Assessing Arctic Ground Surface Temperatures from Borehole Temperatures and Paleoclimatic Model Simulations
Bibliographic record
Abstract
The surface temperature response to changes in our planet’s external forcing is larger at higher latitudes, a phenomenon known as polar amplification. The Arctic amplification has been particularly intense during the last century, with arctic-wide paleoclimatic reconstructions and state-of-the-art model simulations revealing a twofold arctic warming in comparison with the average global temperature increase. As a consequence, Arctic ground temperatures respond with rapid warming, but this response varies with snow cover and permafrost processes. Thus, changes in arctic ground temperatures are difficult to reconstruct from data, and to simulate in climate models. Here, we reconstruct the ground surface temperature histories of 120 borehole temperature profiles above 60ºN for the last 400 years. Past surface temperature evolution from each profile was estimated using a Perturbed Parameter Inversion approach based on a singular value decomposition method. Long-term surface temperature climatologies (circa 1300 and 1700 CE) and quasi-steady state heat flow are also estimated from linear regression through the depth range 200 to 300 m of each borehole temperature profile. The retrieved temperatures are assessed against simulated ground surface temperatures from five Past Millennium and five Historical experiments from the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3), and the fifth phase of the Coupled Model Intercomparison Project (CMIP5) archives, respectively. Preliminary results from borehole estimates and PMIP3/CMIP5 simulations reveal that changes in recent Arctic ground temperatures vary spatially and are related to each site’s earlier thermal state of the surface. The magnitudes of ground warming from data and simulations differ with large discrepancies among models. As a consequence, a better understanding of freezing processes at and below the air-ground interface is necessary to interpret subsurface temperature records and global climate model simulations in the Arctic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".