Learn to visualise any climate claim as a tree of roots, branches, and twigs — then use AI to help you build it. Four prompt templates take you from a single claim to a structured map of what's solid, what's contested, and what's still unknown.
Climate science is complex, and public discourse often collapses it into a single yes/no question — "is it real?" — when the honest picture is a tree of interconnected claims with very different levels of support.
A mind map lets you hold the whole tree in view at once: strong branches next to fractured ones, settled roots next to foggy, uncharted terrain. It's a way to see the shape of an argument, not just its headline conclusion.
A single claim, broken into the components below. This is the pattern every map in this section follows.
| Roots | Core, foundational physics — e.g. CO₂ absorbs and re-emits infrared radiation. |
| Strong branches | Well-supported mechanisms — e.g. the observed rise in global average temperature alongside rising CO₂ concentrations. |
| Fractured branches | Incomplete or debated knowledge — e.g. the precise magnitude of cloud feedback effects. |
| Doubt clouds | Active research areas or major unknowns — e.g. the timing and threshold of climate tipping points. |
| Uncharted terrain | Emerging fields — e.g. deep-ocean heat absorption pathways not yet fully characterised. |
Visualise any climate claim as a tree of roots, branches, and twigs.
Create a mind-map about [Topic] as text using components such as: Roots, branches and Twigs Strong Branches Fractured Branches Fog, pillars, and doubt clouds Pillars with Cracks Crystal balls and broken crystal balls Skepticism components Uncharted Terrain
| Roots, branches & twigs | Core climate processes — e.g. the role of greenhouse gases, solar input, Earth's energy balance. Each root is a starting point (CO₂'s role in trapping heat), branching into detail (ocean heat absorption, ice-albedo effects). |
| Strong branches | Well-supported theories or principles — the greenhouse effect, the cooling impact of aerosols, the observed rise in global temperatures. |
| Fractured branches | Debated or incomplete understanding — long-term cloud feedback effects, how ocean currents will shift under warming. |
| Fog, pillars & doubt clouds | Significant uncertainty or active research — predictability of tipping points (e.g. ice-sheet collapse), non-linear climate responses. |
| Pillars with cracks | Widely accepted concepts challenged by new or conflicting evidence — model accuracy for regional variability, methane release rates from permafrost. |
| Crystal balls / broken crystal balls | Climate models (predictions of future conditions) and past failed predictions or model limitations needing revision. |
| Skepticism components | Critical perspectives that challenge mainstream views — e.g. debates over the extent of human influence versus natural variability. |
| Uncharted terrain | Emerging areas of climate science — deep-ocean heat absorption, unexplored feedback mechanisms. |
Create an Assumptions mind-map about [Topic] as text using components such as: Assumption Clouds of Strong Branches Assumption Clouds of Fractured Branches or Pillars with Cracks Foggy Assumption Clouds
| Strong-branch assumptions | Broadly accepted — e.g. increasing greenhouse gas concentrations lead to global warming; polar ice loss contributes to sea-level rise. |
| Fractured / cracked-pillar assumptions | Face challenges or uncertainty — the expected rate of warming from CO₂ doubling, the accuracy of extreme-weather model predictions. |
| Foggy assumptions | Deep uncertainties — the long-term carbon-cycle response, potential for abrupt shifts triggered by tipping points. |
Create a table of competing assumptions mind-map about [Topic]
The prompt organises and compares different assumptions related to a topic — exploring alternatives and competing perspectives in a structured, visual way, typically used to analyse complex concepts.
The table format sits mainstream assumptions next to competing ones so you can see, at a glance, how they connect, support, or contradict each other and the broader claim.
Create a table of competing evidence mind-map about [Topic]
For each claim or assumption in a topic, AI gathers evidence that supports or refutes it — data, observations, models, or studies — then lines up mainstream and competing evidence side by side for direct comparison.
This is the same discipline behind the Climate Claim Auditor Pack's evidence-visibility checks, applied specifically to building a visual map.