A preliminary study to investigate the biogeophysical impact of desertification on climate based on different latitudinal bands
Bibliographic record
Abstract
ABSTRACT Desertification is an international environmental challenge which poses a risk to portions of over 100 countries. Research into desertification and climate change has the potential to contribute to natural resources management and adaptation to climatic and other changes in Earth systems. An Earth system model of intermediate complexity (EMIC), the McGill Paleoclimate Model‐2 (MPM‐2) was used to explore the climatic biogeophysical effects of desertification in different latitude bands from 1700 to 2000 AD. It was found that latitudinal‐band desertification attributable to forest and grass removal caused global cooling, land surface albedo increasing and precipitation reduction in the Northern Hemisphere as well as heat transport increasing in global ocean. These results highlighted global climate reaction to local desertification and demonstrated that the location of the desertification projected a potentially differential impact on local and global climate. That was, desertification in 0°–15°N gave a somewhat minor effect on global and local climate; desertification in 45°–60°N caused a significant reduction in global temperature while desertification in 15°–30°N induced a prominent reduction in local temperature. In response to desertification, surface albedo change as a forcing was the dominant biogeophysical driver of climate over the Northern Hemisphere while precipitation change as a response was probably the primary driver of climate over the Southern Hemisphere. Overall, the regional desertification may cause a global climatic effect, especially concerning desert expansion along the 15°–30°N and 45°–60°N latitude bands, which led to a more prominent effect on the Earth's climate and even oceanic circulation. The results of this study provide useful information when comparing the effects of desertification in different latitude bands on climate.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".