Clouds to further exacerbate climate crisis as world heats up and carbon dioxide levels soar

Clouds reflect the Sun’s energy, but can also insulate our planet too

Clouds play a complex role in the Earth’s changing climate. Cloud cover can reflect light from the sun back into space, helping keep the planet cool, but they are also huge stores of water which can serve as insulation – keeping things warm.

But alarming new research based on satellite measurements suggests that over the long term clouds will amplify global heating more than they will act to reduce it, further exacerbating the climate crisis.

Scientists at Imperial College London said their results suggest that as the concentration of carbon dioxide (CO2) builds up, and hits double what it was in the pre-industrial era, average global temperatures are unlikely to remain just 2C above what they were back before the 18th century, and instead are now more likely reach more than 3C.

Understanding how clouds will change as the level of carbon dioxide (CO2) in our atmosphere builds up is crucial for creating effective climate models and helping humans mitigate some of the impacts of the worsening climate crisis.

Pre-industrial CO2 levels were around 280 ppm (parts per million), but current levels are approaching 420 ppm, and could approach double the pre-industrial amount by 2050 if significant emissions cuts are not made.

The amount of average global heating predicted from a doubling of pre-industrial CO2 levels is known as the “climate sensitivity” – a measure of how strongly our climate will react to such a change.

Study co-author Dr Paulo Ceppi, from the Grantham Institute at Imperial, said: “The value of the climate sensitivity is highly uncertain, and this translates into uncertainty in future global warming projections and in the remaining ‘carbon budget’ – how much we can emit before we reach common targets of 1.5C or 2C of global warming.

“There is therefore a critical need to more accurately quantify how clouds will affect future global warming. Our results will mean we are more confident in climate projections and we can get a clearer picture of the severity of future climate change. This should help us know our limits – and take action to stay within them.”

Low clouds tend to have a cooling effect, as they block the sun from reaching the ground. High clouds, however, have a warming effect, as while they let solar energy reach the ground, the energy emitted back from the Earth is different. This energy can then be trapped by the clouds, enhancing the greenhouse effect. Therefore, the type and amount of cloud a warming world will produce impacts further warming potential.

The research was inspired by ideas from advances in artificial intelligence, the researchers said.

The team developed a new method to quantify relationships between state-of-the-art global satellite observations of clouds, and the associated temperature, humidity and wind conditions.

From these measurements, they were then able to better forecast how clouds will change as the Earth warms, and what the effect could be.

They found it was likely (more than 97.5 per cent probability) that clouds will amplify global heating, by both reflecting less solar radiation and enhancing the greenhouse effect.

These results also suggest a doubling of CO2 concentrations will lead to around 3.2C of average global heating.

The researchers said this is the highest confidence of any study so far, and is based on data from global observations, rather than local regions or specific cloud types.

Co-author Dr Peer Nowack, from the University of East Anglia and Imperial’s Grantham Institute and Data Science Institute, said: “Over the last few years, there’s been a growing amount of evidence that clouds probably have an amplifying effect on global warming.

“However, our new approach allowed us for the first time to derive a global value for this feedback effect using only the highest quality satellite data as our preferred line of evidence.”

He added: “Our paper makes a major step towards narrowing the most important uncertainty factor in climate sensitivity projections. As such, our work also highlights a new pathway in which machine learning methods can help us constrain the key remaining uncertainty factors in climate science.”

The study is published in the Proceedings of the National Academy of Sciences.