The past is the key to predicting the future climate – Models should be tested by simulating past climates

The inclusion of paleoclimatic data in the development of climate models could help climatologists predict future climate scenarios and suggest mitigation strategies.

An international team of climatologists suggests that research centers around the world using numerical models to predict future climate changes should include simulations of past climates in their assessment and reporting of their model’s performance.

“We urge the community of climate model developers to pay attention to the past and actively involve it in forecasting the future,” said Jessica Tierney, lead author of the article and associate professor in the geosciences department at the ‘University of Arizona. “If your model can accurately simulate past climates, it will probably do a much better job of getting the right future scenarios. “

As more and more information of better quality becomes available about climates in Earth’s distant history, stretching back millions of years before human existence, past climates are increasingly becoming relevant to improving our understanding of how key elements of the climate system are affected by greenhouse gas levels, according to the study’s authors. Unlike historical climate records, which typically only go back a century or two – a nod to the planet’s climatic history – paleoclimates cover a much wider range of climatic conditions that can inform climate models. in a way that historical data cannot. These periods of Earth’s past cover a wide range of temperatures, precipitation patterns, and ice sheet distribution.

“Past climates should be used to evaluate and refine climate models,” Tierney said. “Looking to the past to shed light on the future could help reduce uncertainties around projections of changes in temperature, ice caps and the water cycle. “

Typically, climatologists evaluate their models with data from historical weather records, such as satellite measurements, sea surface temperatures, wind speeds, cloud cover, and other parameters. The model algorithms are then adjusted and adjusted until their predictions match the observed climate records. Thus, if a computer simulation produces a historically accurate climate on the basis of observations made during this period, it is considered to be able to predict the future climate with precision.

“We find that many models work very well with historical climates, but not so well with climates from Earth’s geological past,” Tierney said.

One of the reasons for the discrepancies is the differences in the way models calculate the effects of clouds, which is one of the big challenges in climate modeling, Tierney said. Such differences cause the different models to diverge from each other in terms of what climatologists call climate sensitivity: a measure of how strongly Earth’s climate responds to a doubling of greenhouse gas emissions.

Several of the latest generation models that are being used for the next report of the Intergovernmental Panel on Climate Change, or IPCC, have higher climate sensitivity than previous iterations, Tierney explained.

“That means if you double the carbon dioxide emissions they produce more global warming than their previous counterparts, so the question is: how much confidence do we have in these new, very sensitive models? “

Between IPCC reports, which are typically published every eight years, climate models are updated based on the latest research data.

“Models are getting more complex and in theory they are getting better, but what does that mean? Tierney said. “You want to know what’s going on in the future, so you want to be able to trust the model as to what’s going on in response to higher levels of carbon dioxide. “

While there is no debate in the climate science community about human consumption of fossil fuels pushing the Earth to a warmer state for which there is no historical precedent, different models generate varying predictions. . Some predict an increase of up to 6 degrees Celsius by the end of the century.

Tierney said that although Earth’s atmosphere has experienced concentrations of carbon dioxide much higher than the current level of around 400 parts per million, there is no time in the geological record that matches the speed to which humans contribute greenhouse gas emissions.

In the article, the authors applied climate models to several climate extremes known to the past from geological records. The most recent warm climate offering a glimpse of the future occurred around 50 million years ago during the Eocene epoch, Tierney said. Global carbon dioxide was at 1,000 parts per million at that time and there were no large ice caps.

“If we don’t cut emissions, we are heading for Eocene-type CO₂ levels by 2100, ”Tierney said.

The authors discuss climate change until Cretaceous period, around 90 million years ago, when dinosaurs still ruled the Earth. This period shows that the climate can get even hotter, a scenario Tierney described as “even scarier”, with carbon dioxide levels up to 2,000 parts per million and the oceans as hot as a bathtub. .

“The key is CO₂“said Tierney.” Whenever we see evidence of a hot climate in the geological records, the CO₂ is also high.

Some models are much better than others at producing the climates seen in geological records, underscoring the need to test climate models against paleoclimates, the authors said. In particular, warm climates of the past such as the Eocene highlight the role clouds play in contributing to warmer temperatures under increased levels of carbon dioxide.

“We urge the climate community to test models on paleoclimates early on, while models are under development, rather than afterwards, which tends to be the current practice,” Tierney said. “Seemingly small things like clouds affect the Earth’s energy balance significantly and can affect the temperatures produced by your model for the year 2100.”

Reference: “Past climates inform our future” by Jessica E. Tierney, Christopher J. Poulsen, Isabel P. Montañez, Tripti Bhattacharya, Ran Feng, Heather L. Ford, Bärbel Hönisch, Gordon N. Inglis, Sierra V. Petersen, Navjit Sagoo, Clay R. Tabor, Kaustubh Thirumalai, Jiang Zhu, Natalie J. Burls, Gavin L. Foster, Yves Goddéris, Brian T. Huber, Linda C. Ivany, Sandra Kirtland Turner, Daniel J. Lunt, Jennifer C. McElwain , Benjamin JW Mills, Bette L. Otto-Bliesner, Andy Ridgwell and Yi Ge Zhang, November 6, 2020, Science.
DOI: 10.1126 / science.aay3701