The model planet - Frans-Jan W. Parmentier

Imagine that by tomorrow, fossil fuel emissions have suddenly been reduced to zero. That, in some magical way, every car in the world is electric, we only generate electricity with sun, wind and water, and that chimneys of factories neatly capture CO₂ and store it underground. If so, has the planet been saved?

If the answer is yes, it's at the last moment, because the IPCC described in a recent report how much damage has already been done: the oceans are warming up and acidifying, sea level is rising, glaciers and ice sheets have retreated and sea ice is disappearing. Furthermore, it is unclear how many greenhouse gasses may be released from thawing permafrost - the frozen soils of the Arctic.

Another sobering fact: our climate problems are not immediately over when emissions are reduced to zero. The concentration of CO₂ in the atmosphere is unnaturally high, and it will take centuries for that surplus to be taken up again. Global warming will remain with us for the time being – unless we actively capture CO₂ from the air.

We know this thanks to climate models. If we look back at the initial forecasts of climate change by the IPCC, now 30 years ago, they are generally in line with the temperature rise that we have observed since then. That's a considerable achievement, since the models that were used were relatively simple of design at the time.

That solid foundation has been expanded ever since – by adding new knowledge about how our planet works, and by using more powerful computers. This allows us to predict, for example, how precipitation will change in the future, how the tree line in the mountains will move up while it gets warmer, and whether snow will fall later in the winter. But where climate models can predict the broad outlines of climate change, they are less focused on issues where detail is essential – such as the worldwide loss of biodiversity.

Climate models do not model individual species, such as blueberry or buttercup. To keep calculations efficient, nature is represented with roughly a dozen mathematical representations of groups of plants: conifers, deciduous trees, shrubs and grasses, and then subdivided into climate zones. A mountain meadow with flowers in all sorts of colors, humming insects and birdsong? In a climate model, it looks like a soccer field: a horizontal surface with one type of grass.

Is that a problem? Not so much when you use these models for what they are designed for: to simulate our changing climate. They are highly skilled at that, despite a simplified representation of reality. Or to quote a well-known statement from my field: "All models are wrong, but some are useful".

Scientists are well aware of this: We know that we must be hesitant to equate the logic of a model to what is the best solution in the real world. Unfortunately, the climate debate often goes astray at this point, when the nuance disappears and policy makers think that less CO₂ is the only measure of a better planet. Rather, a reduction in CO₂ emissions does not guarantee that the loss of biodiversity will stop. Sometimes it just makes this worse.

The international aviation organization (ICAO) announced last week that aviation should switch almost entirely to biofuels by 2050. That sounds like a great promise until you realise where all this biofuel will come from. The extra aerable land that is needed will most likely lead to the destruction of ecosystems and the loss of animal species.

Another example is the windmill debate in Norway: windmills are needed to meet the demand for clean energy, but in practice mountain landscapes are impacted by the construction of access roads while the blades are a deadly threat to birds. Ultimately, a megawatt of CO₂-neutral energy is easier to express in an Excel sheet than the difficult-to-quantify value of a small piece of nature.

With the right question, models can show us the way out of the climate crisis. But if success is only measured by a reduction in CO₂ emissions, other answers are not possible. In that case, we get ineffective solutions and unwanted side effects. Here lies a task for science to better communicate the limitations of our models. But there is also a responsibility for policymakers to listen more closely, not to forget the big picture, and above all: not to assume to know the answers beforehand.