The Tipping Points Modelling Intercomparison Project (TIPMIP): Assessing tipping point risks in the Earth system
Bibliographic record
Abstract
Abstract. The risk of transgressing critical thresholds triggering nonlinear change in the Earth system increases with rising human pressures from greenhouse gas emissions, land-use change and other drivers. Several key components of the Earth System such as the Greenland and Antarctic ice sheets, permafrost, the Atlantic Meridional Overturning Circulation (AMOC), and boreal and tropical forests as well as mountain glaciers, terrestrial hydrological systems and the Sahel region have been suggested to exhibit self-amplifying feedback processes that could lead to non-linear and often abrupt and/or irreversible transitions with far-reaching biophysical and socio-economic consequences. While concerns within the scientific community, general public and among policy- and decision-makers are growing, significant uncertainties remain regarding the critical thresholds, timescales, interactions and impacts of such tipping dynamics. To address these critical knowledge gaps, we here present the Tipping Points Modelling Intercomparison Project (TIPMIP), an international collaborative effort to systematically assess tipping point risks using state-of-the-art coupled Earth System Models and stand-alone domain models, e.g., ice sheet and land system models. Building on the success of established Model Intercomparison Projects (MIPs), TIPMIP aims to standardize model experiments, quantify uncertainty ranges for critical forcing thresholds, and provide a multi-model assessment of tipping dynamics across key Earth system components. TIPMIP will enhance our ability to anticipate and mitigate the risks associated with Earth system tipping points, and support science-based decision-making in the face of high-end impacts and deep uncertainties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".