Climate change is being driven largely by the greenhouse gases we’ve pumped into the atmosphere, which trap more of the Sun’s energy there. This added energy increases the odds of extreme events: longer, more intense heat waves and droughts, interspersed with excessive precipitation. But these sorts of events have happened in the past—how can we tell if any given weather disaster has been made more likely by the climate? It’s a question with implications for everything from building codes to disaster preparedness.
According to a report released by the US National Academies of Science on Thursday, the field of climate attribution is growing increasingly mature and can answer some questions for us with far greater confidence than it could just a decade ago. The report also notes that there are still important limits and suggests steps to address them.
Attribution science has been developed to try to answer these questions. At its simplest, it identifies the major atmospheric features associated with a weather event and then asks how often they occur in climate models under two scenarios: one with our present conditions and one without humanity’s greenhouse gas emissions. The difference in frequency within these two scenarios provides a measure of the influence of climate change.
This approach has been through peer review and has since been used to examine a wide variety of weather events, many of which show the fingerprint (or, in some cases, the fist print) of climate change. There have also been some instances where the methods don’t provide a clear picture.
Understanding the role of climate change in these events can be useful for more than satisfying public curiosity. A lot of our infrastructure and regulations are based on the patterns of events we’ve observed in the past. If those patterns no longer apply, then a lot of things need updating. Obvious examples include the drainage needed to handle typical precipitation or the temperatures a road material will need to tolerate without melting.
The National Academies of Science (NAS) have been called on to weigh in on the state of the field; one of its roles has traditionally been to evaluate complex areas of science and provide a summary that policymakers can use. In fact, the NAS was asked to weigh in back in 2016, when the field was developing rapidly.
The report provides a great overview of how attribution analysis works, where it succeeds, and what challenges keep it from being effective in some circumstances. But one of the first things it makes clear is that the field has gotten better since the NAS last checked in. “Over the past decade, advances in physical understanding—through accumulating observational and modeling evidence supporting long-standing theoretical expectations—together with improved and more sophisticated numerical models, expanded observational datasets, and advanced statistical and machine-learning techniques, have strengthened the foundation for extreme event attribution,” the report’s authors write.
While there have been (and continue to be) new approaches developed for answering questions, the report says that most of the work is being done within one of two frameworks. The first is called “probabilistic,” which focuses on how climate change has altered the odds of a similar event occurring. The second is termed “storyline,” and is more focused on the specifics of the weather event (to give one example, the frequency of large hailstones) as well as the atmospheric conditions that make them possible.
That said, there are some clear limits to what we can do. The biggest of these is simply a lack of historical data. Weather monitoring in the pre-satellite era was not very consistent, and there are areas of the Earth, especially in the Global South, where we simply don’t have good enough records to
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