Global water availability and its distribution under the Coupled Model Intercomparison Project Phase Six scenarios
Bibliographic record
Abstract
Abstract Changes in the hydrological cycle have widespread consequences and remain uncertain under climate change. We analyse the changes in major water components of the hydrological cycle, that is, precipitation (P), runoff (Q), evapotranspiration (E), precipitation minus evapotranspiration (P − E), and terrestrial water storage (S), and quantify the uncertainties across the 21st century with Phase Six of the Coupled Model Intercomparison Project (CMIP6) simulations. The multimodel ensemble based on over 10 GCMs shows that P − E and Q share similar trends with P, with increases expected in northern high latitudes of Eurasia and North America, South Asia, and eastern Africa, and decreases expected in Central America, the Mediterranean, and the Amazon. The seasonal changes in S at mid and high latitudes are behind the large seasonal shifts in Q while changes in P − E are dominantly affected by P. The equatorial regions are expected to have the largest changes and intermodel variability. From low emission scenario SSP1‐2.6 to high emission scenario SSP5‐8.5, the spatial patterns for future changes remain consistent while more drastic and more widespread changes are expected globally over time with warming for all water components. Larger intermodel variability is also found under higher emission scenarios. The study provides a comprehensive perspective on the assessment of annual and seasonal changes in all water components within the hydrological cycle as well as the associated uncertainty with the latest CMIP6 simulations under three representative scenarios, providing the most updated climate information for formulating appropriate mitigation and adaptation.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 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".