The climate crisis is often described in numbers: degrees of warming, parts per million of carbon dioxide, targets for 2030 and 2050.But behind every projection and pathway lies something less visible and more contested: the models that generate them, and the political assumptions those models quietly encode. At King’s College London,the project “Modeling the Climate Crisis: The Politics of Paradigmatic Logics” takes aim at this hidden infrastructure of climate governance,asking a provocative question: what if the tools we use to plan our way out of catastrophe are themselves shaping the crisis?
From integrated assessment models that weigh the costs of mitigation against economic growth,to climate scenarios that make certain futures appear “realistic” and others “unthinkable,” the climate debate is increasingly mediated by complex computational systems. These models do not merely describe the world; they help decide which policies are deemed feasible, which sacrifices are acceptable, and whose lives are protected-or put at risk. As governments, corporations and international agencies lean ever more heavily on predictive analytics, the stakes of how climate models are built, interpreted and deployed have never been higher.
By tracing the “paradigmatic logics” that underpin these tools-the economic theories, value systems and geopolitical interests baked into their code-researchers at King’s aim to unpack how climate modeling has become a site of power. Their work situates climate models not as neutral scientific instruments, but as political actors in their own right, influencing negotiations, shaping public narratives and constraining the imagination of possible futures. In doing so, the project invites a rethinking of what counts as rational climate policy-and who gets to decide.
Interrogating the models How climate science frameworks shape what counts as crisis
Behind every emissions curve and temperature projection lies a set of choices about what matters, who is visible, and which futures are even thinkable. Climate models frequently enough privilege what can be easily quantified-carbon budgets, radiative forcing, gross domestic product-while sidelining lived experience, ancient responsibility and uneven vulnerability. This is not a neutral omission. It means that a coastal village threatened with displacement can vanish into a global average, and that systemic injustice appears as statistical “noise.” In this sense, scientific frameworks do not simply describe crisis; they curate it, filtering a complex social and ecological emergency into a legible, governable problem.
These underlying logics shape the politics that follow. What appears in scenarios as the most “rational” pathway-gradual decarbonisation, speculative carbon removal, continued growth-rests on a particular vision of order, risk and acceptable loss. As a result,some responses are pre-legitimised,while others are rendered unthinkable or “too radical.” Within this terrain, researchers, policymakers and activists are beginning to ask pointed questions such as:
- Which harms are tracked, and which are treated as externalities?
- Whose knowledge is embedded in model design, and whose is excluded?
- What timelines are prioritised: election cycles, investment horizons, or generational survival?
- Which regions are framed as sacrifice zones for global stability?
| Model Focus | Often Center-Stage | Often Marginalised |
|---|---|---|
| Integrated assessment | Cost-benefit, GDP, energy mix | Labour, land rights, culture |
| Risk projections | Infrastructure, assets, markets | Informal housing, subsistence livelihoods |
| Mitigation scenarios | Technologies, efficiency, innovation | Care work, Indigenous stewardship |
Paradigmatic power The political interests embedded in climate projections and scenarios
Behind the façade of neutral graphs and color-coded maps lies a quiet struggle over which futures are thinkable, fundable, and ultimately governable. Climate models do not simply describe the world; they prioritise certain questions, actors, and solutions while sidelining others. Integrated assessment models, as a notable example, frequently enough encode assumptions that favour market-based instruments, incremental technological fixes, and economic growth as non-negotiable, turning these into the default horizon of policy imagination.What rarely appears on the dashboard is just as telling: structural redistribution, post-growth pathways, or the political conflicts triggered by radical decarbonisation. These omissions are not mere oversights; they reflect the institutional interests of governments, corporations, and global organisations that commission, endorse, and amplify particular scenarios as “realistic” or “responsible”.
That influence is exercised not only through funding and agenda-setting, but also via technical norms that shape what counts as “good science”. Calibration choices, discount rates, and risk metrics are charged with ideological content, even when presented as routine modelling decisions. Consequently, models frequently enough function as gatekeepers of credibility, filtering out proposals that do not sit comfortably within prevailing economic orthodoxies. The result is a subtle hierarchy of futures:
- Prioritised: growth-compatible mitigation, large-scale carbon removal, high-tech energy transitions
- Marginalised: demand reduction, decolonial climate reparations, community-led energy autonomy
- Silenced: systemic degrowth, radical wealth redistribution, binding limits on extraction
| Modelling Choice | Hidden Political Effect |
|---|---|
| High discount rate | Devalues future climate harms |
| GDP as core welfare metric | Locks in growth-centric policies |
| Tech-optimistic scenarios | Delays tough emission cuts now |
From abstraction to action Rethinking modeling practices for just and effective climate policy
Climate models frequently enough operate as rarefied abstractions-immense equations humming on distant servers-yet their outputs are translated into starkly material outcomes: who gets flood defences, which regions face decarbonisation mandates, and whose livelihoods are deemed “transition risks.” To close this gap, modeling needs to be reoriented from a narrow fixation on aggregate efficiency toward distributive justice, political feasibility, and lived vulnerability. That means embedding social science and local knowledge directly into model design, not as an afterthought or a “sensitivity scenario.” It also requires questioning default assumptions-endless growth, frictionless technology rollouts, and uniform policy compliance-that quietly favour some constituencies while rendering others invisible. A more reflexive practise can surface these buried value judgments,making explicit what has long been smuggled in as “neutral” science.
- Interrogate baseline assumptions about growth, consumption and technology.
- Co-produce scenarios with affected communities, not just expert panels.
- Expose trade-offs between mitigation, adaptation and social protection.
- Translate model outputs into locally legible risks and opportunities.
| Modeling Focus | Policy Effect |
|---|---|
| Carbon price only | Cheaper emissions cuts, higher social backlash |
| Equity-weighted impacts | Slower change, stronger long-term legitimacy |
| Place-based scenarios | Fewer blind spots, more tailored support |
Reimagined this way, models stop being oracular devices that certify a single “optimal pathway” and become contested public instruments that map out competing futures and their winners and losers. Rather of offering policymakers an aura of inevitability-“the model made us do it”-they can provide structured spaces for democratic argument about which risks are tolerable, whose costs are acceptable, and what forms of transition are politically and ethically viable. When paired with transparent documentation, open data, and participatory review, modeling shifts from technocratic abstraction to a form of accountable climate governance, where numerical precision is less vital than whether the choices it underwrites are fair, explainable and open to revision.
Recommending reform Building transparent participatory and accountable climate modeling at Kings College London
At the heart of transforming how climate futures are modeled lies a shift from closed expert-driven systems to collaborative infrastructures that are open to scrutiny and intervention.At King’s,this means building workflows where data sources,assumptions and value choices are not only documented,but also contestable by those affected by the projections. A practical reform agenda includes:
- Open-access model documentation that explains key assumptions in plain language
- Publicly visible version histories for datasets, parameters and code
- Stakeholder forums involving communities, policymakers and NGOs in scenario design
- Ethics reviews for high-impact scenarios, akin to research ethics boards
- Autonomous audits of models to test for bias, blind spots and political implications
| Pillar | Practice | Outcome |
|---|---|---|
| Clarity | Publish assumptions and code | Readable, reviewable models |
| Participation | Co-create scenarios | Locally grounded futures |
| Accountability | Audit and feedback loops | Corrective governance |
Reform also requires institutional commitments that extend beyond any single research group.Embedding climate modeling within university-wide governance structures would align technical practice with public responsibility. This could involve:
- Cross-departmental oversight panels including climate scientists, social scientists and legal scholars
- Mandatory impact statements for models used in external policy advice
- Data justice guidelines to protect vulnerable communities from misrepresentation
- Training for researchers in political economy, ethics and science communication
- Formal channels for communities to challenge or appeal model outputs used in decisions
Key Takeaways
As the climate crisis accelerates, the models we build to understand it are doing more than projecting temperature curves or sea-level rise; they are helping to define what counts as rational action, credible risk, and legitimate sacrifice. King’s College London’s exploration of the “politics of paradigmatic logics” makes one thing clear: climate models are never just technical artefacts.They stabilise certain futures as thinkable and render others implausible,if not invisible.
That insight has concrete implications. It challenges policymakers to interrogate the assumptions that underpin the scenarios on which they rely, from discount rates to technological optimism. It pushes scientists and modellers to be more transparent about the value judgments embedded in their work.And it invites the wider public to see climate projections not as neutral forecasts, but as contested visions of collective destiny.
In an era of tightening carbon budgets and narrowing political options, the struggle over how we model the climate is, increasingly, a struggle over how we imagine power, responsibility and justice on a planetary scale.Understanding the politics of those paradigms will not, on its own, solve the crisis. But without that understanding, we risk fighting for the future with tools that quietly reproduce the very logics that brought us to the brink.
