Why the Social Cost of Carbon is Six Times Higher Than We Think
Plain-language explainer for doi:10.5281/zenodo.20653285 (#403)
The central idea in one sentence
Standard climate economics treats each tipping element (Arctic ice, Amazon rainforest, West Antarctic ice sheet, …) independently; this paper proves that once you account for the triangular interactions between them, the social cost of carbon jumps from ~$51/tonne to ~$316/tonne.
The problem with “bilateral” climate models
Current integrated assessment models (IAMs) compute the damage from climate change by asking: how much does each tipping element cost if it tips? They add up the answers. This is the $H^0$ (bilateral) approach.
But tipping elements interact. The Amazon tipping makes Sahel droughts more likely. Arctic ice loss accelerates Greenland melting. West Antarctic ice and permafrost feedbacks are coupled. The $H^1$ (triangular) approach asks: can the bilateral damages be assembled into a globally consistent picture, or do the triangular interactions create irresolvable contradictions?
The mathematical finding
The paper applies sheaf cohomology — a tool for asking whether locally consistent data can be assembled globally — to the network of climate tipping elements.
The $H^1$ signal turns positive at $T^* \approx 1.8°C$ of warming — between the Paris Agreement targets of 1.5°C and 2.0°C. At this temperature, the triangular couplings between tipping elements become load-bearing: you cannot price the risks bilaterally and get a consistent answer. The correction factor is approximately $6\times$:
| Approach | Social cost of carbon |
|---|---|
| Bilateral ($H^0$, standard IAMs) | ~$51/tonne |
| $H^1$-corrected (triangular interactions) | ~$316/tonne |
Why this matters for policy
The Paris Agreement targets were set without accounting for $H^1$ effects. The analysis suggests 1.5°C is closer to the true topological tipping threshold than policymakers may realise — and that the economic case for aggressive mitigation is much stronger than bilateral models indicate.
What to read next
- The Topology of Risk (#398) — the primer on H⁰/H¹/H² without prerequisites
- Systemic Risk as H² (#397) — the financial crisis as the same mathematics
For the full technical treatment, see doi:10.5281/zenodo.20653285