The probable cause of the increase in global warming is clouded in the latest generation of climate models


Sky clouds

New cloud representations are making the models more sensitive to carbon dioxide.

As scientists work to determine why some of the latest climate models suggest the future may be warmer than previously thought, a new study indicates that the reason is likely related to challenges simulating the formation and evolution of clouds.

The new research, published in Scientific advances, offers an overview of 39 updated models that are part of a major international climate effort, the sixth phase of the Coupled Models Intercomparison Project (CMIP6). The models will also be analyzed for the next sixth evaluation report of the Intergovernmental Panel on Climate Change (IPCC).

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

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

“Many research groups have already published papers looking at 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 goal was to search for any topic that came up, especially with the highly sensitive models. What came up time and time again is that cloud feedbacks in general, and the interaction between clouds and small particles called aerosols in particular, seem to be contributing to increased sensitivity. “

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

Model sensitivity assessment

Researchers have traditionally evaluated the sensitivity of the climate model using two different metrics. The first, which has been in use since the late 1970s, is called equilibrium climate sensitivity (ECS). It measures the rise in temperature after atmospheric carbon dioxide doubles instantaneously from pre-industrial levels and the model is allowed to run until the weather stabilizes.

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

The CMIP6 models, however, have a range of 1.8 to 5.6 ° C (3.2 to 10 ° F), expanding the spread of CMIP5 at the low and high ends. The NCAR-based Community Earth System Model, version 2 (CESM2) is one of the most sensitive models, with an ECS 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 responses seem to boil down to clouds and aerosols. Cloud processes have been developed on very fine scales, making it challenging to simulate accurately on global scale models in the past. However, in CMIP6, many modeling groups added more complex representations of these processes.

New cloud capabilities in some models have produced better simulations in certain ways. The clouds in CESM2, for example, appear more realistic compared to the observations. But clouds have a complicated relationship to global warming: certain types of clouds in some places reflect more sunlight and cool the surface, while others can have the opposite effect, trapping heat.

Aerosols, which can be naturally emitted 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 model groups have determined that adding this new complexity to the latest version of their models is having an impact on ECS. Meehl said this is not surprising.

“When you put more detail into the models, there are more degrees of freedom and more different possible outcomes,” he said. “The models of today’s Earth system are quite complex, with many components that interact in ways that are sometimes not anticipated. When you run these models, you will get behaviors that you would not see in more simplified models. “

An immeasurable amount

ECS is meant to tell scientists something about how Earth will respond to increased atmospheric carbon dioxide. The result, however, cannot be compared to the real world.

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

One reason that scientists continue to use ECS is because it allows them to compare current models with early climate models. But the researchers have devised other metrics to analyze climate sensitivity along the way, including a model’s transient climate response (TCR). To measure that, modelers increase carbon dioxide by 1% per year, compound, until carbon dioxide doubles. While this measure is also idealized, it can offer a more realistic view of the temperature response, at least on the short-term horizon of the coming decades.

In the new paper, Meehl and colleagues also compared how TCR has changed 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 CMIP6 models it only increased slightly, from 1.3 to 3.0 ° C. Overall, the change in average TCR warming was almost imperceptible, from 1.8 to 2.0 ° C (3.2 to 3.6 ° F).

The change in TCR range is more modest than with ECS, which could mean that CMIP6 models may not work any differently than CMIP5 models by simulating temperature for decades to come.

But even with the broader range of ECSs, the average value for that metric “did not increase greatly,” said Meehl, who only increased from 3.2 to 3.7 ° C.

“The upper end is higher, but the lower end is lower, so the average values ​​have not changed too much,” he said.

Meehl also noted that the broader range of ECS 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 of how these interactions unfold in The real world.

“Cloud-aerosol interactions are at the limit of our understanding of how the climate system works, and it is challenging to model what we don’t understand,” Meehl said. “These modelers are pushing the limits of human understanding, and I hope this uncertainty will motivate the new science.”

Reference: “Context for interpreting equilibrium climate sensitivity and transient climate response of CMIP6 terrestrial system models” 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, Scientific advances.
DOI: 10.1126 / sciadv.aba1981