Response of Permafrost Thermal Regime to Climate Change over Northern Hemisphere in the 21st Century
Bibliographic record
Abstract
Based on the CMIP5 simulation and numerical model, the permafrost thermal regimes over Northern Hemisphere land during the early (2016-2035), middle (2046-2065) and late (2080-2099) period of 21st century are projected, and its relationship with climate change is also analyzed. The results show that, relative to the reference period of 1986-2005, the mean annual ground temperature (MAGT) over Northern Hemisphere shows an increasing trend, with a decreasing trend of the depth of zero annual amplitude (DZAA), and the most significant changes occur in Siberia, Tibetan Plateau, Canada arctic and Alaska, and the changes in MAGT and DZAA grow larger with time and emission, especially during the LP for RCP8.5, MAGT will increase by 4 and DZAA decreases by 1.5 m (the relative change exceeds 20%) in most regions. The changes of permafrost in the 21st century mainly depend on the changes of cold permafrost. The relationship between MAGT and air temperature as well as that between DZAA and air temperature suggests that the increase of MAGT and the decrease of DZAA are related to the increase of air temperature in winter, especially in January. However, the rate of change in MAGT and DZAA gradually declines, with the temperature increasing.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".