Influence of 3D earth structure on glacial isostatic adjustment in the Russian Arctic

• Published in: Journal of Geophysical Research: Solid Earth
• Main Authors: Li, Tanghua, Khan, Nicole S., Baranskaya, Alisa V., Shaw, Timothy Adam, Peltier, W. Richard, Stuhne, Gordan R., Wu, Patrick, Horton, Benjamin Peter
• Other Authors: Asian School of the Environment, Earth Observatory of Singapore
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2022
• Subjects: Science::Geology; Sea-Level Change; Glacial Isostatic Adjustment; Lateral Heterogeneity; Rheology; Russian Arctic; Arctic; Barents Sea; Franz Josef Land; Moe; Peltier; Tive; White Sea; Ice Sheet
• Online Access: https://hdl.handle.net/10356/157193; https://doi.org/10.1029/2021JB023631

Analyses of glacial isostatic adjustment (GIA) and deglacial relative sea-level (RSL) change in the Russian Arctic deliver important insights into the Earth's viscosity structure and the deglaciation history of the Eurasian ice sheet complex. Here, we validate the 1D GIA models ICE-6G_C (VM5a) and ICE-7G_NA (VM7) and select new 3D GIA models in the Russian Arctic against a quality-controlled deglacial RSL database of >500 sea-level data points from 24 regions. Both 1D models correspond to the RSL data along the southern coast of the Barents Sea and Franz Josef Land from ∼11 ka BP to present but show notable misfits (>50 m at 10 ka BP) with the White Sea data. We find 3D model predictions of deglacial RSL resolve most of the misfits with the observed data for the White Sea while retaining comparable fits in other regions of the Russian Arctic. Our results further reveal: (a) RSL in the western Russian Arctic is sensitive to elastic lithosphere with lateral thickness variation and 3D viscosity structure in the upper mantle; and (b) RSL in the whole Russian Arctic is less sensitive to 3D viscosity structure in the lower mantle compared to the upper mantle. The 3D models reveal a compromise in the upper mantle between the background viscosity and scaling factor to best fit the RSL data, which needs to be considered in future 3D GIA studies. Ministry of Education (MOE) National Research Foundation (NRF) Published version Tanghua Li, Timothy A. Shaw, and Benjamin P. Horton are supported by the Singapore Ministry of Education Academic Research Fund MOE2019 -T3-1-004, MOE2018-T2-1-030 and MOE-T2EP50120-0007, the National Research Foundation Singapore, and the Singapore Ministry of Education, under the Research Centers of Excellence initia- tive. The research of W. Richard Peltier at Toronto is supported by NSERC discov- ery Grant A9627. The work of Alisa Baranskaya was supported by the Russian Science Foundation Grant 22-77-10,031; she used equipment and facilities obtained within the State Budget Theme ...