As the UK pushes towards its net zero commitments, the models used to predict climate and economic changes are increasingly crucial. These sophisticated tools help policymakers estimate the costs and benefits of climate action, anticipate economic shocks from extreme weather, and plan investment in green infrastructure. Yet, leading UK scientists now warn that many economic climate models have a ‘faulty radar’—they miss key real-world complexities, which risks undermining effective policy. Many economic models currently used by governments assume linear, predictable reactions to climate change: damage rises steadily as temperatures climb, and the market corrects swiftly. But in reality, the impacts of climate disruption—from flooding in Yorkshire to heatwaves in London—can disrupt entire supply chains overnight and create feedback loops that models often miss. They usually underestimate ‘tail risks’—rare but catastrophic events. They often assume technology and the economy will adapt painlessly. Social impacts, like changing migration patterns or workforce health, are hard to factor in. A University of Exeter-led review highlights that these gaps can result in “grossly misleading” assessments of both the challenges and opportunities of the net zero transition. For example, positive feedback effects—where wildfires or melting ice amplify warming—are often left out. Likewise, the economic disruption from climate-driven migration or sharp shifts in food and energy prices needs better modelling. Underestimating these factors can lead to policy gaps. Consider: Flood prevention budgets—set too low if future risks are underestimated. Business investment in renewables—slower than required if models overestimate costs and underplay innovation potential. Insurance—premiums and coverage could be mispriced, leaving UK households and businesses exposed. Scientific and policy leaders now stress the need for more dynamic approaches. Next-generation models for the UK should: Account for non-linear, abrupt changes (“tipping points”). Consider social and environmental disruption beyond GDP—like public health or ecosystem damage. Regularly update assumptions about technology costs and adoption rates. Be transparently available for scrutiny and updating. For policymakers, this means future-proofing investment and regulation—factoring in a wider range of scenarios, not just optimistic or ‘mainstream’ projections. Businesses and investors should demand and use more nuanced data when planning climate risk responses, especially for resilient infrastructure and supply chains. Reliable models are vital to steer the UK towards a low-carbon, resilient future. They must combine deep scientific understanding of climate risks with realistic economic scenarios. With better models, the UK can target investments wisely, strengthen resilience, and secure a fair transition to net zero for all.
