Projected expansion of hottest climate zones over Africa during the mid and late 21st century
Bibliographic record
Abstract
Abstract Projected shifts in thermal climate zones over Africa during the mid and late 21st century are assessed by employing the Thornthwaite thermal classification applied to 40 CMIP6 global climate models under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 forcing scenarios. The CMIP6 multimodel ensemble mean reproduces the observed pattern of thermal zones during the reference period, albeit with some discrepancies. The projections reveal a gradual expansion of the hottest thermal type consisting of a northward and southward displacement of torrid climate zones, with this effect intensifying as greenhouse gas (GHG) forcing increases and the time horizon moves from the mid to the end of the century. In particular, the Mediterranean region, almost all southern African countries, part of East Africa and most Madagascar predominantly warm in present-day conditions, are projected to face mostly hot climates in the mid—21st century and torrid by the end of the 21st century in the high-end forcing scenario. Generally, in the mid—21st century, torrid climates expand by up to ∼15%, 20% and 27% of total Africa’s land areas for the SSP1-2.6, SSP2-4.5 and SSP5-8.5, respectively, with these fractions increasing to ∼16%, 28% and 42% in the late 21st century. Therefore, at the end of the 21st century for the high-end GHG concentration scenario, the African continent will be covered by 81%–87% of torrid climate type, which will have enormous impacts on the sustainable development of African countries.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".