This morning, Copernicus, the Climate Change Service of the European Commission, confirmed that July was by far the hottest month ever recorded. After months of record-breaking temperatures, unprecedented ocean warming, and many rare and devasting extreme weather events, we have officially surpassed the 1.5°C limit for the first time.
With millions of people experiencing the effects of climate change firsthand, many probably wonder if climate change is happening faster than scientists had expected or if the current extreme weather events are more extreme than studies had predicted.
The short answer is no. In fact, the IPCC reports have shown us that models have accurately projected the rise in GHG levels and the global average temperatures. Some impacts, however, are accelerating much faster than expected.
And while current extreme events may reveal some model limitations, they shouldn’t be used to reject the warnings scientists have given us for decades. In fact, scientists have been warning us, in every way they could, that climate change will make our planet warmer, weirder and harder to predict.
Current IPCC climate models have predicted that extreme weather events are more likely to occur and more likely to be severe. But scientists have warned that these models do not give us the full picture and that they are currently underestimating the magnitude and frequency of extreme events and the impact they will have on natural and societal systems.
Scientists have repeatedly stated that current projections aren’t alarmist; they are too conservative still. And if governments and organisations worldwide are going to rely on these models as evidence to support their climate actions, they must be improved. And quickly.
Let’s discuss five reasons why current climate models underestimate extreme weather events.
- There is not enough data on extreme weather events: Each recorded extreme weather event results from a complex combination of factors and weather conditions, and because extremes do not happen frequently, it’s hard to get them into climate models. Current observations do not entirely match up with modelled projections, and with that, many scientists point out that current climate models underestimate the magnitude and frequency of such events.
- There isn’t enough computational power for reliable climate prediction: Regional temperatures and weather patterns are highly impacted by topography, land cover and land use, but these parameters are not well defined in current climate models. Because of a lack of computational power, models still divide the planet into relatively large blocks (cells up to several thousands of square kilometres), limiting the ability to predict local extreme events with high accuracy.
- There is not enough attention to tipping points and feedback loops: Even though climate models consider that temperature change isn’t uniform across the globe, the computed rate of warming is lagging far behind reality in certain areas. This is partly because climate models do not fully account for tipping points and feedback loops. With some natural systems pushed past their tipping points, certain areas already have a higher increased risk of heat and extreme weather events than the global models project.
- Models are biased and lack data on essential natural processes: The Arctic has warmed nearly four times faster than the global average, but climate models struggle to simulate this effect. Scientists stated that current models are biased because they contain incorrect data and assumptions on several critical Arctic and deep sea processes. For some of them, the models lack data because it’s complex and expensive to collect, but without it, models underestimate the impact and consequences of the systems.
- It’s not only the laws of physics, but also people’s behaviour we’re dealing with: Climate projections are based on physical data and assumptions. And while the assumptions in physical models are based on the laws of physics, social and economic models include assumptions about people’s behaviour, social norms and how the public perceives risk. While the latter contains many uncertainties, they influence our policies that determine which emission scenario we will follow and how much climate change we can expect.
- Slingo, J. et al. (2022). Ambitious partnership needed for reliable climate prediction
- Ripple, W.J. et al. (2023). Many risky feedback loops amplify the need for climate action
- Kornhuber, K. et al. (2023) Risks of synchronized low yields are underestimated in climate and crop model projections
- Rantanen, M. et al. (2022). The Arctic has warmed nearly four times faster than the globe since 1979
- Van Oldenborgh, G.J. et al. (2022). Attributing and Projecting Heatwaves Is Hard: We Can Do Better
- Heuzé, C. et al. (2023). The Deep Arctic Ocean and Fram Strait in CMIP6 Models