Impact of borehole depths on reconstructed estimates of ground surface temperature histories and energy storage
Bibliographic record
Abstract
Abstract Estimates of ground surface temperature changes and continental energy storage from geothermal data have become well‐accepted indicators of climatic changes. These estimates are independent contributions to the ensemble of paleoclimatic reconstructions and have been used for the validation of general circulation models, and as a component of the energy budget accounting of the global climate system. Recent global and hemispheric analyses of geothermal data were based on data available in the borehole paleoclimatology database, which contains subsurface temperature profiles from a minimum depth of 200 m to about 600 m. Because of the nature of heat conduction, different depth ranges contain the record of past and persistent changes in the energy balance between the lower atmosphere and the ground for different time periods. Here we examine the dependency of estimated ground surface temperature histories and the magnitude of the subsurface heat content on the depth of borehole temperature profiles. Our results show that uncertainties in the estimates of the long‐term surface temperature are in the range of ±0.5K. We conclude that previous estimates of ground surface temperature change remain valid for the period since industrialization, but longer‐term estimates are subject to considerable uncertainties. The subsurface heat content shows a larger range of variability arising from differences in depth of the borehole temperature profiles, as well as from differences in the time of data acquisition, spanning four decades. These results indicate that estimates of subsurface heat should be carried out with caution to decrease cumulative errors in any spatial analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".