Is transient creep necessary to explain sea level and crustal uplift data from Greenland?

In the 1980s, a series of articles explored the potential importance of transient rheology in the glacial isostatic adjustment (GIA) process (e.g., Peltier et al., Geophys. Res. Lett., 1980; Sabadini et al., Geophys. Res. Lett., 1985; Yuen et al., J. Geophys. Res., 1986). However, in the absence of...

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Bibliographic Details
Main Authors: Pan, L., Mitrovica, J., Milne, G., Woodroffe, S.
Format: Conference Object
Language:English
Published: 2023
Subjects:
Online Access:https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020909
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Summary:In the 1980s, a series of articles explored the potential importance of transient rheology in the glacial isostatic adjustment (GIA) process (e.g., Peltier et al., Geophys. Res. Lett., 1980; Sabadini et al., Geophys. Res. Lett., 1985; Yuen et al., J. Geophys. Res., 1986). However, in the absence of observational evidence for a time dependent viscous response, this level of additional modeling complexity fell out of favor in the GIA community. Recently, a comparison of viscosity models inferred from Holocene relative sea level data and modern crustal uplift rates in Greenland – the latter suggestive of a significantly lower Maxwell viscosity than the former – has renewed interest in the intriguing possibility of transient mantle creep (Adhikari et al., Earth Planet. Sci. Lett., 2021). However, an unambiguous argument that transient rheology is necessary must rule out the possibility that a class of (Maxwell) viscosity models with general depth and lateral variability may reconcile both data sets. We present numerically derived 1-D sensitivity kernels for the relative sea level and uplift rate observations that demonstrate that these two data sets have independent sensitivities to variations in depth-dependent mantle viscosity. Moreover, we explore – within a broad class of such 1-D models – the level of fit that can be achieved to these data using a multi-layer Maxwell viscosity profile. Future work on this important, outstanding issue should extend this analysis of uniqueness using 3-D sensitivity kernels derived via adjoint methods (Crawford et al., Geophys. J. Int., 2018).