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The blame for rain is mainly done in vain

As a climate scientist, it seems for every extreme event - be it the recent hottest 12 months on record for Australia or the floods and heavy rains of 2011 and 2012 - one question is inevitably asked…

Attributing heavy precipitation to climate change isn’t that easy. LordKhan/Flickr

As a climate scientist, it seems for every extreme event - be it the recent hottest 12 months on record for Australia or the floods and heavy rains of 2011 and 2012 - one question is inevitably asked: is human-made climate change to blame?

That is the wrong question.

It is impossible to say whether any single weather event was caused by man-made climate change. What we can do is examine whether the human influence on the climate has increased (or decreased) the odds of certain types of severe weather events happening.

The branch of climate science that looks at this is called attribution studies. Attribution research follows similar methods to those used in epidemiology.

Epidemiologists look at the patterns of disease in communities over a period of time to see where unusual outbreaks may have occurred and to determine what changes in the community might have led to these outbreaks. They may not be able to identify a single case of disease as being caused by the change but they can show that the change has caused the incidences of certain diseases to increase – and even define by how much.

Climate scientists take a similar approach, looking at the patterns and trends of climatic observations over a period of time to see why unusual or persistent weather patterns have changed and to determine what may have caused these changes.

Like epidemiologists, climate scientists cannot identify a single incident as being caused by climate change but they can define within a margin of error whether or not climate change has contributed to the likelihood of these events occurring.

Attribution, it’s just not cricket

To get a sense of how these kinds of attribution studies are applied we can take Australia’s national pastime, cricket, as an example.

Consider a cricketer who starts taking performance-enhancing drugs. Suddenly he hits 50% more boundaries in this season than he did in the last one.

For any single four or six he belts back over the bowler’s head, it would be impossible to say with certainty that one particular shot was made because of the drugs he was taking.

However, we might be able to say that the probability of this cricketer hitting a boundary has increased by 50%, supposing nothing else has changed in his performance.

This is exactly the approach we take to weather events. And certainly, it is useful when it comes to detecting the influence of global warming on large-scale periods of intense heat, as we have experienced over the past 12 months.

However, attributing precipitation events, such as rain and snow, to climate change is a much harder task.

The challenge of drying clothes

The relatively frequent experience of hanging your clothes outside to dry can help explain why.

Many of us may recall the feeling of coming home worried about leaving our washing outside when it’s been pouring with rain close to where we work.

Sometimes we get lucky (although not always!) and, despite passing through showers and storms on the trip back home, our clothes are still dry because it hasn’t rained where we live.

This is completely different to temperature extremes - if it is hot at work, it’s more than likely hot at home.

In short, extreme temperatures generally occur more uniformly over a wide area when compared to intense, localised rainfall events. For this reason, climate models fail to capture extreme precipitation events as well as they capture extreme temperatures.

Climate change and our long wet summers

This is also the reason that two studies into south-east Australia’s wet summers in 2010-2011 and 2011-2012 drew slightly different conclusions.

Figure 1: Summer 2011-2012 was exceptionally wet over parts of Australia.

In the study that my colleagues and I used to investigate these summers, we applied the same kind of methods described above to analyse these extreme weather events.

We looked at the wet summers of 2010-11 and 2011-12 over south-east Australia and tried to assess whether the probability of this kind of extreme rainfall event occurring had altered due to climate change.

It is important to note, these exceptionally wet periods coincided with two consecutive La Niña phases of the El Niño-Southern Oscillation (ENSO). La Niña events are typically associated with cool, wet summers in eastern Australia and therefore may by themselves be likely to be “blamed” for the heavy rains rather than additional human influences.

We used several state-of-the-art climate models to perform this analysis, so we could examine multiple possible realisations of the past century and a half.

All of these models had greater greenhouse gas concentrations later on in the model runs than they did at the beginning to coincide with observed changes over the past century. This meant we could compare extreme rainfall events near the start and end of the model runs to see if heavy rainfall events in south-east Australia had become more (or less) likely.

In the end, we couldn’t find much evidence that the human influence on the climate had played a significant role in these kinds of extreme rainfall events occurring over south-east Australia. In fact natural climate variability related to ENSO was shown to have a far greater influence than the effect humans have had on the climate.

Figure 2: Man-made influences on the climate (left) have less impact on extreme rainfall than ENSO variability (right).

Our study has been featured in the latest issue of the Bulletin of the American Meteorological Society (BAMS), which is devoted to similar analyses looking at other recent extreme weather events, such as the droughts in the central US and the record Arctic sea ice minimum of last year.

By contrast, another study of similar events published in this issue of BAMS found a small influence from man-made climate change on above-average rainfall that fell in March 2012 in eastern Australia (increasing the probability of a wet March by 5-15%).

On the face of it, our study and this one may appear to have reached different conclusions. However, this is not the case.

The two investigations of Australian extreme rainfall events used different methodologies and applied to slightly different regions and time periods.

They both agreed that natural climate variability was the main driver of the heavy rainfalls. While our study found a small and non-significant human influence, the latter study also found that any human influence was likely to be relatively small.

So, while some recent studies have clearly detected substantial human influences on extreme temperatures across Australia, including the record summer temperature of 2012-13 and the record temperature for the last 12 months, the ability to detect the human-induced effects on extreme precipitation events over our continent remains elusive.