Constraining Jumps in Density and Elastic Properties at the 660 km Discontinuity Using Normal Mode Data via the Backus Gilbert Method - INSU - Institut national des sciences de l'Univers Access content directly
Journal Articles Geophysical Research Letters Year : 2021

Constraining Jumps in Density and Elastic Properties at the 660 km Discontinuity Using Normal Mode Data via the Backus Gilbert Method

Abstract

We apply the Backus Gilbert approach to normal mode center frequency data, to constrain jumps in P, S, bulk sound speed and density at the "660" discontinuity in the earth's mantle (∼650-670 km depth). Different 1 D models are considered to compute sensitivity kernels. When using model PREM (Dziewonski & Anderson, 1981, Physics of the Earth and Planetary Interiors, 25, 297-356. doi:10.1016/0031 9201(81)90046 7) as reference, with a "660" at 670 km depth, the best fitting jumps in density, P and S wave speeds range from (5.1-8.2)%, (5.3-8.0)%, (5.0-7.0)%, respectively, so the PREM values lie outside the ranges of acceptable density and P wave speed jumps. When shifting the depth of "660" to 660 km, the density and S wave speed jumps increase, while the P wave speed jump decreases. Normal mode data do not support a global transition at 650 km depth. The density jumps are closer to those of pyrolite than PREM, while our bulk sound wave speed jumps suggest a larger garnet proportion at "660."
Fichier principal
Vignette du fichier
Geophysical Research Letters - 2021 - Lau - Constraining Jumps in Density and Elastic Properties at the 660 km.pdf (1.13 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Dates and versions

insu-03590053 , version 1 (26-02-2022)

Licence

Attribution

Identifiers

Cite

Harriet C. P. Lau, Barbara Romanowicz. Constraining Jumps in Density and Elastic Properties at the 660 km Discontinuity Using Normal Mode Data via the Backus Gilbert Method. Geophysical Research Letters, 2021, 48, pp.97-110. ⟨10.1029/2020GL092217⟩. ⟨insu-03590053⟩
26 View
23 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More