Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017GL075661 |
Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach | |
Rezvanbehbahani, Soroush1,2; Stearns, Leigh A.1,2; Kadivar, Amir3; Walker, J. Doug1; van der Veen, C. J.4 | |
2017-12-28 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS
![]() |
ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2017 |
卷号 | 44期号:24 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Canada |
英文摘要 | Geothermal heat flux (GHF) is a crucial boundary condition for making accurate predictions of ice sheet mass loss, yet it is poorly known in Greenland due to inaccessibility of the bedrock. Here we use a machine learning algorithm on a large collection of relevant geologic features and global GHF measurements and produce a GHF map of Greenland that we argue is within similar to 15% accuracy. The main features of our predicted GHF map include a large region with high GHF in central-north Greenland surrounding the NorthGRIP ice core site, and hot spots in the Jakobshavn Isbraecatchment, upstream of Petermann Gletscher, and near the terminus of Nioghalvfjerdsfjorden glacier. Our model also captures the trajectory of Greenland movement over the Icelandic plume by predicting a stripe of elevated GHF in central-east Greenland. Finally, we show that our model can produce substantially more accurate predictions if additional measurements of GHF in Greenland are provided. |
英文关键词 | Greenland ice sheet geothermal heat flux machine learning |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000422954700006 |
WOS关键词 | BASAL MELT ; ICE ; MODEL ; FLOW ; TEMPERATURES ; LITHOSPHERE ; CRUST |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/26878 |
专题 | 气候变化 |
作者单位 | 1.Univ Kansas, Dept Geol, Lawrence, KS 66045 USA; 2.Univ Kansas, Ctr Remote Sensing Ice Sheets, Lawrence, KS 66045 USA; 3.McGill Univ, Dept Math & Stat, Quebec City, PQ, Canada; 4.Univ Kansas, Dept Geog & Atmospher Sci, Lawrence, KS 66045 USA |
推荐引用方式 GB/T 7714 | Rezvanbehbahani, Soroush,Stearns, Leigh A.,Kadivar, Amir,et al. Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach[J]. GEOPHYSICAL RESEARCH LETTERS,2017,44(24). |
APA | Rezvanbehbahani, Soroush,Stearns, Leigh A.,Kadivar, Amir,Walker, J. Doug,&van der Veen, C. J..(2017).Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach.GEOPHYSICAL RESEARCH LETTERS,44(24). |
MLA | Rezvanbehbahani, Soroush,et al."Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach".GEOPHYSICAL RESEARCH LETTERS 44.24(2017). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论