WILL FRONTLINE CONFRONT THE POWER OF HOT MODELS?

 NATURE  COMMENT 04 May 2022

Climate simulations: recognize the ‘hot model’ problem

The sixth and latest IPCC assessment weights climate models according to how well they reproduce other evidence. Now the rest of the community should do the same.

• Zeke Hausfather , 
• Kate Marvel , 
• Gavin A. Schmidt , 
• John W. Nielsen-Gammon & 
• Mark Zelinka

Computer models that project future climates are widely used for adaptation, mitigation and resilience planning. More than 50 such models were assessed and compared in the latest round of the Coupled Model Intercomparison Project, phase 6 (CMIP6), run by the World Climate Research Programme1. It is crucial that researchers know the best way to use those outputs to provide consistent information for climate science and policy.

We are climate modellers and analysts who develop, distribute and use these projections. We know scientists must treat them with great care. Users beware: a subset of the newest generation of models are ‘too hot’2 and project climate warming in response to carbon dioxide emissions that might be larger than that supported by other evidence3–7….

The CMIP6 models include more sophisticated treatments of ice, water and clouds than earlier ones did, including those in phase 5 (CMIP5). The latest models also include a wider variety of physical processes than before. As models become more realistic, they are expected to converge. In the meantime, individual improvements can affect how sensitive the models are to certain warming processes, in ways that are often impossible to predict.

The Intergovernmental Panel on Climate Change (IPCC), to its credit, has recognized this ‘hot model’ problem. Scientists contributing to the main sections of its Sixth Assessment Report (AR6; published over the past few months) reconciled the newest climate models with key observational constraints on global mean warming, sea-level rise and ocean heat content, and other analyses. They applied statistics to determine the most reasonable projections, consistent with many lines of evidence, which they call ‘assessed warming’.

Unfortunately, little guidance was made available for scientists wishing to study projections in other contexts. We are concerned that in the absence of such guidance, much of the scientific literature is at risk of reporting projections that are inconsistent with the approach taken by the IPCC, and that are overly influenced by the hot models.

Studies that cover monthly or daily extremes or regional climate impacts, for example, are instead left to use the full set of CMIP6 models. And simply taking an average of those leads to higher projections of warming than the IPCC’s assessed-warming averages. As a result, some studies have reported projections that might be inconsistent with AR6 assessments. Findings that show projected climate change will be ‘worse than we thought’ are often attributable to the hot models in CMIP6.

Hot tail

The largest source of uncertainty in global temperatures 50 or 100 years from now is the volume of future greenhouse-gas emissions, which are largely under human control. However, even if we knew precisely what that volume would be, we would still not know exactly how warm the planet would get. This is because human-caused global warming is an enormous experiment that has no precedent, and feedback processes, such as changes to cloud cover, will affect the pace and magnitude of warming.

To quantify the influence of these effects, climate modellers define standardized metrics. One is the transient climate response (TCR), or the amount of global warming in the year in which atmospheric CO2 concentrations have finally doubled after having steadily increased by 1% every year. A second metric is equilibrium climate sensitivity (ECS), the eventual long-term temperature response to CO2 concentrations that have doubled and remain doubled. The two metrics are distinct but related: ECS measures a long-term equilibrium climate response, whereas TCR measures a climate that has not yet had time to fully adjust2. Models with a high TCR tend to have a high ECS4.

Numerous studies have found that these high-sensitivity models do a poor job of reproducing historical temperatures over time and in simulating the climates of the distant past. Specifically, they often show no warming over the twentieth century and then a sharp warming spike in the past few decades and some simulate the last ice age as being much colder than palaeoclimate evidence indicates7...

Beyond model democracy

The climate community has debated what to do about the hot models since results began to appear in 2019. Before then, the IPCC and many other assessments simply used the mean and spread of models to estimate impacts and their uncertainties. Such ‘model democracy’ assumed that each model is independent and equally valid. Other methods of combining model projections did not yield results that were more consistent or credible9

In AR6, such simple methods no longer work: the high-sensitivity models are not as equally valid as others for estimating global temperature. AR6 authors decided to apply weights to each model before averaging them, to produce ‘assessed global warming’ projections. Specifically, the AR6 report used various published statistical weighting methods4–6 to combine the projections of different climate models, giving more weight to those that agreed with historical temperature observations.

They also used a climate model ‘emulator’ — a simpler model requiring less computing power — that incorporated the latest estimates of the sensitivity of the climate to CO2 emissions, based on lines of evidence beyond climate models. This approach provides a more realistic range of future warming projections, which are better constrained by observations than the raw CMIP6 model output, but are difficult for non-specialists to reproduce...

Nature 605, 26-29 (2022)

doi: https://doi.org/10.1038/d41586-022-01192-2