Long-Term Global Ground Heat Flux and Continental Heat Storage from Geothermal Data
Bibliographic record
Abstract
<p>Energy exchanges among climate subsystems are of critical importance to determine the climate sensitivity of the Earth's system to changes in external forcing, to quantify the magnitude and evolution of the Earth's energy imbalance, and to make projections of future climate. Additionally, climate phenomena sensitive to land heat storage, such as permafrost stability and sea level rise, are important due to their impacts on society and ecosystems. Thus, ascertaining the magnitude and change of the Earth's energy partition within climate subsystems has become urgent in recent years. </p><p>Here, we provide new global estimates of changes in ground surface temperature, ground surface heat flux and continental heat storage derived from geothermal data using an expanded database and new techniques developed in the last two decades. This new dataset contains 253 recent borehole profiles that were not included in previous estimates of global continental heat storage. In addition, our analysis considers additional sources of uncertainty that were not included in previous borehole studies. Results reveal markedly higher changes in ground heat flux and heat storage within the continental subsurface during the second half of the 20th century than previously reported, with a land mean temperature increase of 1 K and continental heat gains of around 12 ZJ relative to preindustrial times. Half of the heat gained by the continental subsurface since 1960 have occurred in the last twenty years. These results may be important for estimates of climate sensitivity based on energy budget constrains, as well as for the evaluation of global transient climate simulations in terms of the Earth’s heat inventory and energy-dependent subsurface processes. Our estimate of land heat storage is included in the new assessment of the components of the Earth’s heat inventory recently released (von Schuckmann et al. 2020), together with the oceans, the atmosphere and the cryosphere.</p>
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".