論文

査読有り 最終著者 本文へのリンクあり 国際共著 国際誌
2019年12月

Constraining the geothermal heat flux in Greenland at regions of radar-detected basal water

Journal of Glaciology
  • Soroush Rezvanbehbahani
  • ,
  • Leigh A. Stearns
  • ,
  • C. J. Van der Veen
  • ,
  • Gordon K. A. Oswald
  • ,
  • Ralf Greve

65
254
開始ページ
1023
終了ページ
1034
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1017/jog.2019.79
出版者・発行元
Cambridge University Press

The spatial distribution of basal water critically impacts the evolution of ice sheets. Current estimates of basal water distribution beneath the Greenland Ice Sheet (GrIS) contain large uncertainties due to poorly constrained boundary conditions, primarily from geothermal heat flux (GHF). The existing GHF models often contradict each other and implementing them in numerical ice-sheet models cannot reproduce the measured temperatures at ice core locations. Here we utilize two datasets of radar-detected basal water in Greenland to constrain the GHF at regions with a thawed bed. Using the three-dimensional ice-sheet model SICOPOLIS, we iteratively adjust the GHF to find the minimum GHF required to reach the bed to the pressure melting point, GHF_pmp, at locations of radar-detected basal water. We identify parts of the central-east, south and northwest Greenland with significantly high GHF_pmp. Conversely, we find that the majority of low-elevation regions of west Greenland and parts of northeast have very low GHF_pmp. We compare the estimated constraints with the available GHF models for Greenland and show that GHF models often do not honor the estimated constraints. Our results highlight the need for community effort to reconcile the discrepancies between radar data, GHF models, and ice core information.

リンク情報
DOI
https://doi.org/10.1017/jog.2019.79 本文へのリンクあり
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000510631500013&DestApp=WOS_CPL
ID情報
  • DOI : 10.1017/jog.2019.79
  • ISSN : 0022-1430
  • eISSN : 1727-5652
  • Web of Science ID : WOS:000510631500013

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