
Antarctic Geothermal Heat Flow Model: Aq1
Author(s) -
Stål Tobias,
Reading Anya M.,
Halpin Jacqueline A.,
Whittaker Joanne M.
Publication year - 2021
Publication title -
geochemistry, geophysics, geosystems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.928
H-Index - 136
ISSN - 1525-2027
DOI - 10.1029/2020gc009428
Subject(s) - geology , geothermal gradient , observable , flow (mathematics) , antarctic ice sheet , glacier , meteorology , cryosphere , climatology , geophysics , geomorphology , mechanics , geography , physics , sea ice , quantum mechanics
We present a refined map of geothermal heat flow for Antarctica, Aq1, based on multiple observables. The map is generated using a similarity detection approach by attributing observables from geophysics and geology to a large number of high‐quality heat flow values ( N = 5,792) from other continents. Observables from global, continental, and regional datasets for Antarctica are used with a weighting function that allows the degree of similarity to increase with proximity and how similar the observables are. The similarity detection parameters are optimized through cross correlation. For each grid cell in Antarctica, a weighted average heat flow value and uncertainty metrics are calculated. The Aq1 model provides higher spatial resolution in comparison to previous results. High heat flow is shown in the Thwaites Glacier region, with local values over 150 mW m −2 . We also map elevated values over 80 mW m −2 in Palmer Land, Marie Byrd Land, Victoria Land and Queen Mary Land. Very low heat flow is shown in the interior of Wilkes Land and Coats Land, with values under 40 mW m −2 . We anticipate that the new geothermal heat flow map, Aq1, and its uncertainty bounds will find extended use in providing boundary conditions for ice sheet modeling and understanding the interactions between the cryosphere and solid Earth. The computational framework and open architecture allow for the model to be reproduced, adapted and updated with additional data, or model subsets to be output at higher resolution for regional studies.