TY - JOUR
T1 - Joint Inversion for Surface Accumulation Rate and Geothermal Heat Flow From Ice-Penetrating Radar Observations at Dome A, East Antarctica. Part I
T2 - Model Description, Data Constraints, and Inversion Results
AU - Wolovick, M. J.
AU - Moore, J. C.
AU - Zhao, L.
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (No. 41941006) and COLD:Finnish Academy, #322430. Undated layer picks were produced by Sara Wolovick. We thank all of the participants in the AGAP project for their hard work in collecting and analyzing the data sets used in this study. M. J. Wolovick thanks the members of the Polar Geophysics Group at the Lamont‐Doherty Earth Observatory for years of stimulating discussion about Dome A and other places.
Publisher Copyright:
© 2021. American Geophysical Union. All Rights Reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/5
Y1 - 2021/5
N2 - Ice-penetrating radar data contain a wealth of information about the bed and internal structure of the ice sheet. While these data have long been used to diagnose the presence of basal water, infer attenuation rates, or explore the internal stratigraphy of the ice sheet, they have rarely been used jointly in a formal inverse model for the ice sheet temperature structure. Here, we invert a coupled thermomechanical ice sheet and basal hydrology model to infer both geothermal heat flow (GHF) and accumulation rate from multiple classes of radar observations in the area around Dome A, East Antarctica. Our forward model solves for a coupled steady state between the ice sheet flow field, temperature, and basal hydrology, including melt, water transport, and freeze-on. We fit radar observations of basal water, freeze-on, and internal layers, along with a GHF prior based on aeromagnetic observations. We minimize the combined misfit function by first using an evolutionary algorithm followed by localized perturbation tests. In addition to inferring the spatial distribution of GHF and accumulation rate, we are also able to estimate the uncertainty about our best-fit answer, as well as quantify how our result depends on each individual data constraint. Our results demonstrate a new method for combining multiple glaciological constraints into a single inverse model of the ice sheet, and give us a more rigorous picture of the information content provided by each data set. In a companion paper we analyze and interpret the best-fit model.
AB - Ice-penetrating radar data contain a wealth of information about the bed and internal structure of the ice sheet. While these data have long been used to diagnose the presence of basal water, infer attenuation rates, or explore the internal stratigraphy of the ice sheet, they have rarely been used jointly in a formal inverse model for the ice sheet temperature structure. Here, we invert a coupled thermomechanical ice sheet and basal hydrology model to infer both geothermal heat flow (GHF) and accumulation rate from multiple classes of radar observations in the area around Dome A, East Antarctica. Our forward model solves for a coupled steady state between the ice sheet flow field, temperature, and basal hydrology, including melt, water transport, and freeze-on. We fit radar observations of basal water, freeze-on, and internal layers, along with a GHF prior based on aeromagnetic observations. We minimize the combined misfit function by first using an evolutionary algorithm followed by localized perturbation tests. In addition to inferring the spatial distribution of GHF and accumulation rate, we are also able to estimate the uncertainty about our best-fit answer, as well as quantify how our result depends on each individual data constraint. Our results demonstrate a new method for combining multiple glaciological constraints into a single inverse model of the ice sheet, and give us a more rigorous picture of the information content provided by each data set. In a companion paper we analyze and interpret the best-fit model.
KW - Dome A
KW - East Antarctica
KW - genetic algorithm
KW - ice model
KW - ice-penetrating radar
KW - inversion
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U2 - 10.1029/2020JF005937
DO - 10.1029/2020JF005937
M3 - Article
AN - SCOPUS:85106890494
SN - 2169-9003
VL - 126
JO - Journal of Geophysical Research: Earth Surface
JF - Journal of Geophysical Research: Earth Surface
IS - 5
M1 - e2020JF005937
ER -