Author: Site Owner

“The weather forecast looks sunny and particularly hot from Sunday to Friday, with afternoon temperatures above 30°C every day, and likely exceeding 35°C by the middle of the week. One consequence is that the poster sessions (Tuesday and Thursday) have been moved to the morning as they will be held outside under a marquee.”

I have never received a notification like this before a conference. And it was then followed up by a warning from the Guardian: ‘Hell is coming’: week-long heatwave begins across Europe.

The heatwave took place and was an appropriate frame for the International meeting on statistical climatology (IMSC), which took place in Toulouse, France (June 24-28). France set a new record-high temperature 45.9°C on June 28th, beating the previous record 44.1°C from 2003 by a wide margin (1.8°C).

One of the topics of this meeting was indeed heatwaves and one buzzword was “event attribution”. It is still difficult to say whether a single event is more likely as a result of climate change because of model inaccuracies when it comes to local and regional details.

Weather and climate events tend to be limited geographically and involve very local processes. Climate models, however, tend to be designed to reproduce more large-scale features, and their output is not exactly the same as observed quantity. Hence, there is often a need for downscaling global climate model results in order to explain such events.

A popular strategy for studying attribution of events is to run two sets of simulations: ‘factual’ (with greenhouse gas forcing) and ‘counterfactual’ (without greenhouse gas forcings) runs for the past, and then compare the results. Another question is how to “frame” the event, as different definitions of an event can give different indicators.

Individual heatwaves are still difficult to attribute to global warming because soil moisture may be affected by irrigation wheras land surface changes and pollution (aerosols) can shift the temperature. These factors are tricky when it comes to modeling and thus have an effect on the precision of the analysis.

Nevertheless, there is little doubt that the emerging pattern of more extremes that we see is a result of the ongoing global warming. Indeed, the results presented at the IMSC provide further support for the link between climate change and extremes (see previous post absence of evidence).

I braved the heat inside the marquee to have a look at the IMSC posters. Several of them presented work on seasonal and decadal forecasting, so both seasonal and decadal prediction still seem to be hot topics within the research community.

A major hurdle facing decadal predictions is to design climate models and give them good enough information so that they are able to predict how temperature and circulation evolve (see past post on decadal predictions). It is hard enough to predict the global mean temperature (link), but regional scales are even more challenging. One question addressed by the posters was whether advanced statistical methods improve the skill when applied to model output.

A wide range of topics was discussed during the IMSC. For instance, how the rate of new record-breaking events (link) can reveal trends in extreme statistics. There was one talk about ocean wave heights and how wave heights are likely to increase as sea-ice retreats. I also learned how severe thunderstorms in the US may be affected by ENSO and climate change.

Another interesting observation was that so-called “emergent constraints” (and the Cox et al, (2018) paper) are still debated, in addition to methods for separating internal variability from forced climate change. And there is ongoing work on the reconstruction of temperature over the whole globe, making use of all available information and the best statistical methods.

It is probably not so surprising that the data sample from the ARGO floats shows an ongoing warming trend, however, by filling in the spaces with temperature estimates between the floats, the picture becomes less noisy. It seems that a better geographical representation removes a bias that gives an underestimated warming trend.

While most talks were based on statistics, there was one that was mostly physics-based on the transition between weather regimes. Other topics included bias-adjustment (multi-variate), studies of compound events (straining the emergency service), the connection between drought and crop yields, how extreme weather affects health, snow avalanches, precipitation from tropical cyclones, uncertainties, downscaling based on texture analysis, and weather generators. To cover all of these would take more space than I think is appropriate for a blog like this.

One important issue was about data sharing which merits wider attention. The lack of open and free data is still a problem, especially if we want to tackle the World Climate Research Programme’s grand challenges. European and US data are freely available and the Israeli experience indicate that open access is beneficial.

This month’s open thread for climate science discussions.

Guest commentary by Michael Tobis, a retired climate scientist. He is a software developer and science writer living in Ottawa, Ontario.

A recent opinion piece by economist Ross McKitrick in the Financial Post, which attracted considerable attention in Canada, carried the provocative headline “This scientist proved climate change isn’t causing extreme weather – so politicians attacked”.

In fact, the scientist referenced in the headline, Roger Pielke Jr., proved no such thing. He examined some data, but he did not find compelling evidence regarding whether or not human influence is causing or influencing extreme events.

Should such a commonplace failure be broadly promoted as a decisive result that merits public interest?

ABSENCE OF EVIDENCE VERSUS EVIDENCE OF ABSENCE

Statistics is a vital tool of science, but it is not the only one. It is most effective when dealing with large quantities of data. Using statistical methods to detect the effect of one factor among several amounts to proving that the other factors did not align as a matter of happenstance. The more abundant the data, the less likely such a coincidence.

In the case of extreme weather, the number of sample points is small because extreme events by definition are rare. Up until the beginning of the satellite era, records of past events are often incomplete. There is little we can do to improve the amount of such data at hand. Because the data are irredeemably scarce, and time series short, using purely “frequentist” statistical methods to decide whether or not climate change makes a certain type of severe event more likely will tend to be inconclusive.

Limiting attention only to the most severe storms of a particular type, and then further limiting it to those causing the most extreme financial damage, drastically reduces the number of samples considered, and so further reduces the likelihood that a real trend will be detected.

It’s a well-known motto in research that “absence of evidence” is not “evidence of absence”. It’s well known because it is a common beginners’ error to conflate these. Scientists in training quickly learn that “we find no evidence of phenomenon P” is not the same as “we found evidence that phenomenon P is false”. The proposition in question could well be true but the analysis may lack have enough data to show it. (The test is said to be underpowered). Yet a systematic neglect of this simple point is pervasive among those skeptical of the risks of climate change.

Those who wish to avoid vigorous climate policy have gotten a lot of mileage out of inconclusive results.

HOW TO GET INCONCLUSIVE RESULTS

There is, along the periphery of climate science, an enthusiastic audience for null results: people who don’t want to accept the seriousness of climate risk will celebrate any absence of a demonstrated trend or inconclusive attribution. But it’s always possible to obtain a null result, i.e., a lack of statistical significance, if one seeks it, by reducing the amount of data under consideration.

Most science works the other way around, looking for relationships and trends that actually do seem to be happening! There is, under ordinary circumstances an audience for significant results. Were we not operating in a politicized context, detection would be considered more important than lack thereof.

To increase the likelihood of detection, we can look at larger categories of event. For example, in a 2013 report, the European Academies’ Science Advisory Council, examined trends in the specific extremes of heat and cold, precipitation, storms, winds and surges, and drought. The agency found evidence for “overall increases in the frequency and economic costs of extreme events”.

Much of Pielke’s work focuses largely on insurance costs of landfalling hurricanes in the USA, an especially rare phenomenon influenced by numerous factors and one with especially peculiar statistics. It’s an ideal field in which to get a null result, if that’s what the investigator is seeking.

An important point in looking at actuarial damages is that building standards and warning systems have systematically improved. In the absence of a climate-driven trend, we’d expect damages to decline. This counter-argument is made in many places, for example Dr. Kevin Trenberth in a book review:

“[Pielke] ignores the benefits from improvements in hurricane warning times, changes in building codes, and other factors that have been important in reducing losses.”

Another approach to hide climate-driven damage is to blur trends. We expect (from physical arguments and models) and find (from observations) increasing precipitation at higher latitudes and decreasing precipitation in dry subtropical latitudes. Aggregating them, the net result is no global trend in drought, and true to form McKitrick celebrates this result as well.

Aggregating such non-results and obscured results brings us to McKitrick’s sweeping conclusion.

“There’s no trend in hurricane-related flooding in the U.S. Nor is there evidence of an increase in floods globally. Since 1965, more parts of the U.S. have seen a decrease in flooding than have seen an increase. And from 1940 to today, flood damage as a percentage of GDP has fallen to less than 0.05 per cent per year from about 0.2 per cent. And on it goes. There’s no trend in U.S. tornado damage (in fact, 2012 to 2017 was below average). There’s no trend in global droughts. Cold snaps in the U.S. are down but, unexpectedly, so are heatwaves.”

McKitrick leaves the impression that all these conclusions are unequivocal, and that none of them have been hamstrung by approaches that are unlikely to yield significant trends.

Even at face value these specific claims, combined with a world-weary “and on it goes” isn’t enough to logically support his broad conclusion that “The bottom line is there’s no solid connection between climate change and the major indicators of extreme weather.”

Jumping from specific observations to a broad conclusion, as McKitrick does, is rhetorical, not scientific. In addition to being a logical fallacy, it ignores a great deal of evidence to the contrary. 

“This cow is black, and that one, and that one, and on it goes,” is not enough to prove that all cows are black when there are spotted cows aplenty in the field.

TIME AND TIDE

The evidence to the effect that there is a connection between anthropogenic climate change and increasing severe events, far from being absent, is in fact rapidly accumulating.

McKitrick makes much of Pielke’s role in a 2006 conference on severe weather which released a consensus document, the Hohenkammer Consensus, that was a fair assessment of knowledge at the time. That report asserts that “In the near future the quantitative link (attribution) of trends in storm and flood losses to climate changes related to GHG emissions is unlikely to be answered unequivocally.”

It is in exactly this pool of equivocality that Pielke has been content to operate. But is that pool shrinking?

Both science and climate change itself are advancing at a rapid pace. What was true in the “near future” of 2006 is not necessarily true today! So in using more advanced methods to study a more advanced disruption, has the situation changed?

In fact it has. Methods for attributing individual severe events partially to climate change have emerged. In 2016, the National Academy of Science of the USA issued a report entitled Attribution of Extreme Weather Events In the Context of Climate Change, which enumerates the ongoing efforts. Among its key conclusions:

“The ability to understand and explain extreme events in the context of climate change has developed very rapidly over the past decade. In the past, a typical climate scientist’s response to questions about climate change’s role in any given extreme weather event was, ‘We cannot attribute any single event to climate change.’ The science has advanced to the point that this is no longer true.”

While not without complexity or controversy, attribution studies are complex and subject to the usual debates and disagreements that evolving fields of science undergo. Such work is extensive and carried out by multiple research groups in multiple countries (see also Going To Extremes from this site).

The Bulletin of the American Meteorological Society has, since 2011, been releasing special issues on the subject of extreme event attribution. In recent issues, cases of severe events have been identified that would have been essentially impossible in the undisturbed climate. New examples have been published recently, indicating that heat waves in Europe and North America and in Japan couldn’t have occurred in the absence of human-caused climate change.

So McKitrick’s claim that “the bottom line is there’s no solid connection between climate change and the major indicators of extreme weather, despite Trudeau’s claims to the contrary” is at best out-of-date and ill-informed. Some might call it deceptive.

One can always dismiss evidence one doesn’t like as not “solid”, of course. But by now, there’s quite a lot of evidence to dismiss and McKitrick, rather than addressing it avoids any mention of any of it whatsoever. One expects better from an academic.

SO WHAT IS REALLY GOING ON?

While determining exactly which severe events are more likely already under climate change, and which will become so, we should begin by focusing on what is known currently.

Quoting from the aforementioned 2006 consensus document that McKitrick celebrates, it was already known that:

• Climate change is real, and has a significant human component related to greenhouse gases
• For future decades the IPCC (2001) expects increases in the occurrence and/or intensity of some extreme events as a result of anthropogenic climate change
• Direct economic losses of global disasters have increased in recent decades with particularly large increases since the 1980s
• There is evidence that changing patterns of extreme events are drivers for recent increases in global losses.

McKitrick leaves the reader with the impression that the report had other conclusions. The 2006 report only said that the reasonably inferred causality between human-caused climate change and increasing severe events wasn’t as yet proven.

Since the time of that conference, not only climate change but increases in the frequency of disruptive events have become rather obvious in many regions of the world, including Canada. The evidence has shifted remarkably. 

These are the troublesome events we expect, and many of these troubles appear to be happening with increased frequency and severity.

If someone argues, as they may, that the connection is not yet proven to their satisfaction, they may or may not have a case. Indeed, I (the author of this article) have expressed some concerns about the validity of the single-event attribution approach. But questioning an approach is one thing. To claim or imply that something is disproved by systematically ignoring evidence to the contrary is another thing entirely. To do so is to undermine discourse. It’s simply misleading and irresponsible.

WHAT ABOUT CANADA?

Environment and Climate Change Canada recently released “Canada’s Changing Climate Report”. As with most scientific consensus documents, it is careful to emphasize scientific uncertainty. Its opening sentence is nevertheless unequivocal: “There is overwhelming evidence that the Earth has warmed during the Industrial Era and that the main cause of this warming is human influence. “

Regarding the specific issues raised by McKitrick, the report’s conclusion is

“In the future, a warmer climate will intensify some weather extremes. Extreme hot temperatures will become more frequent and more intense. This will increase the severity of heatwaves, and contribute to increased drought and wildfire risks. While inland flooding results from multiple factors, more intense rainfalls will increase urban flood risks. It is uncertain how warmer temperatures and smaller snowpacks will combine to affect the frequency and magnitude of snowmelt-related flooding.”

Katherine Hayhoe, in an article in Chatelaine, a popular magazine published in Canada, points out that

“The Insurance Bureau of Canada estimates “catastrophic losses due to natural disasters have increased dramatically” over the last 10 years, with $1.9 billion of insured loss in 2018 alone. Extreme weather-related losses reported during the ’90s and 2000s averaged around half a billion dollars per year. Even leaving out damages from the record-breaking Fort McMurray wildfires, losses in the 2010s are still three times higher, averaging almost $1.5 billion per year through 2018.”

This is what climate science expects, and this is what we see. There are conflating influences  – more property value exists, and conceivably it is, for some extraneous reason, more at risk. Still the trend in Canada is particularly striking.

One can argue whether the connection is as yet “proven” in the sense of statistical hypothesis testing, but it’s far from being disproven. To the contrary, it is reasonable to expect the proof to continue to emerge.

SCIENCE, POLITICS AND REASON

Scientists, being humans living on the Earth, are not immune from political and policy preferences. While as scientists they are trained to resist such biases, no one denies that such influences exist and need to be considered. But this cuts both ways.

Of course, taking climate change seriously will require substantial shifts in public policy, and many are threatened by these, whether by direct financial motivation or a strong philosophical preference for laissez-faire organization of society. Those scientists who are most popular among those so threatened are ones who seem to actively look for inconclusive results. In doing so they may advance their own careers, but they hardly advance either science or public discourse.

When one-sided articles like McKitrick’s come out that are rife with logical fallacies, it’s more than a little bit ironic to see them accusing their opposition of bias.

Democracies, including Canada. historically have been especially capable of arguing about contentious issues from common values and shared understanding of facts. Recent adverse trends in political discourse have been very disturbing.

McKitrick’s article is a part of this disturbing trend – it amounts to a personal attack on Prime Minister Trudeau, selecting and bending facts to create a misleading conclusion. The attacks imply that the Prime Minister and his government are casually misinformed, and concede nothing to those with whom the author disagrees.

This is not the way to solve problems or maintain a civil society. Let’s do better.