We think about climate risk all wrong

This is in stark contrast to the IPCC’s prediction that the AMOC will weaken in the 21st century but “collapse is unlikely,” with only a 50/50 chance of a 2300 collapse in the high-emissions scenario.

Stefan Rahmsdorf, a professor of ocean physics at the University of Potsdam in Germany, said that although there is still “huge uncertainty where the AMOC reaches… in the next decade or two,” and “the conservative IPCC projections, based on stable climate models… in my view are now outdated.” “

Rahmsdorf added: “However, ‘unlikely’ in IPCC jargon only means less than 10 percent, and this is only limited certainty in the case of a high risk that you want to reject by 99.9 percent.”

One of the The main policy-making tools for the IPCC’s emissions reduction analysis and carbon budget creation are climate-energy-economy models known as Coupled Assessment Models. How Integrated Assessment Models deal with risk and uncertainty is a key question due to the political nature of it.

While the term “model” suggests technological neutrality, empirically constructed experimental models are in fact social constructs, where “the nature of the model depends on the modeler’s beliefs about social functioning.” They have the potential to privilege certain policy approaches and to entice policy makers to think that the predictions produced by the models and their approach to risk have some form of scientific validity.

But this is not the case. Joeri Rogelj, director of research at the Grantham Institute on Climate Change and Environment says: “What they are not, it is important to note, in the forecast or forecast of the future. “Therefore, the conditions in the IPCC database have no predictive power—and no amount of analysis, selection, or looking at spaghetti plots will change that.”

Integrated assessment models address the risk by providing a cost-benefit risk analysis in different scenarios for reducing emissions and energy options, and rely on the ability to calculate the extent of both the damage caused by climate disturbances, and the probability of such events. But this is a very flawed approach, because the damage is unpredictable, and the chances are deeply uncertain.

We don’t know have accurate estimates of the economic costs of future climate damage. Tom Kompas, a professor of environmental economics and environmental protection at the University of Melbourne, says that estimates of economic damage under different scenarios of global warming “are difficult to come by, except for simple, integrated measures taken from basic computational models… they are very misleading given their extreme bias and lack of transparency in general results. “

The International Monetary Fund notes a growing consensus among economists and scientists that “the risk of an irreversible disaster is increasing, reflecting the long-term costs of climate change, including human extinction.” And the 2020 report concludes that the overabundance of climate observatories “could lead to dangerous and irreversible impacts quantification of monetary damages is impossible” (emphasis added).

In other words, we can’t put a dollar figure on how much damage climate change will cause at the levels of warming we’re currently at. It is a state of “deep uncertainty” that occurs when decision makers and stakeholders do not know or disagree about the likelihood of different future scenarios.

Adding to the uncertainty are the system’s weather responses and advisory scores. Feedback occurs when a first change in a system, for example warming produced by carbon emissions, causes a second change that amplifies the first effect and reinforces it. An example is Arctic sea ice, which is retreating due to the burning of fossil fuels, but as the white heat-reflective ice is replaced by dark sea water, more heat is absorbed in this feedback loop.

In a complex system, second-order social impacts including armed conflict, government collapse, and mass migration are deeply uncertain. Climate change is a “disruptive” problem of irreversible damage and the risk of total failure, meaning that the negative consequences are not economically measurable and may pose an existential threat to human civilization.

Climate models they are complex sets of statistics about the real world—the sky, the oceans, and the land, and the carbon cycle, including human emissions—as much as they can. Climate science is a relatively new field, and as information has accumulated rapidly, models have become more accurate in describing what is likely to happen.

Models assume that all relevant processes can be measured in terms of a mathematical value, formula, or probability. A model estimate is generally defined as the most likely outcome, with a range to include uncertainty; for example: “predicted temperature is 2.4 C with a range of 1.6-3.2 C (95% probability).”

The models are good for linear processes, and are financially accurate in predicting future temperatures based on increasing emissions, for example. There is also a direct relationship between warming and the amount of moisture that can be carried by the wind: an additional 7 percent for each degree of increase of 1 degree Celsius and thus the volume of heavy rain events. Warm oceans can also produce strong hurricanes.

But assigning probabilities to static or sudden change events and tipping points is very difficult.

The problem is not about the lack of knowledge if the system will change if it is hot enough, but when. Current climate models do not capture all risks, and William Ripple and his researchers show that many of the positive responses are not fully accounted for in the models. This deficit covers the cryosphere (the frozen regions of the earth, such as glaciers and sea ice) and changes in other ocean and atmospheric circulation systems—including the Southern Ocean, the AMOC, the Arctic Jet Stream, and Greenland and the Antarctic ice sheets. .

If the damage is seriously uncertain, and the non-linearity limits the ability to assign probabilities to future events, then relying on integrated test models to provide a choice of actions is a very poor policy-making option.

When i very basic modern society and complex and fragile, the global network where co-existence is threatened, the usual method of risk management is not appropriate given the shortcomings of the current model, the largely unquantifiable nature of climate damage, and deep uncertainty.

But the main focus of the IPCC reports on the natural sciences has been the promotion of climate models at the center of the process, relegating to second place the understanding of the big picture from climate history (paleoclimatology). Paleoclimatology teaches that over time each degree of warming will raise the sea level by 10 to 20 meters, or about 30 to 65 feet. The models, which are unable to properly include cryosphere processes, suggest sea level rise by the year 2100 to be so small that the predictions are not credible, a scientific retreat emphasized by NASA’s head of science James Hansen since 2007.

In such circumstances, how can scientists and policy makers deal with questions of risk and profound uncertainty?

First, they need to understand the limitations of the Earth system and climate economic models and not give them the high status they don’t deserve. Other forms of information derived from past climate history should be given more weight, as should expert opinion. Asking a group of climate experts what they think is likely based on their knowledge and experience will produce a clearer picture than one drawn strictly from peer-reviewed literature where conclusions must be “beyond a reasonable doubt.”

Second, they need to understand that the highest potentials have the highest overall risks, and should receive special attention. Because climate change presents an existential risk to society, the focus is on one question above all others: “What is the best scenario and what should we do to prevent it?”

Writing about “the end of the climate game,” Luke Kemp from the Cambridge Center for the Study of Current Risk and his colleagues agree that “smart risk management requires consideration of the worst-case scenario” because it is likely to be lower, more affected. the consequences are so devastating that they cannot be explained. They say that the great uncertainty about the dangers of shock are “reasons to prioritize them rather than ignore them.”

But this is what the IPCC and climate research and risk managers in the financial system have largely failed to do. A new analysis shows that the potential to end humanity is “not viewed as dangerous” by the IPCC, a text analysis found that their assessments have shifted from high warming to focus on low temperature increases, such as “global warming could be ‘catastrophic.’ ‘ in society that the rise in temperatures is worse than most predicted or caused the occurrence of events that we have yet to consider, or indeed both” as noted by a paper published in the journal. Proceedings of the National Institute of Science. “We know very little about the most critical conditions,” Kemp said.

Policy makers and world leaders do not seem to understand that when there is risk, a negative outcome means that the future is extraordinarily different from the past. By underestimating the potential for serious harm, the IPCC and others are foolishly conducting an unprecedentedly dangerous experiment: how much warming—how much change—can humanity endure before it collapses?