We’re living through an era of extremes – hotter heat waves, drier droughts, more inundating floods, and increasingly powerful storms to name just a few. Each time an event happens, the question arises: Is climate change the culprit? Much of the media coverage surrounding the recent record-breaking tornadoes across the Midwest wrestled with exactly that question

The costs of extreme events in terms of human suffering and lost capital are staggering and they’re only growing. Scientists have long known climate change is making extreme weather more frequent or more intense, but it has been difficult to pin a specific storm or heat wave on global warming. Without that connection, it’s harder for people to grasp the ways in which climate change impacts their lives.

Today’s 24-hour media cycles and social media frenzy create a constant headline churn. How much discussion do devastating 2021 events like Hurricane Ida in August, or the October Caldor Fire still generate? To catch people’s attention and educate the public, climate researchers must produce timely research that accurately demonstrates how a warmer climate contributed to these disasters.  

Now, innovations in climate research are helping to make that possible.

Science as detective work

Identifying human “fingerprints” for a single event is more difficult than attributing human-driven climate change to multiple events that indicate a global trend (as the Intergovernmental Panel on Climate Change does with increasing confidence for many extremes). Yet for decades scientists have been honing methods needed to detect buried clues within the data.

“Attribution” studies, as they are called, work by comparing observational records of the actual climate (with current, human-caused greenhouse gas emissions levels) with a computer-simulated counterfactual climate (without these human-generated emissions). Real-world events that significantly exceed ranges of variability from the counterfactual climate reveal clearer fingerprints of human influence.

Put simply, if a real-world event is unlikely to occur in a simulated model not having increased GHG levels, human-caused climate change is more likely a culprit.

… the importance of ‘clear, timely communication’

Scientists are now finding new ways to produce these attribution studies. Analytical advances, along with better communication of the findings, make attribution studies a meaningful tool for impacted communities, policymakers, and the media in the wake of a particular extreme event. Clear, timely communication matters as we seek to understand our changing world and build the necessary political will to enact policies that will prevent the worst impacts of climate change.

Attribution studies dust for ‘fingerprints’

A team of scientists, working as World Weather Attribution (WWA), is transforming how attribution studies are produced, opening up enormous opportunities to better communicate about climate change to broader audiences.

WWA leverages peer-reviewed methods with considerations for how best to communicate the outcomes of each study. A pioneer in this space, Geert Jan van Oldenborgh, who passed away last year, had spent much of his career advancing the physical science of attribution. Oldenborgh and his colleague’s most lasting impact may be how they constructed a workflow that could rapidly and credibly relay attribution science’s findings to larger audiences.

Take for example their study of this past summer’s heat wave in western North America. During those brutal June weeks, temperatures soared to as high as 121°F in British Columbia. At least 200 deaths in Oregon and Washington and more than 500 in British Columbia were recorded as heat-related.

WWA analysis of that event compared observations of the heatwave to the simulated climate of the region without elevated levels of  greenhouse gases. The authors found events like the 2021 western North America heatwave would be 150 times less likely to occur in a natural climate. Their analysis also showed extreme heat waves like those of the past summer could occur once every five to ten years in a simulated world with 2°C of climate warming – a future rapidly approaching, and one which national commitments made at the recent COP26 in Glasgow fall short of preventing.

Strikingly, this heat wave study was conducted and disseminated within just nine days of the event, light speed in the academic time-space continuum. In the past, similar studies have taken months or even years to complete. The enhanced speed of this process plays a critical role in helping the public better understand how climate change plays in extreme weather events.

Attribution studies can also improve understanding when climate change is not the culprit for extreme weather events, adding additional credibility to the studies overall. For example, analysis of recent droughts in Madagascar found it’s unlikely that climate change caused the dry spell to be so severe.

Creating new methods to better identify the ‘culprit’

The WWA attribution workflow is about more than just the attribution analysis, and herein lies its genius. Just as comparing observations and models is the core of attribution science, the workflow integrates other crucial steps that enable researchers to appropriately capture, and then quickly communicate, the many unique factors that influence an investigation in any single event.

For instance, the process begins with guidance on several judgment calls researchers must make. Extreme events are frequently occurring somewhere on the planet, so researchers first must decide which to study, given limited technical resources. They must also define each event in terms of climate variables, timing, and location. These decisions can be crucial to the outcome of the study and require careful, transparent selection procedures.

Having once decided to study a specific event, researchers must collect and analyze observed climate and weather data from the affected area. Some regions have better monitoring coverage than others. Importantly, reduced coverage, quality, or access to data can increase the amount of uncertainty about the extent to which a particular event exceeded historical levels. Low- and middle-income countries, lacking technical and financial resources to establish monitoring networks, more often lack access to quality data.

The physical impacts of some events can also directly impair monitoring equipment during an event itself, as was the case in the 2021 Western Europe floods, which destroyed long-term flood monitoring stations. Missing observations in that case prevented a full accounting of the magnitude of flooding, thus hampering the attribution analysis. However, instead of abandoning the attribution study altogether, the WWA approach incorporated this shortcoming into a set of modified analyses that found climate change a likely driver for flooding in the wider region (while being unable to say much about the specific location of the flooding).

The WWA workflow also includes guidance on how to select a set of climate models appropriate for the phenomena and region in question. Using only models capable of representing the phenomena and regional climate under study helps to ensure that conclusions about attribution based on the comparison between models and observations are not merely comparing apples to oranges.

In the communication of results, researchers ultimately try to pin down three data points if possible: 1) the probability the event would occur in the current climate, 2) the probability the event will occur in a future climate with elevated warming, and 3) an attribution statement of how (and how confidently) one can attribute the event to human-driven climate change.

As is often the case in science, these results come with caveats, such as when modeling or observational data is limited or when climate impacts result from compounding factors (e.g., fires are often the result of heat, wind, precipitation, and various forms of ignition). The WWA approach guides the translation of an analysis from focusing on a single climate variable into a wider discussion of the complex nature of hazards and vulnerability.

Changing perceptions to engage on climate action

So, what about the tornadoes in the midwestern U.S.? The jury is still out, in part because the two key ingredients for attribution studies – consistent observations and good representation in models – are spotty when it comes to tornadoes. But increasingly for events like heatwaves and heavy rainfall, attribution studies offer a vital tool to explain in a timely way what’s happening in the changing world, and why.

The human mind gravitates toward events in the here and now, commonly referred to as “the recency effect.”  Making the connection between extreme weather and climate change in the days after an event will have a stronger impact on people’s perceptions than doing so only months after the fact, therefore spurring further support for action to reduce atmospheric pollutants such as CO2. The WWA’s approach shows how the scientific community can apply new computing tools, and new approaches to engaging in a public service, making its research more actionable. Every fraction of degree of avoided warming will limit the damages that climate change causes, and this new field of study provides another way to help communicate the urgency.

James Arnott, Ph.D., is Executive Director of the Aspen Global Change Institute, and Greg Alvarez is Deputy Communications Director at Energy Innovation.