Extreme event attribution

We examine extreme weather events to identify the proportion of economic losses that can be attributed to human-induced climate change.

Brown flood water surrounds an old stone building with half-submerged cars
Extreme weather events are becoming more common (Image: Chris Gallagher, Unsplash)

We partner with international attribution scientists and economics of disaster scientists to study the cost of climate change.

Extreme event attribution defined

When extreme weather events occur, the question often arises whether the event is due to climate change. Extreme event attribution tries to answer this question.

Extreme event attribution is a relatively new field in climate science. It sits at the intersection of statistics, atmospheric physics, and geography. It aims to describe how much the probability of an event, like a drought or flood, depends on climate change.

The costs of climate change

Events like droughts, floods, and storms cause untold damage. The climate crisis is changing the frequency of these events, and they are becoming more damaging. But how can we quantify the role and impact of climate change in these events?

It is in fact possible to calculate the current economic costs attributable to climate change through extreme weather events. We do this by combining an economic assessment of damage from natural disasters with an atmospheric science assessment of the increased probability these events will occur.

Our research

One of our strands of research investigates the climate change cost of Hurricane Harvey—a Category 4 hurricane that struck Texas and the Caribbean in 2017, causing catastrophic flooding. In this project, we showed that these quantifications suggest that the mainstream economic estimates of the cost of climate change are most likely severely underestimated.

In another strand of research, we calculated a measure of the degree to which human-induced climate change affected the chance of a number of extreme events in New Zealand between 2007 and 2017. We combined these assessments with existing estimates of economic costs associated with these events to examine what fraction of the costs of these extreme events can be attributed to human influence on the climate.

Assessing probability

To determine whether the probability of extremes has increased, we start by comparing different types of long-time series data (for example, observations and climate models).

The second step involves determining the probability of the extreme event in the recent climate in the “normal” period and its probability in the past when the concentration of greenhouse gases (GHGs) was much lower. We use n model-based approaches to simulate and compare weather and climate phenomena with and without human-caused changes in GHGs.

For determining the probabilities, we use observational data, fit a Generalised Extreme Value Distribution (or other statistical distributions), and determine confidence intervals. This allows us to determine whether there are significant changes or trends in the occurrence of these extreme events.

Even if climate change is detected, for causal attribution, we need a link with a factor that is clearly influenced by increasing GHGs. The most obvious climate variable is temperature. Using a statistical approach, we factor in global warming by allowing the fit to the distribution to be a function of the global mean surface temperature (GMST). If there is a clear relation between the climate index under study and the GMST—and thus with the increase of GHGs—the probability of the climate index under study will have changed over time.