When people talk about “the climate model,” they often imagine a single, all-knowing simulation. In reality, climate modelling is not one model, but an ecosystem: a family of models, each addressing different parts of a complex system.
Different models, different lenses
Models act like lenses on the world. Some simulate atmosphere and ocean dynamics at the global or regional scale. Others focus on land use, vegetation, hydrology, or flood risks. Still others model energy systems, emissions pathways, or link climate processes with economic and social assumptions through integrated assessment models.
As our understanding of climate change has deepened, connecting these perspectives has become essential. Increasingly, models are not used in isolation but combined into integrated approaches that reflect the complexity of real-world interactions. Modern climate science, therefore, relies on model ensembles: many models, run under many scenarios. Reliability does not come from a single “perfect” model, but from consistent patterns across different approaches. The strength of climate modelling lies precisely in this plurality.
What models get right – and where they reach limits
Climate models have not only anticipated long-term warming trends; they have demonstrated predictive power far earlier than many assume. Already in the late 1970s, the Charney Report estimated that a doubling of CO₂ would lead to around 3°C of warming, a range still consistent with current science. Later projections from the 1980s and 1990s closely match observed temperature trends when actual emissions are considered.
Where models struggle is not with physics, but with human systems: political decisions, economic crises, wars, technological shifts, or behavioural change. These are not failures of modelling, but reminders that climate change is not purely a physical problem.
From future projections to present realities
More recently, climate modelling has entered a new phase: event attribution science. Using ensembles of climate models, researchers can now estimate how much more likely specific extreme weather events have become due to human-induced climate change. Studies coordinated by the World Weather Attribution (WWA) initiative show, for example, that recent heatwaves in Europe and North America would have been virtually impossible without anthropogenic warming, and that climate change has increased their likelihood by factors of ten or more.
These attribution studies do not claim that climate change caused a single event in isolation. Instead, they quantify how human emissions have shifted the odds, turning rare extremes into frequent risks. In doing so, climate models have moved from projecting distant futures to diagnosing present realities, directly linking global warming to lived experience.
What comes next:
In part 3 of our series on climate models, we explore why better models do not automatically lead to behaviour change and why their real value lies in supporting decisions under uncertainty, not predicting the future.
Haven’t read part 1? Start from the beginning to explore how climate models actually work and why understanding them differently matters.
About KNOWING
KNOWING is a Horizon Europe project that develops tools, models and participatory formats to support climate-transformation. By combining scientific analysis with local knowledge and stakeholder input, the project supports regions and sectors to understand climate risks, assess options, and design effective, inclusive pathways for change.