Kristín Vogfjörd
  • , Bergur H. Bergsson
  • , Pálmi Erlendsson
  • , G. R. Foulger
  • , Steinunn Jakobsdóttir
  • , Bruce R. Julian
  • , Matt Pritchard
  • , Sturla Ragnarsson
  • , Ragnar Stefánsson

Research output: Contribution to journalArticlepeer-review

Abstract

We present the results of a seismological investigation of the frequency-dependent amplitude variations across Iceland using data from the HOTSPOT array currently deployed there. The array is composed of 30 broad-band PASSCAL instruments. We use the parameter t(*), defined in the usual manner from spectral ratios (Halderman and Davis 1991), to compare observed S-wave amplitude variations with those predicted due to both anelastic attenuation and diffraction effects. Four teleseismic events at a range of azimuths are used to measure t(*). A 2-D vertical cylindrical plume model with a Gaussian-shaped velocity anomaly is used to model the variations. That part of t(*) caused by attenuation was estimated by tracing a ray through IASP91, then superimposing our plume model velocity anomaly and calculating the path integral of 1/vQ. That part of t(*) caused by diffraction was estimated using a 2-D finite difference code to generate synthetic seismograms. The same spectral ratio technique used for the data was then used to extract a predicted t(*). The t(*) variations caused by anelastic attenuation are unable to account for the variations we observe, but those caused by diffraction do. We calculate the t(*) variations caused by diffraction for different plume models and obtain our best-fit plume, which exhibits good agreement between the observed and measured t(*). The best-fit plume model has a maximum S-velocity anomaly of - 12 per cent and falls to 1/e of its maximum at 100 km from the plume centre. This is narrower than previous estimates from seismic tomography, which are broadened and damped by the methods of tomography. This velocity model would suggest greater ray theoretical traveltime delays than observed. However, we find that for such a plume, wave-front healing effects at frequencies of 0.03-0.175 Hz (the frequency range used to pick S-wave arrivals) causes a 40 per cent reduction in traveltime delay, reducing the ray theoretical delay to that observed.

Original languageEnglish
Pages (from-to)51-63
Number of pages13
JournalGeophysical Journal International
Volume137
Issue number1
DOIs
Publication statusPublished - Apr 1999

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 1 - No Poverty
    SDG 1 No Poverty
  2. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  3. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  4. SDG 4 - Quality Education
    SDG 4 Quality Education
  5. SDG 5 - Gender Equality
    SDG 5 Gender Equality
  6. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  7. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  8. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  9. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  10. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities
  11. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  12. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  13. SDG 13 - Climate Action
    SDG 13 Climate Action
  14. SDG 14 - Life Below Water
    SDG 14 Life Below Water
  15. SDG 15 - Life on Land
    SDG 15 Life on Land
  16. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions
  17. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Other keywords

  • Attenuation
  • Diffraction
  • Plume
  • S waves
  • Spectral analysis
  • Upper mantle

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