The western Russian Arctic was partly covered by the large Eurasian ice sheet complex during the Last Glacial Maximum and is therefore a potentially useful additional focus area for Glacial Isostatic Adjustment (GIA) studies. To date few such studies have been conducted in the Russian Arctic due to the lack of high quality deglacial relative sea-level (RSL) data from this region. To rectify this, Baranskaya et al (2018, QSR) recently released a quality-controlled deglacial RSL database of the Russian Arctic. The database consists of ~400 sea-level index points, which define the discrete position of RSL at a given point in time and space, and ~250 marine and terrestrial limiting data, which constrain the lower and upper limits of the RSL, respectively. Here, we use the deglacial RSL database to validate the latest iterations in the development of 1D GIA models ICE-6G_C (VM5a) (Peltier et al., 2015, JGR) and ICE-7G_NA (VM7) (Roy and Peltier, 2017, GJI) and new 3D GIA models (inferred on the basis that the loading history is fixed to ICE-6G_C). GIA models with a 3D structure have the potential to better fit the deglacial RSL data because they incorporate lateral heterogeneity information derived from seismic tomography.
The RSL predictions of the 1D models ICE-6G_C (VM5a) and ICE-7G_NA (VM7) are found to well fit the deglacial RSL data along the southern coast of Barents Sea and on Franz-Josef-Land, but notable misfits are evident in the White Sea region. We find 3D model predictions (with a fixed ice model) improve the fits in White Sea while retaining comparable fits in other regions. Similarly, via tuning the ICE-7G_NA ice model in the White Sea area (with a fixed Earth model), we can improve the fits with the deglacial RSL data in the White Sea. The comparable fits of the best-fit 3D model and the ICE-7G_NA (VM7) model with locally modified loading history to the deglacial RSL data implies that the uncertainty in the ice model might be improperly mapped into 3D viscosity structure when a fixed model of deglaciation history is employed. We conclude that the uncertainty in ice model and correlation/interaction between the ice and Earth models need to be considered carefully in future GIA studies.