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BEN SANTER, HENRY JACOBY, RICHARD RICHELS, AND GARY YOHE
Hardly a day passes without a popular article describing the latest scientific study of rapid changes in Antarctic glaciers and ice shelves, or the latest research highlighting a possible slowdown of the ocean circulation systemthat warms eastern North America and Europe.
Such tipping point references are now so commonplace that it’s easy to lose focus on the serious environmental, economic and social threats they present.
The notion of a tipping point is that there are thresholds in a warming climate system — climatic “points of no return” which, if crossed, will have serious climatic, environmental and social consequences difficult to stop or reverse over a single human lifetime. Crossing certain tipping points might have irreversible climatic consequences for centuries.
Risks are magnified because these potential tipping points are not completely separate from one another; they are part of an interconnected climate system. The warming caused by exceeding one tipping point, such as the rapid thawing of Arctic permafrost and release of greenhouse gases, will inevitably have knock-on effects, possibly breaching other tipping points sensitive to warming.
The scientific and policy concern is that by burning fossil fuels and warming the planet, humanity is moving ever closer to triggering multiple climate tipping points. Yet our understanding of how near we are to those events is still disturbingly uncertain.
We’d want to know if a meteor were on course to hit the only planetary home we have. Advance knowledge gives us the possibility of taking countermeasures.
Likewise, we want the best possible scientific understanding of how continued global warming may affect such critical things as the stability of the West Antarctic Ice Sheet. A warming-induced collapse of just this one ice sheet could raise global sea levels by more than 10 feet over the coming centuries, altering the coastal zones where billions of people live.
The search for greater understanding of tipping points lies in three separate lines of evidence that are the basis for current concerns: paleoclimate data, present-day observations, and computer models.
Paleoclimate is the study of “deep time.” It relies on climate information covering spans of history ranging from hundreds to millions of years. This information is painstakingly teased out of ice cores, ocean sediment records, tree rings, coral reefs and other sources. Paleoclimate records show that tipping points do actually exist. These critical climate thresholds have been exceeded in the past without any human intervention — for example, as Earth has slowly warmed while coming out of an Ice Age.
Unfortunately, there’s no single time in paleoclimate records that had precisely today’s atmospheric levels of greenhouse gases, today’s geographical distribution of continents and ice sheets, and today’s orbital parameters (i.e., tilt and gyroscopic wobble of Earth’s axis, along with the shape of the Earth’s orbital path around the Sun). Nor is there any paleoclimate analog for the large and rapid human-caused increase in carbon dioxide since the Industrial Revolution.
While “deep time” information can give scientists valuable clues about what conditions might be influential in triggering tipping points, the direct relevance of those clues to today’s unique climatic situation is uncertain.
The second source of tipping point information comes from direct observations of climate conditions and processes that influence tipping points, or from measurements that record key aspects of tipping-point behavior. Examples include monitoring the melting of Antarctic ice shelves by ocean warming, studying the release of methane from thawing permafrost, and taking the pulse of ocean currents at various latitudes and depths of the North Atlantic. All of these measurements yield insights into rates of change, potentially providing some advanced warning of unusually rapid change — a possible sign of uncomfortable proximity to a tipping point.
But observations also have their problems. We may not be measuring the things that are most informative about tipping points, or measuring often enough, or long enough, or in the best places. We don’t have dedicated networks for making such measurements.
The final source of tipping point information comes from computer models of the climate system. They can be used to study the past and possible future behavior of tipping points. Models are run with estimates of “deep time” changes in greenhouse gas levels, continent and ice sheet configurations, and orbital properties. The output from such simulations can tell us something valuable about the ability of models to capture key aspects of tipping point behavior evident in paleodata.
Importantly, models are also run routinely with future changes in atmospheric concentrations of greenhouse gases based on different storylines of future population growth, energy use, technological advances and international cooperation. Model simulations of 21st century climate change can tell us how close we might be to passing tipping points, and what physical processes might kick in as we approach them.
Models, however, have their own problems. Although they are the product of many decades of scientific development, involving thousands of scientists around the globe, models represent the incredibly complex real-world climate system in simplified numerical form. There will always be climate processes “lost in translation” of that complex reality into computer code.
Furthermore, the divergent modeling approaches used by different researchers contribute to uncertainty in what models tell us about how fast are we approaching tipping points.
So how can we better determine this, and improve the now-poor communication between the climate modeling community, those making observations relevant to tipping points, and paleoclimate experts?
We believe that part of the answer to these questions involves applying “lessons learned” from three decades of evaluating climate models. Since the early 1990s, the climate science community has used so-called “model intercomparison projects” (MIPs) to answer key questions about climate model performance. How successfully do they reproduce today’s average climate? Over time, have models gotten better at reproducing today’s climate? Are there relationships between how well models simulate today’s climate and the large “spread” in their projections of 21st century climate change?
Large international model intercomparison projects have been valuable for answering these and many other scientific questions. But MIPs, and the lessons learned from them, have not really been applied to the study of tipping points. We don’t have a coherent scientific program for comparing tipping point behavior across today’s state-of-the-art climate models, to determine which models are most suitable and reliable for studying specific tipping points. We should.
We need a clear, sober and concerted scientific effort to understand the risks posed by exceeding tipping points. These risks are becoming more serious with every tenth of a degree of global warming. Investment in a better understanding of tipping point risks might be the best investment humanity could now make in the effort to preserve a livable planet.
Source: The Hill
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