A
new four-step “framework” aims to test the contribution of climate change to
record-setting extreme weather events.
BY KER THAN, Stanford University
After
an unusually intense heat wave, downpour or drought, Noah Diffenbaugh and
his research group inevitably receive phone calls and emails asking whether
human-caused climate change played a role.
“The question is being asked by the general
public and by people trying to make decisions about how to manage the risks of
a changing climate,” said Diffenbaugh, a professor of Earth system science at
Stanford’s School of Earth, Energy & Environmental
Sciences.
“Getting an accurate answer is important for everything from
farming to insurance premiums, to international supply chains, to
infrastructure planning.”
In
the past, scientists typically avoided linking individual weather events to
climate change, citing the challenges of teasing apart human influence from the
natural variability of the weather. But that is changing.
“Over the past decade, there’s been an explosion of research, to the point that we are seeing results released within a few weeks of a major event,” said Diffenbaugh, who is also the Kimmelman Family Senior Fellow at the Stanford Woods Institute for the Environment.
In a
new study, published in this week’s issue of Proceedings
of the National Academy of Sciences, Diffenbaugh and a group of current and
former Stanford colleagues outline a four-step “framework” for testing whether
global warming has contributed to record-setting weather events.
The
new paper is the latest in a burgeoning field of climate science called
“extreme event attribution,” which combines statistical analyses of climate
observations with increasingly powerful computer models to study the influence
of climate change on individual extreme weather events.
Climate change
fingerprints
In
order to avoid inappropriately attributing an event to climate change, the
authors began with the assumption that global warming had played no role, and
then used statistical analyses to test whether that assumption was valid.
“Our
approach is very conservative,” Diffenbaugh said. “It’s like the presumption of
innocence in our legal system: The default is that the weather event was just
bad luck, and a really high burden of proof is required to assign blame to
global warming.”
The
authors applied their framework to the hottest, wettest and driest events that
have occurred in different areas of the world. They found that global warming
from human emissions of greenhouse gases has increased the odds of the hottest
events across more than 80 percent of the surface area of the globe for which
observations were available.
“Our
results suggest that the world isn’t quite at the point where every record hot
event has a detectable human fingerprint, but we are getting close,”
Diffenbaugh said.
For
the driest and wettest events, the authors found that human influence on the
atmosphere has increased the odds across approximately half of the area that
has reliable observations.
“Precipitation
is inherently noisier than temperature, so we expect the signal to be less
clear,” Diffenbaugh said. “One of the clearest signals that we do see is an
increase in the odds of extreme dry events in the tropics. This is also where
we see the biggest increase in the odds of protracted hot events – a
combination that poses real risks for vulnerable communities and ecosystems.”
The
Stanford research team, which includes a number of former students and postdocs
who have moved on to positions at other universities, has been developing the
extreme event framework in recent years, focusing on individual events such as
the 2012-2017
California drought and the catastrophic
flooding in northern India in June 2013.
In
the new study, a major goal was to test the ability of the framework to
evaluate events in multiple regions of the world, and to extend beyond extreme
temperature and precipitation, which have been the emphasis of most event
attribution studies.
Test cases
One
high-profile test case was Arctic sea ice, which has declined by around 40
percent during the summer season over the past three decades. When the team
members applied their framework to the record-low Arctic sea ice cover observed
in September 2012, they found overwhelming statistical evidence that global
warming contributed to the severity and probability of the 2012 sea ice
measurements.
“The
trend in the Arctic has been really steep, and our results show that it would
have been extremely unlikely to achieve the record-low sea ice extent without
global warming,” Diffenbaugh said.
Another
strength of a multi-pronged approach, the team said, is that it can be used to
study not only the weather conditions at the surface, but also the meteorological
“ingredients” that contribute to rare events.
“For
example, we found that the atmospheric pressure pattern that occurred over
Russia during the 2010 heat wave has become more likely in recent decades, and
that global warming has contributed to those odds,” said co-author Daniel
Horton, an assistant professor at Northwestern University in Evanston,
Illinois, and a former postdoc in Diffenbaugh’s lab who has led research on the influence
of atmospheric pressure patterns on surface temperature extremes.
“If
the odds of an individual ingredient are changing – like the pressure patterns
that lead to heat waves – that puts a thumb on the scales for the extreme
event.”
Diffenbaugh
sees the demand for rigorous, quantitative event attribution growing in the
coming years. “When you look at the historical data, there’s no question that
global warming is happening and that extremes are increasing in many areas of
the world,” he said.
“People
make a lot of decisions – short term and long term – that depend on the
weather, so it makes sense that they want to know whether global warming is
making record-breaking events more likely. As scientists, we want to make sure
that they have accurate, objective, transparent information to work with when
they make those decisions.”
Other authors on the study,
titled “Quantifying the influence of global warming on unprecedented extreme
climate events,” include Danielle Touma, Allison Charland, Yunjie Liu and Bala
Rajaratnam of Stanford University, and Stanford alumni Deepti Singh and Justin
Mankin (now at the Lamont-Doherty Earth Observatory of Columbia University);
Daniel Swain and Michael Tsiang (now at the University of California, Los Angeles);
and Matz Haugen (now at the University of Chicago). Funding was provided by the
U.S. National Science Foundation, the Department of Energy, the National
Institutes of Health and Stanford University.
