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Clouds are the likely cause of increased global warming in the latest generation of climate models

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Sky clouds

New representations of clouds make models more sensitive to carbon dioxide.

While scientists are investigating why some of the latest climate models suggest that the future may be warmer than expected, new research indicates that the reason is likely linked to challenges simulating cloud formation and evolution.

The new research, published in Scientists progress, provides an overview of 39 updated models that are part of a major international climate effort, the sixth phase of the coupled model comparison project (CMIP6). The models will also be analyzed for the upcoming sixth assessment report of the Intergovernmental Panel on Climate Change (IPCC).

Compared to older models, a subset of these updated models showed higher sensitivity to carbon dioxide – that is, more warming for a given concentration of greenhouse gases – although some also showed lower sensitivity. The end result is a wider range of model responses than any previous generation of models, dating back to the early 1990s. If the high-end models are correct and the Earth is really more sensitive to carbon dioxide than it is scientists had thought, the future could also be much warmer than expected. But it is also possible that the updates made to the models between the last comparison project and this one cause or expose errors in their results.

In the new article, the authors sought to systematically compare CMIP6 models with previous generations and to catalog the likely reasons for the widening of the sensitivity range.

“Many research groups have already published articles analyzing the possible reasons why the climate sensitivity of their models changed when they were updated,” said Gerald Meehl, senior scientist at the National Center for Atmospheric Research (NCAR ) and lead author of the new study. “Our objective was to research emerging themes, in particular with high-sensitivity models. The thing that has come up over and over again is that cloud feedbacks in general, and the interaction between clouds and tiny particles called aerosols in particular, seem to contribute to higher sensitivity. “

The research was funded in part by the National Science Foundation, which is the sponsor of NCAR. Other supporters include the United States Department of Energy, the Helmholtz Society, and the Deutsches Klima Rechen Zentrum (climate computing center in Germany).

Model sensitivity assessment

Researchers have traditionally assessed the sensitivity of the climate model using two different measures. The first, which has been used since the late 1970s, is called climatic equilibrium sensitivity (ECS). It measures the increase in temperature after atmospheric carbon dioxide has instantly doubled from pre-industrial levels and the model is allowed to operate until the climate stabilizes.

Over the decades, the range of DHW values ​​has remained remarkably consistent – somewhere between 1.5 and 4.5 degrees Celsius (2.7 to 8.1 degrees Fahrenheit) – even as the models have become much more complex. For example, the models included in the previous phase of CMIP for the past decade, known as CMIP5, had ECS values ​​ranging from 2.1 to 4.7 ° C (3.6 to 8.5 ° F) .

CMIP6 models, however, have a range of 1.8 to 5.6 ° C (3.2 to 10 ° F), widening the spread of CMIP5 at both the low and high ends. The community terrestrial system model based on NCAR, version 2 (CESM2) is one of the models with higher sensitivity, with a DHW value of 5.2 ° C.

Model developers have been busy selecting their models for the past year to understand why ECS has changed. For many groups, the answers seem to boil down to clouds and aerosols. Cloud processes take place at very fine scales, which has made it difficult to accurately model models globally in the past. In CMIP6, however, many modeling groups have added more complex representations of these processes.

The new cloud capabilities of some models have produced better simulations in some respects. Clouds in CESM2, for example, appear more realistic compared to observations. But clouds have a complicated relationship to global warming – some types of clouds in some places reflect more sun, cooling the surface, while others can have the opposite effect, trapping heat.

Aerosols, which can be emitted naturally by volcanoes and other sources as well as by human activity, also reflect sunlight and have a cooling effect. But they also interact with clouds, changing their formation and brightness and, therefore, their ability to heat or cool the surface.

Many modeling groups have determined that adding this new complexity to the latest version of their models has an impact on ECS. Meehl said it was not surprising.

“When you put more details into the models, there are more degrees of freedom and more different results possible,” he said. “Models of the Earth system are quite complex today, with many components interacting in unexpected ways. When you run these models, you will get behaviors that you wouldn’t see in more simplified models. “

An immeasurable amount

The ECS is supposed to explain to scientists how the Earth will react to the increase in atmospheric carbon dioxide. The result, however, cannot be compared to the real world.

“ECS is an immeasurable amount,” said Meehl. “It’s a rudimentary metric, created when the models were much simpler. It’s always useful, but it’s not the only way to understand how the increase in greenhouse gases will affect the climate. “

One of the reasons why scientists continue to use ECS is that it allows comparison of current models to early climate models. But the researchers found other measures to study climate sensitivity along the way, including a model’s transient climate response (TCR). To measure this, modellers increase carbon dioxide by 1% per year, compound, until the carbon dioxide is doubled. Although this measurement is also idealized, it can give a more realistic vision of the temperature response, at least on the short-term horizon of the next decades.

In the new document, Meehl and colleagues also compared the evolution of TCR over time since its first use in the 1990s. CMIP5 models had a TCR range of 1.1 to 2.5 ° C, while the range of the CMIP6 models increased only slightly, going from 1.3 to 3.0 ° C. On the whole, the variation of the average heating of the TCR was almost imperceptible, going from 1.8 to 2.0 ° C (3.2 to 3.6 ° F).

The change in the TCR range is more modest than with ECS, which could mean that the CMIP6 models may not function differently from the CMIP5 models when simulating temperature over the next decades.

But even with the widest range of DHW, the average value for this metric “has not increased enormously,” said Meehl, dropping only from 3.2 to 3.7 ° C.

“The high end is higher but the low end is lower, so the average values ​​haven’t changed too much,” he said.

Meehl also noted that expanding the range of DHW could have a positive effect on science by stimulating more research on cloud processes and cloud-aerosol interactions, including field campaigns to collect better observations. about how these interactions take place in the real world.

“Cloud-aerosol interactions are at the forefront of our understanding of how the climate system works, and it’s a challenge to model what we don’t understand,” said Meehl. “These model makers are pushing the boundaries of human understanding, and I hope this uncertainty will motivate new science.”

Reference: “Context for interpreting climate sensitivity to equilibrium and transient climate response from models of the CMIP6 terrestrial system” by Gerald A. Meehl, Catherine A. Senior, Veronika Eyring, Gregory Flato, Jean-Francois Lamarque, Ronald J. Stouffer, Karl E. Taylor and Manuel Schlund, June 24, 2020, Scientists progress.
DOI: 10.1126 / sciadv.aba1981

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